Military Medicine

Rauch, Terry M

doi: 10.1093/milmed/usy354pmid: 30901462

The future battlespace demands advanced solutions. The delivery of medical care to troops deployed in this volatile, uncertain, and complex environment necessitates an investment in operationally focused research targeting prevention, treatment, and performance optimization. The ability to maintain a high quality of medical care over increased time and distance, in scenarios involving distributed operations and/or degraded or denied communications, while overcoming the associated logistics issues is a challenge being accepted, and met, by Department of Defense sponsored researchers and program managers. These efforts are faithfully augmented through the expertise and experience brought to the table by our partner nations, and by strategic alliances across academia, industry, and other Federal government agencies. Open in new tabDownload slide Terry M. Rauch, Ph.D. Acting Deputy Assistant Secretary of Defense (Health Readiness Policy and Oversight) Open in new tabDownload slide Terry M. Rauch, Ph.D. Acting Deputy Assistant Secretary of Defense (Health Readiness Policy and Oversight) The 1,728 abstracts presented in podium talks and posters at the 2017 Military Health System Research Symposium (MHSRS) is evidence to the dedication of our researchers in aggressively addressing the challenges to our Nation’s future operational medical readiness, and to the Department of Defense’s commitment to the Warfighter. Since 1993, as the Advanced Technology Applications meeting for Combat Casualty Care and later (since 2012) as MHSRS, this meeting has served as an incubator for nurturing collaborations that have developed into strong alliances focused on finding innovative solutions (e.g., formation of the Armed Forces Institute of Regenerative Medicine) and in product development partnerships resulting in Food and Drug Administration approved products for fielding (e.g., the first blood test that can be used to augment the diagnosis of Traumatic Brain Injury). This supplement to Military Medicine, along with its sister 2017 MHSRS supplement to the Journal of Trauma, are essential tools to communicate the significance of the Department of Defense’s research investment related to meeting future military medical operational challenges. I am delighted to lead off this important supplement and, in the process, recognize the men and women who perform the research, development, and acquisition mission of the Military Health System. Published by Oxford University Press on behalf of Association of Military Surgeons of the United States 2019. This work is written by (a) US Government employee(s) and is in the public domain in the US. Published by Oxford University Press on behalf of Association of Military Surgeons of the United States 2019.

Reilly, Patricia A; Hendrickson, Teresa L

doi: 10.1093/milmed/usy404pmid: 30901444

Capability gap, Warfighter, MHSRS, research This Military Health System Research Symposium (MHSRS) annual supplement to Military Medicine was first published in 2014 as a Proceedings to the 2012 meeting. That issue featured 11 articles presented over 70 pages. Since 2012, the MHSRS has grown in content and stature, with the number of scientific abstracts submitted tripling (from approximately 600 to 1,942), the number of breakout sessions increasing from 29 to 65, and meeting attendance doubling (from 1,463 to 2,810). (See Table 1 in The 2017 Military Health System Research Symposium Awards in this issue). That growth is paralleled by this Supplement, with submissions increasing annually in both number and quality with each MHSRS since 2012. This 2017 MHSRS Supplement to Military Medicine is the largest yet, and features 89 peer-reviewed articles presented over 550 pages. This issue presents articles from five of the 2017 Plenary speakers (Palmieri et al., Alam and Jeffery, Rossi and Nowak, Lowndes et al., and Rolland-Harris) and one 2017 poster award winner (Held et al.). All areas of Joint sponsored medical research are represented – combat casualty care (to include blast), infectious diseases, health information technology and medical simulation, radiation health, military operational medicine (human performance and psychological health), and clinical and rehabilitative medicine (pain management and sensory systems). The medical research sponsored by the U.S. Congress and the Department of Defense as well as our Allies is focused on supporting investigations pursuing the closure/narrowing of capability gaps impacting effective Warfighter medical care. The enormous complexities involved in carrying out these investigations is reflected in the scientific content of this issue, which serves as an annual account of the ongoing efforts towards the ultimate target - providing superior, technologically advanced, and life-saving medical pre-deployment, deployment, and post deployment medical care to those that serve in our defense. Patricia A. Reilly, Col, USAF (RET), Ph.D. Ms. Teresa L. Hendrickson, MAT Guest Editors 2017 MHSRS Supplement to Military Medicine Author notes The views expressed in this article are those of the author and do not necessarily reflect the official policy or position of the Department of the Navy, Department of Defense, nor the U.S. Government. Published by Oxford University Press on behalf of the Association of Military Surgeons of the United States 2019. This work is written by (a) US Government employee(s) and is in the public domain in the US. Published by Oxford University Press on behalf of the Association of Military Surgeons of the United States 2019.

Reilly, Patricia A

doi: 10.1093/milmed/usy391pmid: 30901423

MHSRS, Awards, Distinguished Service, Poster INTRODUCTION Twenty-two awards recognizing the year’s most outstanding individual and collective research accomplishments were presented at the 2017 MHSRS. These awardees are highlighted on the following pages. Congratulations to all of the investigators, and special thanks to the supervisors and co-workers who took the time to submit award packages for the individual and team achievement awards. In addition, Table I provides a comparison of various 2017 MHSRS statistics as compared to previous meetings. TABLE I. The Military Health System Research Symposium (MHSRS) Historical Data Number of: . 2012 . 2013 . 2014 . 2015 . 2016 . 2017 . Abstracts submitted ~600 520 1,135 1,196 1,539 1,942 Abstracts accepted 561 516 624 991 1,362 1,728 Abstract review panels 14 20 23 28 44 62 Breakout sessions (2 hours) 29 25 28 28 48 65 Breakout sessions (1 hour) 2 Posters presented 374 252 (number capped) 387 733 1,026 1,281 Award nomination packages N/A N/A 29 58 48 49 Young investigator submissions (Presented as 2 breakout sessions) Not a category 131 184 250 305 Paid attendees 1,463 1,175 1,524 2,004 2,319 2,810 International attendees No data No data 85 84 48 58 Exhibitors 90 80 76 71 82 97 Number of: . 2012 . 2013 . 2014 . 2015 . 2016 . 2017 . Abstracts submitted ~600 520 1,135 1,196 1,539 1,942 Abstracts accepted 561 516 624 991 1,362 1,728 Abstract review panels 14 20 23 28 44 62 Breakout sessions (2 hours) 29 25 28 28 48 65 Breakout sessions (1 hour) 2 Posters presented 374 252 (number capped) 387 733 1,026 1,281 Award nomination packages N/A N/A 29 58 48 49 Young investigator submissions (Presented as 2 breakout sessions) Not a category 131 184 250 305 Paid attendees 1,463 1,175 1,524 2,004 2,319 2,810 International attendees No data No data 85 84 48 58 Exhibitors 90 80 76 71 82 97 Originating as the US Army-sponsored Advanced Technology Applications for Combat Casualty Care meeting in 1993, the name was changed to the MHSRS in 2012, when the Assistant Secretary of Defense for Health Affairs became the sponsor, and the individual Service research meetings were rolled under the MHSRS. Note: Before 2014, award nominations were submitted as an e-mail message to the Planning Committee. Open in new tab TABLE I. The Military Health System Research Symposium (MHSRS) Historical Data Number of: . 2012 . 2013 . 2014 . 2015 . 2016 . 2017 . Abstracts submitted ~600 520 1,135 1,196 1,539 1,942 Abstracts accepted 561 516 624 991 1,362 1,728 Abstract review panels 14 20 23 28 44 62 Breakout sessions (2 hours) 29 25 28 28 48 65 Breakout sessions (1 hour) 2 Posters presented 374 252 (number capped) 387 733 1,026 1,281 Award nomination packages N/A N/A 29 58 48 49 Young investigator submissions (Presented as 2 breakout sessions) Not a category 131 184 250 305 Paid attendees 1,463 1,175 1,524 2,004 2,319 2,810 International attendees No data No data 85 84 48 58 Exhibitors 90 80 76 71 82 97 Number of: . 2012 . 2013 . 2014 . 2015 . 2016 . 2017 . Abstracts submitted ~600 520 1,135 1,196 1,539 1,942 Abstracts accepted 561 516 624 991 1,362 1,728 Abstract review panels 14 20 23 28 44 62 Breakout sessions (2 hours) 29 25 28 28 48 65 Breakout sessions (1 hour) 2 Posters presented 374 252 (number capped) 387 733 1,026 1,281 Award nomination packages N/A N/A 29 58 48 49 Young investigator submissions (Presented as 2 breakout sessions) Not a category 131 184 250 305 Paid attendees 1,463 1,175 1,524 2,004 2,319 2,810 International attendees No data No data 85 84 48 58 Exhibitors 90 80 76 71 82 97 Originating as the US Army-sponsored Advanced Technology Applications for Combat Casualty Care meeting in 1993, the name was changed to the MHSRS in 2012, when the Assistant Secretary of Defense for Health Affairs became the sponsor, and the individual Service research meetings were rolled under the MHSRS. Note: Before 2014, award nominations were submitted as an e-mail message to the Planning Committee. Open in new tab DISTINGUISHED SERVICE AWARD This award is designed to recognize individuals who, over the years, have contributed significantly to the success of military health system research. The 2017 awardee was Frank K. Butler, Jr., M.D., CAPT, USN (RET), Chairman, Committee of Tactical Combat Casualty Care, Joint Trauma System, San Antonio, Texas (Fig. 1). FIGURE 1. Open in new tabDownload slide The 2017 Military Health System Research Symposium individual award winners pictured with VADM Bono. (A) Distinguished Service Award winner, Dr. Frank K. Butler. Outstanding Research Accomplishment/Individual award winners: (B) Military/Active Duty: MAJ Stephen Schauer, USA, (C) Civilian/Military: Dr. Michael Morris, (D) Academia-Industry: Dr. Veena Taneja. FIGURE 1. Open in new tabDownload slide The 2017 Military Health System Research Symposium individual award winners pictured with VADM Bono. (A) Distinguished Service Award winner, Dr. Frank K. Butler. Outstanding Research Accomplishment/Individual award winners: (B) Military/Active Duty: MAJ Stephen Schauer, USA, (C) Civilian/Military: Dr. Michael Morris, (D) Academia-Industry: Dr. Veena Taneja. Citation: Dr. Frank Butler’s name is synonymous with prehospital trauma care. He has facilitated, promoted, and applied the results of military health system research for over three decades. Dr. Butler’s 20 years dedication to the Committee on Tactical Combat Casualty Care, and 30 years of first responder expertise, has led to casualty care breakthroughs for military application that have crossed into the civilian trauma care world. Dr. Butler’s contributions to trauma care are immeasurable, and have met with world-wide acceptance and implementation. Submitted by Ms. Cynthia Kurkowski Outstanding Research Accomplishment/Individual This award is designed to recognize outstanding research contributions by an individual research scientist with the focus on significant accomplishment(s) of high impact achieved during the past year (Fig. 1). In the category of Active Duty Military, the 2017 awardee was MAJ Steven Schauer, MC, USA from the U.S. Army Institute of Surgical Research, San Antonio, Texas. Citation: MAJ Steven Schauer is recognized for outstanding research contributions in the category of Military Operational Medicine. Over the past year, nine months of which he was deployed to Iraq in support of Operation Inherent Resolve, MAJ Schauer devised 14 original research projects emphasizing the prehospital management of critical injuries. These include the utilization of tranexamic acid for traumatic hemorrhage, the application of occlusive dressings for open pneumothorax, and the use of analgesic agents for pain control. He also led efforts to analyze previously untouched data from the Joint Trauma System’s Prehospital Trauma Registry, and spearheaded Foreign Internal Defense initiatives to establish and enhance nation medical capabilities, particularly for the treatment of pediatric victims. In addition, he was awarded $3M in funding for research projects germane to Warfighters. In executing this research, MAJ Schauer engaged military and civilian counterparts throughout the spectrum of the prehospital arena to ensure broad, thorough, and relevant investigations. Submitted by: MAJ Jason Naylor, USA In the category of Civilian/Military, the 2017 awardee was Michael J. Morris, M.D., San Antonio Uniformed Services Health Education Consortium, Fort Sam Houston, TX, USA. Citation: Dr. Michael Morris is recognized for outstanding research contributions in the category of Occupational Medicine. Since 2011, Dr. Morris has been the Department of Defense (DoD) lead in investigating the clinical questions surrounding the relationship between airborne hazards encountered during Southwest Asia deployment and the development of respiratory disease. His current study in this area has thus far evaluated over 300 patients with chronic symptoms at two military medical treatment facilities. The data indicate that chronic respiratory symptoms following deployment occur due to interacting factors such as age and tobacco use that primarily manifest as airway hyper-reactivity. This work led to a 2016 publication describing a new syndrome of exercise-associated dynamic airway collapse. Dr. Morris is recognized for his research efforts that have profoundly impacted countless veterans within the DoD and Veterans Administration health systems. Submitted by: LTC Aaron Holley, USA In the category of Academia-Industry, the 2017 awardee was Veena Taneja, PhD, Associate Professor, Department of Immunology, Mayo Clinic, Rochester, Minnesota. Citation: Dr. Veena Taneja is recognized for outstanding research contributions in the category of Precision Medicine. Focusing on the role of the microbiome in inflammatory diseases, Dr. Taneja has demonstrated that the gut microbiota can be used as a biomarker for disease status, and that the microbiome can be utilized for individualized medicine. Using arthritic humanized mice that mimic human arthritis, her laboratory has demonstrated human gut-derived commensals can be used for treating inflammatory arthritis. In 2016, her work was highlighted in two high impact peer-reviewed journals, as well as on the Congressionally Directed Medical Research Programs website. In addition, DoD support led to the filing of a patent with the U.S. Patent Office. OUTSTANDING RESEARCH ACCOMPLISHMENT/TEAM This award is designed to recognize outstanding research contributions by a team of research scientists, with the focus on significant accomplishment(s) of high impact achieved during the past year. The 2017 winners in the academic and military categories are listed below (Fig. 2). Figure 2. Open in new tabDownload slide Open in new tabDownload slide The 2017 Military Health System Research Symposium team award winners pictured with MG Holcomb. (A) Mr. Michael Mulligan and Dr. Erik Edwards (team lead) accepting the Academic-Industry Team award on behalf of the Battelle Memorial Institute team, pictured in (B). (C) Ms. Leila Walker accepting the First Place/Military Team award on behalf of the Operational Physical Assessment team from USARIEM, pictured in (D). (E) Dr. Connie Schmaljohn accepting the Honorable Mention/Military Team award on behalf of the Hantavirus Team from USAMRIID, pictured in (F). (G) Mr. Bruce Robertson accepting the Honorable Mention/Military Team award on behalf of the Multi-Channel Negative Wound Pressure Device Team from the U.S. Air Force Medical Support Agency, Falls Church, VA. Figure 2. Open in new tabDownload slide Open in new tabDownload slide The 2017 Military Health System Research Symposium team award winners pictured with MG Holcomb. (A) Mr. Michael Mulligan and Dr. Erik Edwards (team lead) accepting the Academic-Industry Team award on behalf of the Battelle Memorial Institute team, pictured in (B). (C) Ms. Leila Walker accepting the First Place/Military Team award on behalf of the Operational Physical Assessment team from USARIEM, pictured in (D). (E) Dr. Connie Schmaljohn accepting the Honorable Mention/Military Team award on behalf of the Hantavirus Team from USAMRIID, pictured in (F). (G) Mr. Bruce Robertson accepting the Honorable Mention/Military Team award on behalf of the Multi-Channel Negative Wound Pressure Device Team from the U.S. Air Force Medical Support Agency, Falls Church, VA. In the team category of Academia-Industry and the research category of Combat Casualty Care, the 2017 Academic-Industry team winner was the Acute Care Covering for Severely Injured Limbs Project Team from the Battelle Memorial Institute, Columbus, OH, USA. The team was led by Erik Edwards, PhD. Citation: ln 2016, Battelle’s Acute Care Covering for Severely Injured Limbs team worked with the Office of Naval Research to develop a next generation device to treat severely injured limbs, with the specific focus of maximizing tissue preservation during transport from field to trauma center. The goal was to develop a wrap that would cover and conform to the injured limb while releasing antibiotics into the wound. In 2016, the team focused on how to make oxygen available to the tissue in order to avoid ischemia. The result was an oxygen generating “pump” requiring no power and that provides three liters of oxygen over a 72 hour period. This technology lays the foundation for other active functionalities and key subcomponents of the development effort. The concept has been filed as an invention report and is being prepared for publication. Team Members: Erik Edwards, Richard Wolterman, Kelly Jenkins, David Marshall, Jeff Boyce, Tony Duong, Phil Denen, and Scott Ulrich. Submitted by Mr. Michael Mulligan The 2017 first place award in the Military team category, in the research category of Musculoskeletal Injury, was the Occupational Physical Assessment Team (OPAT) from the U.S. Army Research Institute of Environmental Medicine (USARIEM), Natick, Massachusetts. The team was led by Marilyn Sharp, M.S. Citation: From January to December, 2016, USARIEM’s OPAT Team successfully completed a study involving 1,200 recruits and 27 field studies that resulted in a physical test battery to predict which trainees are best suited for physically demanding combat occupations. The test battery was approved for Army-wide implementation by the Secretary of the Army in December 2016 and, as of 3 January 2017, is being administered to all persons joining the Army. This effort is the culmination of 36 months of coordinated effort between USARIEM, the US Army Public Health Center, and multiple other Army organizations. Prospective data collection will continue over the next 2 years to determine injury rates for each participant, and to examine relationships between injury rates and OPAT results. Team Members: Marilyn Sharp, Stephen Foulis, Jan Redmond, Josue Contreras, Jenna Ensko, Peter Frykman, Gabriele Furbay, Alexis Gonzalez, Katelyn Guerriere, Keith Hauret, Julie Hughes, Philip Karl, Alvin Korus, Stephen Mason, James Persson, Czarina Rodriguez, Glen Rossman, Tanja Roy, Sarah Sauers, Anna Schuh, Laurel Smith, Janet Staab, Jiyo Torres, Leila Walker, and Richard Westrick. Submitted by Dr. Susan Proctor Honorable Mention in the Military team category, in the research category of Infectious Diseases was the Hantavirus team from the U.S. Army Research Institute of Infectious Diseases, Ft Detrick, Maryland. The team was led by Connie Schmaljohn, Ph.D. Citation: This team of Army civilian and military scientists is recognized for the successful development and human clinical testing of a state-of-the art DNA vaccine to prevent hemorrhagic fever with renal syndrome caused by Hantavirus infection. The team’s integrated approach resulted in novel methods and assays, as well as a clear demonstration that the candidate vaccine is safe and immunogenic. Their pioneering work led to the first potential medical countermeasure for a life threatening infectious disease long associated with military operations. Team Members: Connie Schmaljohn, Jay Hooper, Steven Kwilas, Mathew Josleyn, Catherine Badger, Rhonda DaSilva, and MAJ Kristopher Paolino. Submitted by Dr. Sina Bavari Honorable Mention in the Military team category, in the research category of Advanced Development, was awarded to the Multi-Channel Negative Wound Pressure Device Team from the U.S. Air Force Medical Support Agency, Falls Church, Virginia. The team was led by Mr. Calvin Griner. Citation: In 2016, Food and Dr.ug Administration approval culminated a 7-year developmental effort by the Multi-Channel Negative Pressure Wound Therapy Device team to improve care of wounded service members. This device is capable of treating up to four wounds simultaneously with individual controls, while drastically decreasing the power utilization and the logistical footprint, It was designed specifically to meet requirements of care in the air and forward surgical environments, and will be the only device of its kind on the market. The device will be available as a commercial-off-the-shelf item in August 2017. Team Members: Calvin Griner, Charlie Dean, Daniel Dukruif, James Luckemeyer, Nicholas Voiles, Lt Col Lewis Wilbur; John Plaga, Maj Melissa Buzbee-Stiles, Richard Stefanski, Lt Col Cheryl Hale, Thomas Solomon, Natalie Bryan, Robert Traynor, Bruce Robertson, David Hefner, Timothy Smith, and Richard Koleszar. Submitted by Mr. Calvin Griner Young Investigator Competition This category was designed to highlight and promote the research accomplishments of residents, fellows, and post-docs within 5 years of graduation from a terminal degree, and Service Academy cadets. In 2017, 305 abstracts were submitted to this category. After a two-tier review process, 10 abstracts were selected for oral presentation. The top three oral presentations are listed below (Fig. 3). FIGURE 3. Open in new tabDownload slide The 2017 Military Health System Research Symposium Young Investigator award winners. (A) Pictured with Dr. Rauch is the First Place winner, Ms, Lauren Cornell. (B) Second Place winner, LT Jenny Held, USN. (C) Third Place winner, Ms. Kate Ziegler. FIGURE 3. Open in new tabDownload slide The 2017 Military Health System Research Symposium Young Investigator award winners. (A) Pictured with Dr. Rauch is the First Place winner, Ms, Lauren Cornell. (B) Second Place winner, LT Jenny Held, USN. (C) Third Place winner, Ms. Kate Ziegler. First Place: Lauren Cornell, M.S., U.S. Army Institute of Surgical Research, San Antonio, Texas for her presentation: Utility of Magnetic Nanoparticles for Targeted Endothelial Transplantation in an Ex-vivo Model. Second Place: LT Jenny M. Held, USN, Naval Medical Center Portsmouth, Portsmouth, Virginia for her presentation: Insertional Safety, Device Stability, and Decompression Efficacy of Alternative Decompression Devices for Tension Pneumothorax: Results of Complementary Studies Using Human Cadaver and Yorkshire Swine Models. Third Place: Ms. Kate Ziegler, B.S., Uniformed Services University, Bethesda, Maryland for her presentation: Clearance of Rabies-like Lyssavirus Infection via Antibody Therapy Post-central Nervous System Invasion. 2017 MHSRS POSTER COMPETITION A total of 1,281 posters were presented over two poster sessions. The award winners are listed in Table II and pictured in Figure 4. TABLE II. The 2017 Military Health System Research Symposium Poster Award Winners Award . Title . Authors . Institutional Affiliation . Best in show Service Members & Veterans with Transhumeral Osseointegration: Initial Rehabilitation Experiences from the DoD OI Program at WRNMMC Michelle Nordstrom, OTR/L1,3, Mark Beachler, CP3, Joe Butkus, OTR/L3, Annemarie Orr, OTD, OTR/L3, Brad Hendershot, PhD1-3, Barri Schnall, MPT3, Stanly Breuer, OTR/L3, Paul Pasquina, MD1,3, Benjamin Potter, MD3, Jonathan Forsberg, MD3, Chris Dearth, PhD2,3 1Uniformed Services University of the Health Sciences, Bethesda, MD 2DOD-VA Extremity Trauma and Amputation Center of Excellence, Bethesda, MD 3Walter Reed National Military Medical Center, Bethesda, MD Award . Title . Authors . Institutional Affiliation . Best in show Service Members & Veterans with Transhumeral Osseointegration: Initial Rehabilitation Experiences from the DoD OI Program at WRNMMC Michelle Nordstrom, OTR/L1,3, Mark Beachler, CP3, Joe Butkus, OTR/L3, Annemarie Orr, OTD, OTR/L3, Brad Hendershot, PhD1-3, Barri Schnall, MPT3, Stanly Breuer, OTR/L3, Paul Pasquina, MD1,3, Benjamin Potter, MD3, Jonathan Forsberg, MD3, Chris Dearth, PhD2,3 1Uniformed Services University of the Health Sciences, Bethesda, MD 2DOD-VA Extremity Trauma and Amputation Center of Excellence, Bethesda, MD 3Walter Reed National Military Medical Center, Bethesda, MD Poster Session 1 Award . Title . Authors . Institutional Affiliation . First Place Adaptive Vacuum Suspension for Optimal Residual Limb Health and Prosthetic Function Matthew Wernke, PhD1, Alexander Albury, CPO1, Cameron Rink, PhD2, Christopher L. Dearth, PhD3-5, Chandan K. Sen, PhD1,2, James Colvin, MS2 1Ohio Willow Wood, Mount Sterling, OH 2The Ohio State University, Columbus, OH 3The Uniformed Services University of the Health Sciences, Bethesda, MD 4Walter Reed National Military Medical Center, Bethesda, MD 5DoD-VA Extremity Trauma & Amputation Center of Excellence, Fort Sam Houston, TX Second place Toward the Rational Design of Advanced Broad Host Range Therapeutic Bacteriophage Cocktails Mikeljon Nikolich, Andrey Filippov, Kirill Sergueev, Akhil Reddy, Jenny He, Amanda Roth Walter Reed Army Institute of Research, Silver Spring, MD Third place Fluid Deprivation Exacerbates Renal Dysfunction & Under-Perfusion in a Porcine 40% TBSA Burn Model Belinda I. Gómez, Tony Chao, Joshua S. Little, Matthew K. McIntyre, Michael A. Dubick, David M. Burmeister US Army Institute of Surgical Research, Fort Sam Houston, TX Honorable mention The Effect of Prolonged Activity & Lower Limb Trauma on Variable Terrain Walking Stability Riley C. Sheehan, PhD1, Christopher A. Rabago, PT, PhD1,2, Kelly A. Ohm, MS1, Jason M. Wilken, PT, PhD1,2 1Center for the Intrepid, Brooke Army Medical Center, JBSA Ft. Sam Houston, TX, 2Extremity Trauma & Amputation Center of Excellence, JBSA Ft. Sam Houston, TX Honorable mention Targeted Interventions for Sleep Disorders in Chronic TBI Produce Improved Sleep Status: A TEAM-TBI Study Ryan Soose, Tina Harrison, Kathryn Edelman, Allison Borrasso, Jane Sharpless, Dana Williams, Valerie Reeves, Dan Pultz, Ron Poropatich, Sue Beers, Anthony Kontos, Micky Collins, Walter Schneider, David Okonkwo University of Pittsburgh, Pittsburgh, PA Poster Session 2 Award Title Authors Institutional Affiliation First place Comparison of Direct Site Endovascular Repair Utilizing Expandable PTFE Stent Grafts Vs. Standard Vascular Shunts in a Porcine (Sus Scrofa) Model Anders J. Davidson, MD1,2, Lucas P. Neff, MD1,2, J. Kevin Grayson, DVM, PhD2, Nathan F. Clement, MD2, Erik S. DeSoucy, MD1,2, Meryl A. Simon-Logan, MD1,2 Christopher M. Abbot, MD3, James B. Sampson, MD2, Timothy K. Williams, MD2 1UC Davis Medical Center, Sacramento, CA 2David Grant USAF Medical Center, Travis Air Force Base, CA 3Kaiser Permanente South Sacramento Medical Center, Sacramento, CA Second place Providing Evidence-based Treatments for PTSD & the Risk of Secondary Traumatic Stress: Results from the PTSD Clinicians Exchange Elizabeth A. Penix, BA1, Kristina Clarke-Walper, MPH1, Ashley M. Wilkinson, MPH2, Erica Simon, PhD3,4,5, Samantha Regala, BS3,4,5, Kile Ortigo, PhD3,4, Josef I. Ruzek, PhD3,4, Raymond C. Rosen, PhD2, Joshua Wilk, PhD1 1Walter Reed Army Institute of Research, Silver Spring, MD 2New England Research Institutes, Watertown, MA 3VA Palo Alto Health Care System, Livermore, CA 4National Center for PTSD, Dissemination and Training Division, Menlo Park, CA 5Palo Alto Veterans Institute for Research, Palo Alto, CA Third place Feasibility & Validation of a Reusable Perfused Human Cadaver Model for Trauma, General Surgery, & Vascular Surgery Training Jenny M. Held, MD, Travis Polk, MD Naval Medical Center Portsmouth, Portsmouth, VA Honorable mention Effect of Hypoxia on Porcine & Human Mesenchymal Stem Cells Ben Antebi, PhD1, Kerfoot P. Walker, MS1,3, Arezoo Mohammadipoor, DVM, PhD1,3, Andriy I. Batchinsky, MD1,3, Leopoldo C. Cancio, MD1 1US Army Institute of Surgical Research, San Antonio, TX 2Oak Ridge Institute for Science & Education, Oak Ridge, TN 3The Geneva Foundation, Tacoma, WA Honorable mention Intrathoracic Pressure Regulation for Treatment of Brain Injury: Results from a Limited Clinical Evaluation Victor Convertino, PhD1, Anja Metzger, PhD2, DaiWai Olson, PhD3, Stephen Figueroa, PhD3, Farid Sadaka, PhD4, Katie Krause, PhD4, Robert Neumann, PhD5, Keith Lurie, PhD2 1US Army Institute of Surgical Research, San Antonio, TX 2ZOLL, Roseville, MN 3UT Southwestern, San Antonio, TX 4Mercy, Denver, CO 5UC Denver, Denver, CO Poster Session 1 Award . Title . Authors . Institutional Affiliation . First Place Adaptive Vacuum Suspension for Optimal Residual Limb Health and Prosthetic Function Matthew Wernke, PhD1, Alexander Albury, CPO1, Cameron Rink, PhD2, Christopher L. Dearth, PhD3-5, Chandan K. Sen, PhD1,2, James Colvin, MS2 1Ohio Willow Wood, Mount Sterling, OH 2The Ohio State University, Columbus, OH 3The Uniformed Services University of the Health Sciences, Bethesda, MD 4Walter Reed National Military Medical Center, Bethesda, MD 5DoD-VA Extremity Trauma & Amputation Center of Excellence, Fort Sam Houston, TX Second place Toward the Rational Design of Advanced Broad Host Range Therapeutic Bacteriophage Cocktails Mikeljon Nikolich, Andrey Filippov, Kirill Sergueev, Akhil Reddy, Jenny He, Amanda Roth Walter Reed Army Institute of Research, Silver Spring, MD Third place Fluid Deprivation Exacerbates Renal Dysfunction & Under-Perfusion in a Porcine 40% TBSA Burn Model Belinda I. Gómez, Tony Chao, Joshua S. Little, Matthew K. McIntyre, Michael A. Dubick, David M. Burmeister US Army Institute of Surgical Research, Fort Sam Houston, TX Honorable mention The Effect of Prolonged Activity & Lower Limb Trauma on Variable Terrain Walking Stability Riley C. Sheehan, PhD1, Christopher A. Rabago, PT, PhD1,2, Kelly A. Ohm, MS1, Jason M. Wilken, PT, PhD1,2 1Center for the Intrepid, Brooke Army Medical Center, JBSA Ft. Sam Houston, TX, 2Extremity Trauma & Amputation Center of Excellence, JBSA Ft. Sam Houston, TX Honorable mention Targeted Interventions for Sleep Disorders in Chronic TBI Produce Improved Sleep Status: A TEAM-TBI Study Ryan Soose, Tina Harrison, Kathryn Edelman, Allison Borrasso, Jane Sharpless, Dana Williams, Valerie Reeves, Dan Pultz, Ron Poropatich, Sue Beers, Anthony Kontos, Micky Collins, Walter Schneider, David Okonkwo University of Pittsburgh, Pittsburgh, PA Poster Session 2 Award Title Authors Institutional Affiliation First place Comparison of Direct Site Endovascular Repair Utilizing Expandable PTFE Stent Grafts Vs. Standard Vascular Shunts in a Porcine (Sus Scrofa) Model Anders J. Davidson, MD1,2, Lucas P. Neff, MD1,2, J. Kevin Grayson, DVM, PhD2, Nathan F. Clement, MD2, Erik S. DeSoucy, MD1,2, Meryl A. Simon-Logan, MD1,2 Christopher M. Abbot, MD3, James B. Sampson, MD2, Timothy K. Williams, MD2 1UC Davis Medical Center, Sacramento, CA 2David Grant USAF Medical Center, Travis Air Force Base, CA 3Kaiser Permanente South Sacramento Medical Center, Sacramento, CA Second place Providing Evidence-based Treatments for PTSD & the Risk of Secondary Traumatic Stress: Results from the PTSD Clinicians Exchange Elizabeth A. Penix, BA1, Kristina Clarke-Walper, MPH1, Ashley M. Wilkinson, MPH2, Erica Simon, PhD3,4,5, Samantha Regala, BS3,4,5, Kile Ortigo, PhD3,4, Josef I. Ruzek, PhD3,4, Raymond C. Rosen, PhD2, Joshua Wilk, PhD1 1Walter Reed Army Institute of Research, Silver Spring, MD 2New England Research Institutes, Watertown, MA 3VA Palo Alto Health Care System, Livermore, CA 4National Center for PTSD, Dissemination and Training Division, Menlo Park, CA 5Palo Alto Veterans Institute for Research, Palo Alto, CA Third place Feasibility & Validation of a Reusable Perfused Human Cadaver Model for Trauma, General Surgery, & Vascular Surgery Training Jenny M. Held, MD, Travis Polk, MD Naval Medical Center Portsmouth, Portsmouth, VA Honorable mention Effect of Hypoxia on Porcine & Human Mesenchymal Stem Cells Ben Antebi, PhD1, Kerfoot P. Walker, MS1,3, Arezoo Mohammadipoor, DVM, PhD1,3, Andriy I. Batchinsky, MD1,3, Leopoldo C. Cancio, MD1 1US Army Institute of Surgical Research, San Antonio, TX 2Oak Ridge Institute for Science & Education, Oak Ridge, TN 3The Geneva Foundation, Tacoma, WA Honorable mention Intrathoracic Pressure Regulation for Treatment of Brain Injury: Results from a Limited Clinical Evaluation Victor Convertino, PhD1, Anja Metzger, PhD2, DaiWai Olson, PhD3, Stephen Figueroa, PhD3, Farid Sadaka, PhD4, Katie Krause, PhD4, Robert Neumann, PhD5, Keith Lurie, PhD2 1US Army Institute of Surgical Research, San Antonio, TX 2ZOLL, Roseville, MN 3UT Southwestern, San Antonio, TX 4Mercy, Denver, CO 5UC Denver, Denver, CO Open in new tab TABLE II. The 2017 Military Health System Research Symposium Poster Award Winners Award . Title . Authors . Institutional Affiliation . Best in show Service Members & Veterans with Transhumeral Osseointegration: Initial Rehabilitation Experiences from the DoD OI Program at WRNMMC Michelle Nordstrom, OTR/L1,3, Mark Beachler, CP3, Joe Butkus, OTR/L3, Annemarie Orr, OTD, OTR/L3, Brad Hendershot, PhD1-3, Barri Schnall, MPT3, Stanly Breuer, OTR/L3, Paul Pasquina, MD1,3, Benjamin Potter, MD3, Jonathan Forsberg, MD3, Chris Dearth, PhD2,3 1Uniformed Services University of the Health Sciences, Bethesda, MD 2DOD-VA Extremity Trauma and Amputation Center of Excellence, Bethesda, MD 3Walter Reed National Military Medical Center, Bethesda, MD Award . Title . Authors . Institutional Affiliation . Best in show Service Members & Veterans with Transhumeral Osseointegration: Initial Rehabilitation Experiences from the DoD OI Program at WRNMMC Michelle Nordstrom, OTR/L1,3, Mark Beachler, CP3, Joe Butkus, OTR/L3, Annemarie Orr, OTD, OTR/L3, Brad Hendershot, PhD1-3, Barri Schnall, MPT3, Stanly Breuer, OTR/L3, Paul Pasquina, MD1,3, Benjamin Potter, MD3, Jonathan Forsberg, MD3, Chris Dearth, PhD2,3 1Uniformed Services University of the Health Sciences, Bethesda, MD 2DOD-VA Extremity Trauma and Amputation Center of Excellence, Bethesda, MD 3Walter Reed National Military Medical Center, Bethesda, MD Poster Session 1 Award . Title . Authors . Institutional Affiliation . First Place Adaptive Vacuum Suspension for Optimal Residual Limb Health and Prosthetic Function Matthew Wernke, PhD1, Alexander Albury, CPO1, Cameron Rink, PhD2, Christopher L. Dearth, PhD3-5, Chandan K. Sen, PhD1,2, James Colvin, MS2 1Ohio Willow Wood, Mount Sterling, OH 2The Ohio State University, Columbus, OH 3The Uniformed Services University of the Health Sciences, Bethesda, MD 4Walter Reed National Military Medical Center, Bethesda, MD 5DoD-VA Extremity Trauma & Amputation Center of Excellence, Fort Sam Houston, TX Second place Toward the Rational Design of Advanced Broad Host Range Therapeutic Bacteriophage Cocktails Mikeljon Nikolich, Andrey Filippov, Kirill Sergueev, Akhil Reddy, Jenny He, Amanda Roth Walter Reed Army Institute of Research, Silver Spring, MD Third place Fluid Deprivation Exacerbates Renal Dysfunction & Under-Perfusion in a Porcine 40% TBSA Burn Model Belinda I. Gómez, Tony Chao, Joshua S. Little, Matthew K. McIntyre, Michael A. Dubick, David M. Burmeister US Army Institute of Surgical Research, Fort Sam Houston, TX Honorable mention The Effect of Prolonged Activity & Lower Limb Trauma on Variable Terrain Walking Stability Riley C. Sheehan, PhD1, Christopher A. Rabago, PT, PhD1,2, Kelly A. Ohm, MS1, Jason M. Wilken, PT, PhD1,2 1Center for the Intrepid, Brooke Army Medical Center, JBSA Ft. Sam Houston, TX, 2Extremity Trauma & Amputation Center of Excellence, JBSA Ft. Sam Houston, TX Honorable mention Targeted Interventions for Sleep Disorders in Chronic TBI Produce Improved Sleep Status: A TEAM-TBI Study Ryan Soose, Tina Harrison, Kathryn Edelman, Allison Borrasso, Jane Sharpless, Dana Williams, Valerie Reeves, Dan Pultz, Ron Poropatich, Sue Beers, Anthony Kontos, Micky Collins, Walter Schneider, David Okonkwo University of Pittsburgh, Pittsburgh, PA Poster Session 2 Award Title Authors Institutional Affiliation First place Comparison of Direct Site Endovascular Repair Utilizing Expandable PTFE Stent Grafts Vs. Standard Vascular Shunts in a Porcine (Sus Scrofa) Model Anders J. Davidson, MD1,2, Lucas P. Neff, MD1,2, J. Kevin Grayson, DVM, PhD2, Nathan F. Clement, MD2, Erik S. DeSoucy, MD1,2, Meryl A. Simon-Logan, MD1,2 Christopher M. Abbot, MD3, James B. Sampson, MD2, Timothy K. Williams, MD2 1UC Davis Medical Center, Sacramento, CA 2David Grant USAF Medical Center, Travis Air Force Base, CA 3Kaiser Permanente South Sacramento Medical Center, Sacramento, CA Second place Providing Evidence-based Treatments for PTSD & the Risk of Secondary Traumatic Stress: Results from the PTSD Clinicians Exchange Elizabeth A. Penix, BA1, Kristina Clarke-Walper, MPH1, Ashley M. Wilkinson, MPH2, Erica Simon, PhD3,4,5, Samantha Regala, BS3,4,5, Kile Ortigo, PhD3,4, Josef I. Ruzek, PhD3,4, Raymond C. Rosen, PhD2, Joshua Wilk, PhD1 1Walter Reed Army Institute of Research, Silver Spring, MD 2New England Research Institutes, Watertown, MA 3VA Palo Alto Health Care System, Livermore, CA 4National Center for PTSD, Dissemination and Training Division, Menlo Park, CA 5Palo Alto Veterans Institute for Research, Palo Alto, CA Third place Feasibility & Validation of a Reusable Perfused Human Cadaver Model for Trauma, General Surgery, & Vascular Surgery Training Jenny M. Held, MD, Travis Polk, MD Naval Medical Center Portsmouth, Portsmouth, VA Honorable mention Effect of Hypoxia on Porcine & Human Mesenchymal Stem Cells Ben Antebi, PhD1, Kerfoot P. Walker, MS1,3, Arezoo Mohammadipoor, DVM, PhD1,3, Andriy I. Batchinsky, MD1,3, Leopoldo C. Cancio, MD1 1US Army Institute of Surgical Research, San Antonio, TX 2Oak Ridge Institute for Science & Education, Oak Ridge, TN 3The Geneva Foundation, Tacoma, WA Honorable mention Intrathoracic Pressure Regulation for Treatment of Brain Injury: Results from a Limited Clinical Evaluation Victor Convertino, PhD1, Anja Metzger, PhD2, DaiWai Olson, PhD3, Stephen Figueroa, PhD3, Farid Sadaka, PhD4, Katie Krause, PhD4, Robert Neumann, PhD5, Keith Lurie, PhD2 1US Army Institute of Surgical Research, San Antonio, TX 2ZOLL, Roseville, MN 3UT Southwestern, San Antonio, TX 4Mercy, Denver, CO 5UC Denver, Denver, CO Poster Session 1 Award . Title . Authors . Institutional Affiliation . First Place Adaptive Vacuum Suspension for Optimal Residual Limb Health and Prosthetic Function Matthew Wernke, PhD1, Alexander Albury, CPO1, Cameron Rink, PhD2, Christopher L. Dearth, PhD3-5, Chandan K. Sen, PhD1,2, James Colvin, MS2 1Ohio Willow Wood, Mount Sterling, OH 2The Ohio State University, Columbus, OH 3The Uniformed Services University of the Health Sciences, Bethesda, MD 4Walter Reed National Military Medical Center, Bethesda, MD 5DoD-VA Extremity Trauma & Amputation Center of Excellence, Fort Sam Houston, TX Second place Toward the Rational Design of Advanced Broad Host Range Therapeutic Bacteriophage Cocktails Mikeljon Nikolich, Andrey Filippov, Kirill Sergueev, Akhil Reddy, Jenny He, Amanda Roth Walter Reed Army Institute of Research, Silver Spring, MD Third place Fluid Deprivation Exacerbates Renal Dysfunction & Under-Perfusion in a Porcine 40% TBSA Burn Model Belinda I. Gómez, Tony Chao, Joshua S. Little, Matthew K. McIntyre, Michael A. Dubick, David M. Burmeister US Army Institute of Surgical Research, Fort Sam Houston, TX Honorable mention The Effect of Prolonged Activity & Lower Limb Trauma on Variable Terrain Walking Stability Riley C. Sheehan, PhD1, Christopher A. Rabago, PT, PhD1,2, Kelly A. Ohm, MS1, Jason M. Wilken, PT, PhD1,2 1Center for the Intrepid, Brooke Army Medical Center, JBSA Ft. Sam Houston, TX, 2Extremity Trauma & Amputation Center of Excellence, JBSA Ft. Sam Houston, TX Honorable mention Targeted Interventions for Sleep Disorders in Chronic TBI Produce Improved Sleep Status: A TEAM-TBI Study Ryan Soose, Tina Harrison, Kathryn Edelman, Allison Borrasso, Jane Sharpless, Dana Williams, Valerie Reeves, Dan Pultz, Ron Poropatich, Sue Beers, Anthony Kontos, Micky Collins, Walter Schneider, David Okonkwo University of Pittsburgh, Pittsburgh, PA Poster Session 2 Award Title Authors Institutional Affiliation First place Comparison of Direct Site Endovascular Repair Utilizing Expandable PTFE Stent Grafts Vs. Standard Vascular Shunts in a Porcine (Sus Scrofa) Model Anders J. Davidson, MD1,2, Lucas P. Neff, MD1,2, J. Kevin Grayson, DVM, PhD2, Nathan F. Clement, MD2, Erik S. DeSoucy, MD1,2, Meryl A. Simon-Logan, MD1,2 Christopher M. Abbot, MD3, James B. Sampson, MD2, Timothy K. Williams, MD2 1UC Davis Medical Center, Sacramento, CA 2David Grant USAF Medical Center, Travis Air Force Base, CA 3Kaiser Permanente South Sacramento Medical Center, Sacramento, CA Second place Providing Evidence-based Treatments for PTSD & the Risk of Secondary Traumatic Stress: Results from the PTSD Clinicians Exchange Elizabeth A. Penix, BA1, Kristina Clarke-Walper, MPH1, Ashley M. Wilkinson, MPH2, Erica Simon, PhD3,4,5, Samantha Regala, BS3,4,5, Kile Ortigo, PhD3,4, Josef I. Ruzek, PhD3,4, Raymond C. Rosen, PhD2, Joshua Wilk, PhD1 1Walter Reed Army Institute of Research, Silver Spring, MD 2New England Research Institutes, Watertown, MA 3VA Palo Alto Health Care System, Livermore, CA 4National Center for PTSD, Dissemination and Training Division, Menlo Park, CA 5Palo Alto Veterans Institute for Research, Palo Alto, CA Third place Feasibility & Validation of a Reusable Perfused Human Cadaver Model for Trauma, General Surgery, & Vascular Surgery Training Jenny M. Held, MD, Travis Polk, MD Naval Medical Center Portsmouth, Portsmouth, VA Honorable mention Effect of Hypoxia on Porcine & Human Mesenchymal Stem Cells Ben Antebi, PhD1, Kerfoot P. Walker, MS1,3, Arezoo Mohammadipoor, DVM, PhD1,3, Andriy I. Batchinsky, MD1,3, Leopoldo C. Cancio, MD1 1US Army Institute of Surgical Research, San Antonio, TX 2Oak Ridge Institute for Science & Education, Oak Ridge, TN 3The Geneva Foundation, Tacoma, WA Honorable mention Intrathoracic Pressure Regulation for Treatment of Brain Injury: Results from a Limited Clinical Evaluation Victor Convertino, PhD1, Anja Metzger, PhD2, DaiWai Olson, PhD3, Stephen Figueroa, PhD3, Farid Sadaka, PhD4, Katie Krause, PhD4, Robert Neumann, PhD5, Keith Lurie, PhD2 1US Army Institute of Surgical Research, San Antonio, TX 2ZOLL, Roseville, MN 3UT Southwestern, San Antonio, TX 4Mercy, Denver, CO 5UC Denver, Denver, CO Open in new tab FIGURE 4. Open in new tabDownload slide The 2017 Military Health System Research Symposium poster award winners. Poster Session 1 third place winner Belinda Gomez with Dr. Rauch (A). Poster Session 2 first place winner, Erik S. DeSoucy, MD (B), and Honorable Mention award winner Dr. Victor Convertino with Dr. Rauch (C). FIGURE 4. Open in new tabDownload slide The 2017 Military Health System Research Symposium poster award winners. Poster Session 1 third place winner Belinda Gomez with Dr. Rauch (A). Poster Session 2 first place winner, Erik S. DeSoucy, MD (B), and Honorable Mention award winner Dr. Victor Convertino with Dr. Rauch (C). Author notes The views expressed in this article are those of the authors and do not necessarily represent the official position or policy of the U.S. Government, the Department of Defense, or the U.S. Army. Published by Oxford University Press on behalf of the Association of Military Surgeons of the United States 2019. This work is written by (a) US Government employee(s) and is in the public domain in the US. Published by Oxford University Press on behalf of the Association of Military Surgeons of the United States 2019.

Palmieri, Tina, L;Holmes, James, H;Arnoldo,, Brett;Peck,, Michael;Cochran,, Amalia;King, Booker, T;Dominic,, William;Cartotto,, Robert;Bhavsar,, Dhaval;Tredget,, Edward;Stapelberg,, Francois;Mozingo,, David;Friedman,, Bruce;Sen,, Soman;Taylor, Sandra, L;

Alam,, Khurshid;Jeffery, Steven L, A

doi: 10.1093/milmed/usy280pmid: 30901429

Abstract When treating large burns, autologous skin availability becomes a problem and burn surgeons rely heavily on allogenic and xenogeneic skin for temporary coverage after excision. Application of cadaveric and pig skin grafts carries a risk of auto-immune response and risk of viral and bacterial diseases transmission, and there are many cultural and religious rejections for use of porcine grafts. There has recently become available an alternative resource of xenograft using acellular fish skin (KerecisTM Omega3 Burn). This has been described as providing an effective, safe, efficient skin substitute, free of the risk of transmission of viral disease, and auto-immune reaction risk. Methods Ten patients having split-thickness skin grafting for burn injury were treated with the fish skin xenografts. Results There were no adverse reactions noted on the use of the fish skin grafts. No patient had any reaction to the fish skin and there was a zero incidence of infection. The handling of the fish skin was excellent, a robust and pliable xenograft that was easy to apply. The quality of donor site healing was judged to be good in all cases. Both the analgesic effect noted and the relatively short average times until 100% re-epithelialization are promising. We also illustrate two cases where the dressing was used to treat superficial burns. INTRODUCTION Early excision and application of Split Skin Grafting is the main stay of treatment of deep dermal and full thickness burn injury to avoid common complications like sepsis, multi-organ failure, and acute kidney injury.1 When treating large burns, autologous skin availability becomes a problem and burn surgeons often rely heavily on allogenic and xenogeneic skin for temporary coverage after excision. Human cadaver and pig skin are major sources of this temporary coverage. Application of cadaveric and pig skin grafts carries a risk of auto-immune response and risk of viral and bacterial diseases transmission,2 and there are many cultural and religious rejections for use of porcine grafts in many Muslim countries.3 Cadaveric skin is in limited supply and is understandably very expensive. There has recently become available an alternative resource of xenograft using acellular fish skin (Kerecis Omega3 Burn). This has been described as providing an effective, safe, efficient skin substitute, free of the risk of transmission of viral disease,4 and auto-immune reaction risk.3,5 Furthermore, acellular fish skin has also been used with significant success in the healing process of acute6 and hard to heal wounds like diabetic foot ulcer, and chronic non-healing leg wounds of other varieties.3 Despite being separated by over 350 million years of evolution, fish skin has great similarity to mammalian skin due to its conserved protein structure.7 The skin of cold-sea adapted species like the Atlantic cod is, however, far richer in omega-3 polyunsaturated fatty acids (PUFAs) than warm-sea adapted species. It has a porous microstructure8,9 and has been described as being useful to cover exposed tendon and bone,10,11 initiating granulation of the exposed wound bed to kickstart a stagnated healing process. The minimal processing required in the manufacturing of fish skin maintains its three-dimensional structure, as well as its anti-inflammatory and anti-infective properties. Fish species indeed live in an aquatic environment substantially richer in pathogens compared to the aerial environment of humans.12 Fish skin is rich in Omega3 PUFAs, eicosapentaenoic acid, and docosahexaenoic acid13 which are highly effective as antimicrobial agents and in modulating the inflammatory response of the acute wound healing stage. The fish skin is stored at room temperature, has a shelf life of 3 years and is marketed as an off-the-shelf product.6 Due to these properties, fish skin is an ideal choice for the treatment of combat casualties at Field Hospital level, where cadaver skin or pig skin are not practical to use due to their short shelf life and cold chain issues.4 Due to these properties, we started using the acellular fish skin on our burn casualties at Burn Centre of the Queen Elizabeth Hospital Birmingham, one of the Major Burns Centres in the UK, as a pilot to inform future randomized controlled studies. SPLIT THICKNESS SKIN GRAFT HARVESTING PROCEDURE Ten patients having split-thickness skin grafting for burn injury were treated with the fish skin xenografts. All patients were over 18 years of age. All donor sites were harvested at a depth of 8/1,000th of an inch. After soaking of the fish skin in saline, the fish skin was applied and held in place with a secondary dressing of dry gauze. All skin graft donor sites for each patient were thus treated. The first dressing change to the donor site after surgery was performed at 7 days and then was performed every 3 days thereafter until fully healed. The symptoms and signs of infection were assessed, and pain was assessed using a Verbal rating Score of 0–10 at each dressing change. Days to 90% epithelialization and to 100% epithelialization were recorded, as assessed visually by the senior author. RESULTS Ten patients were included in the donor site study. The average age of the patients was 45 (range 19–80), which included six males and four females. The size of the donor sites ranged from 40 cm2 to 950 cm2. Time to 90% epithelialization was reached with an average of 8.5 days (range 7–13). Time to 100% epithelialization had an average of 11.5 days (range 10–16) (Fig. 1). The patient that had the longest time until 100% re-epithelialization was the patient with the largest surface area of donor site (950 cm2) and had the most severe burn injuries. FIGURE 1. View largeDownload slide Time in days until re-epithelialization of donor site wounds. Gray bars represent 90% and red bars complete re-epithelialization. FIGURE 1. View largeDownload slide Time in days until re-epithelialization of donor site wounds. Gray bars represent 90% and red bars complete re-epithelialization. No patients developed signs or symptoms of infection. Pain scores averaged 2.3 (range 1–4) at day 7. There were no adverse reactions noted on the use of the fish skin grafts. No patient had any reaction to the fish skin and there was a zero incidence of infection of the wounds. The handling of the fish skin was excellent, a robust and pliable xenograft that was easy to apply. The quality of donor site healing was judged to be good in all cases (Fig. 2). FIGURE 2. View largeDownload slide Left: Donor site to front of thigh. Middle: After application of fish skin. Right: Donor site fully re-epithelialized. FIGURE 2. View largeDownload slide Left: Donor site to front of thigh. Middle: After application of fish skin. Right: Donor site fully re-epithelialized. PARTIAL THICKNESS BURNS We have used the fish skin as a treatment for partial thickness burns in selected patients, including a cooking-oil burn to the thigh (Fig. 3) and a flame injury on a hand (Fig. 4). Neither of these cases required skin grafting so were not included in the donor site study. Both of the wounds were completely epithelialized at the 2-week follow-up. Furthermore, the patients found the fish skin to be comfortable and have an immediate analgesic effect. Several patients noticed the “fish smell” of the product, but no-one strongly objected to this. The end results were esthetically pleasing, minimal scarring or color changes (Figs 3 and 4). FIGURE 3. View largeDownload slide Healing sequence of a cooking oil deep partial thickness burn to lower part of anterior thigh and knee. Left: Burn after debridement. Middle left: 1 week after application of fish skin. Middle right: Good progression of healing at 2 weeks. Right: Three months after injury wound is healed with excellent esthetic outcome. FIGURE 3. View largeDownload slide Healing sequence of a cooking oil deep partial thickness burn to lower part of anterior thigh and knee. Left: Burn after debridement. Middle left: 1 week after application of fish skin. Middle right: Good progression of healing at 2 weeks. Right: Three months after injury wound is healed with excellent esthetic outcome. FIGURE 4. View largeDownload slide Healing sequence of a hand burn following flame injury. Left: After burn debridement. Middle left: Application of fish skin. Middle right: Burn wound at 1 week, prior to reapplication of fish skin. Right: Follow-up at 2 weeks with a good healing outcome. FIGURE 4. View largeDownload slide Healing sequence of a hand burn following flame injury. Left: After burn debridement. Middle left: Application of fish skin. Middle right: Burn wound at 1 week, prior to reapplication of fish skin. Right: Follow-up at 2 weeks with a good healing outcome. DISCUSSION As this is a small case series we cannot make claims of effectiveness, which would require a more rigorous clinical trial. When compared to the literature it reflects favorably on the use of the fish skin graft. In the largest, multicenter randomized clinical trial that has been performed on various dressings to treat donor site wounds the median healing time was much higher. For the hydrocolloid dressing, which outperformed the other treatment modalities the average time to heal was 16 days.14 Any product that can shorten the healing times of donor site wounds can be immensely valuable under circumstances of a large surface area burn, necessitating frequent re-harvesting of donor site areas that are very limited in these cases. The fish skin maintains its three-dimensional structure and is highly porous which provide an extracellular matrix composed of glycosaminoglycans, proteoglycans, fibronectin and growth factors15,16 which allows the migration of autologous cells to promote the proliferative and epithelialization phases of the burn healing process.15,17 The graft contracts slightly after salination and insertion in the wound bed, so it is recommended that pre-wetting takes place before the product is applied so that any shrinkage occurs before application to the patient. A small area of overlap should be made, as is normal when applying any dressing, to allow for any slight slippage. CONCLUSIONS This is the first study to show the effectiveness of using fish skin in acute burns. The experience in our center for partial thickness burns is promising. The healing outcomes for the treatment of donor site wounds are also highly encouraging, especially when compared to other RCTs on other products (Fig. 5 and Table I).14,18–22 One of the weaknesses of this study is that this was a pilot case series with a low number of patients. Both the analgesic effect noted and the relatively short average times until 100% re-epithelialization are promising and need to be studied further in a randomized controlled trial comparing the fish skin with current standard of care. FIGURE 5. View largeDownload slide Comparison of results in days until healing when using fish skin on donor site wounds in this case series with published literature. FIGURE 5. View largeDownload slide Comparison of results in days until healing when using fish skin on donor site wounds in this case series with published literature. TABLE I. Literature Review on Various Healing Times of Donor Sites with Different Treatment Modalities Type of Study Case Series RCT RCT RCT RCT RCT RCT RCT RCT RCT RCT RCT RCT Reference Khurshid et al 2018 Markl et al18 Markl et al18 Bailey et al22 and Assadian et al19 Assadian et al19 – USA Solanki et al20 and Brölmann et al14 Kaiser et al21 Solanki et al20 Brölmann et al14 and Markl et al18 Brölmann et al14 Brölmann et al14 Brölmann et al14 Brölmann et al14 Number of patients 10 26 20 27 17 57 15 8 74 47 45 50 49 Type Fish skin graft Foam dressing Dressing Silver dressing Dressing Dressing Gauze Dressing Silicone dressing Dressing Alginate dressing Gauze Semipermeable film Brand name Kerecis Omega3 by Kerecis Biatain lbu by Coloplast Suprathel by Polymedics Aquacel Ag Extra Hydrofiber by ConvaTec Altrazeal by Uluru Duoderm by ConvaTec Bactigras by Smith & Nephew Biobrain by Smith & Nephew Mepitel by Molnlycke Aquacel by ConvaTec Kaltostat by ConvaTec Adaptic by Acelity or Jelonet by Smith & Nephew Tegaderm by 3 M Time to healing (mean number of days) 11.5 12.8 12.9 13.0 14.2 15.2 15.4 17.0 21.0 26.0 27.1 27.9 32.9 Type of Study Case Series RCT RCT RCT RCT RCT RCT RCT RCT RCT RCT RCT RCT Reference Khurshid et al 2018 Markl et al18 Markl et al18 Bailey et al22 and Assadian et al19 Assadian et al19 – USA Solanki et al20 and Brölmann et al14 Kaiser et al21 Solanki et al20 Brölmann et al14 and Markl et al18 Brölmann et al14 Brölmann et al14 Brölmann et al14 Brölmann et al14 Number of patients 10 26 20 27 17 57 15 8 74 47 45 50 49 Type Fish skin graft Foam dressing Dressing Silver dressing Dressing Dressing Gauze Dressing Silicone dressing Dressing Alginate dressing Gauze Semipermeable film Brand name Kerecis Omega3 by Kerecis Biatain lbu by Coloplast Suprathel by Polymedics Aquacel Ag Extra Hydrofiber by ConvaTec Altrazeal by Uluru Duoderm by ConvaTec Bactigras by Smith & Nephew Biobrain by Smith & Nephew Mepitel by Molnlycke Aquacel by ConvaTec Kaltostat by ConvaTec Adaptic by Acelity or Jelonet by Smith & Nephew Tegaderm by 3 M Time to healing (mean number of days) 11.5 12.8 12.9 13.0 14.2 15.2 15.4 17.0 21.0 26.0 27.1 27.9 32.9 TABLE I. Literature Review on Various Healing Times of Donor Sites with Different Treatment Modalities Type of Study Case Series RCT RCT RCT RCT RCT RCT RCT RCT RCT RCT RCT RCT Reference Khurshid et al 2018 Markl et al18 Markl et al18 Bailey et al22 and Assadian et al19 Assadian et al19 – USA Solanki et al20 and Brölmann et al14 Kaiser et al21 Solanki et al20 Brölmann et al14 and Markl et al18 Brölmann et al14 Brölmann et al14 Brölmann et al14 Brölmann et al14 Number of patients 10 26 20 27 17 57 15 8 74 47 45 50 49 Type Fish skin graft Foam dressing Dressing Silver dressing Dressing Dressing Gauze Dressing Silicone dressing Dressing Alginate dressing Gauze Semipermeable film Brand name Kerecis Omega3 by Kerecis Biatain lbu by Coloplast Suprathel by Polymedics Aquacel Ag Extra Hydrofiber by ConvaTec Altrazeal by Uluru Duoderm by ConvaTec Bactigras by Smith & Nephew Biobrain by Smith & Nephew Mepitel by Molnlycke Aquacel by ConvaTec Kaltostat by ConvaTec Adaptic by Acelity or Jelonet by Smith & Nephew Tegaderm by 3 M Time to healing (mean number of days) 11.5 12.8 12.9 13.0 14.2 15.2 15.4 17.0 21.0 26.0 27.1 27.9 32.9 Type of Study Case Series RCT RCT RCT RCT RCT RCT RCT RCT RCT RCT RCT RCT Reference Khurshid et al 2018 Markl et al18 Markl et al18 Bailey et al22 and Assadian et al19 Assadian et al19 – USA Solanki et al20 and Brölmann et al14 Kaiser et al21 Solanki et al20 Brölmann et al14 and Markl et al18 Brölmann et al14 Brölmann et al14 Brölmann et al14 Brölmann et al14 Number of patients 10 26 20 27 17 57 15 8 74 47 45 50 49 Type Fish skin graft Foam dressing Dressing Silver dressing Dressing Dressing Gauze Dressing Silicone dressing Dressing Alginate dressing Gauze Semipermeable film Brand name Kerecis Omega3 by Kerecis Biatain lbu by Coloplast Suprathel by Polymedics Aquacel Ag Extra Hydrofiber by ConvaTec Altrazeal by Uluru Duoderm by ConvaTec Bactigras by Smith & Nephew Biobrain by Smith & Nephew Mepitel by Molnlycke Aquacel by ConvaTec Kaltostat by ConvaTec Adaptic by Acelity or Jelonet by Smith & Nephew Tegaderm by 3 M Time to healing (mean number of days) 11.5 12.8 12.9 13.0 14.2 15.2 15.4 17.0 21.0 26.0 27.1 27.9 32.9 Presentations Presented as an oral presentation at the 2017 Military Health System Research Symposium. 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Rossi, Kristen, R;Nowak,, Gosia

doi: 10.1093/milmed/usy366pmid: 30901398

Abstract Sexually transmitted infections (STIs) have posed a threat to military service members throughout history, but limited evidence describes current sexually transmitted infection burden for personnel in-theater and stationed abroad. This study assessed chlamydia and gonorrhea rates by unit of country assignment and evaluated the demographic profile of affected personnel during deployment. Chlamydia and gonorrhea cases among active duty personnel were identified from laboratory results and ambulatory encounter records in the Military Health System from fiscal years October 2006 through September 2015; these were linked to personnel and deployment records to ascertain demographic characteristics, unit of country assignment, and if the case was captured during a period of deployment. Case rates were higher for chlamydia (1,321.7 per 100,000) than gonorrhea (222.7 per 100,000). Approximately 2% of both chlamydia and gonorrhea cases were identified during deployment, with significant differences by service, sex, and age. Elevated rates were identified in several countries of unit assignment outside the USA, warranting further assessment to better understand implications of screening programs or increased morbidity. Pertinent limitations for this study potentially underestimate STI cases during deployment, due to incomplete capture of records from shipboard and in-theater facilities. BACKGROUND Historical literature well documents the threat of sexually transmitted infections (STIs) to maintaining military troop readiness, particularly during wartime operations.1 Today, Chlamydia trachomatis (CT) and Neisseria gonorrhoeae (GC) remain the most frequently reported diseases in the Department of Defense.2 U.S. military personnel represent a highly mobile population, operating in fluctuating environments including shipboard communities, large fixed military installations, and war zones around the world. From the scope of public health surveillance, the mobility and range of environmental factors for deployed and active duty personnel assigned outside the USA poses challenges for routine assessments of disease risk, including STIs. Today, the risk for STIs with troop mobility and deployments remains relevant for several factors, including the overall impact of increasing STI rates in young adults, the changing sex ratios of deployed personnel, and the potential for assignment to areas with antimicrobial-resistant GC.3–5 In recent years, a significant enhancement of STI surveillance and research has taken place in the U.S. military through the establishment of collaborative networks crossing domestic-international boundaries.5 Despite this, analyses describing STI rates with respect to unit of country assignment among active duty personnel have yet to be described worldwide. Furthermore, literature highlights the complexities to assess true morbidity among deployed personnel with respect to timing of acquisition and screening practices.6,7 One study demonstrates higher CT rates in pre-deployment phases as opposed to deployment and post-deployment, which may be attributed to enhanced pre-deployment screening procedures, such as HIV testing and pre-deployment health assessments.7 Behavioral risk assessments also suggest that most STI transmission within the shipboard community may occur in local versus foreign ports, as a cohort of personnel in the pre-deployment phase who self-reported a STI in the past 12 months indicated nearly all infections were acquired in the USA.8 Traditional surveillance efforts using medical event reports for CT likely underestimate the burden of disease because most infections are asymptomatic, thus many go undiagnosed, unreported, and untreated. Furthermore, surveillance efforts based on medical event reports may not be reliable indicators to estimate population incidence or prevalence of CT and GC, as they are strongly dependent on screening practices.9 One report documents prevalence estimates from a universal screening initiative to address the large number of clinically symptomatic CT infections among U.S. military personnel assigned to Korea, finding 5.1% of those ages 20–24 years tested positive at in-processing, higher than reported in US population of the same age (2.9%).9,10 While both Army and Navy medicine guidelines instruct annual CT screening for sexually active women ages 25 years and younger, as well as for older women at risk, service-specific differences for screening during training and recruitment phases may contribute to surveillance bias.11–14 For deployed personnel, surveillance efforts are also met with challenges around data capture, as in-theater settings may have limited STI screening and incomplete documentation of medical records. Given these limitations and literature gaps discussed above, this study aims to assess two simple and distinctly separate measures with respect to troop mobility for active duty personnel across all services from fiscal years (FY) 1 October 2006 through 30 September 2015: (1) a proportion of CT and GC cases during deployment to US Central Command (CENTCOM) and (2) CT and GC rates by the unit of country assignment. To better define limitations related to data source capture for deployed personnel, our methods employ a dual-source surveillance approach combining laboratory results with ambulatory encounters. For comparability to other literature, the demographic profile of GC and CT cases identified during CENTCOM deployment are defined, whereas the overall rates per unit of country of assignment are presented as a preliminary assessment to inform future surveillance studies. METHODS The CT and GC cases among active duty Army, Air Force, Marine Corps, and Navy personnel were captured from positive laboratory results and ambulatory encounter records in the Military Health System (MHS). Records were queried from October 1, 2006 through September 30, 2015 by laboratory specimen collection date or ambulatory encounter date, hereafter referred to as clinical event date. Laboratory results were identified with algorithms that capture positive chlamydia and gonorrhea specimens collected from genitourinary, pharyngeal, and rectal sites. These algorithms were previously developed by the Navy and Marine Corps Public Health Center, which routinely utilizes Health Level 7 formatted laboratory results for public health surveillance applications, such as case-finding processes.15,16 Ambulatory encounters were identified with select International Classification of Diseases, 9th Revision (ICD-9) diagnostic codes in the primary or secondary position, guided by case definitions published by the Armed Forces Health Surveillance Branch (AFHSB) (AFHSC, 2012). Defining ICD-9-CM diagnoses for chlamydia included nongonococcal urethritis specific to Chlamydia trachomatis (099.41) and all extensions under code grouping for other venereal diseases due to Chlamydia trachomatis (099.5*). For gonorrhea, defining ICD-9-CM diagnoses included all code groupings for acute and chronic gonococcal infection for the lower and upper genitourinary tract, gonococcal infection of the pharynx, gonococcal infection of the anus and rectum, and gonococcal infection of other specified sites (098.0*, 098.1*, 098.2*, 098.3*, 098.6*, 098.7*, 098.8*). The CT and GC cases were linked by unique identifier to personnel records from the Defense Manpower Data Center (DMDC) to identify demographic characteristics, such as sex, age, and country of unit assignment. If no overlapping demographic record was obtained relative to the clinical event date, a second match was employed to identify a demographic record within 30 days of the clinical event date; if no resulting demographic record was still obtained, the demographic characteristics were coded to unknown. CT and GC cases were also linked by unique identifier to the DMDC Contingency Tracking System (CTS) to determine if the case occurred during a deployment to areas of operation within CENTCOM; these records contain both boots-on-the-ground and shipboard deployments entering areas of CENTCOM operation. To define a case as one occurring during deployment, this assessment specified that the clinical event date fall within a deployment start and end date per DMDC CTS records and made no specifications for a minimum or maximum number of days in-theater. Unduplicated case lists for CT and GC were compiled using a 30-day gap-in-care rule; any record within 30 days of another record for the same person was considered part of the same case. To review the data source of case capture, we classified each case as identified (1) exclusively from laboratory results, (2) exclusively from ambulatory encounters, or (3) from both data sources. Annual case rates were calculated using denominator population estimates from DMDC as of October 1 for each fiscal year, expressed per 100,000 person-years (p-yrs). Chi-square and logistic regression analyses were used to describe the relationship between CENTCOM deployment with source of data capture and demographics. All analyses were completed using Statistical Analysis Software (SAS) Version 9.4 (SAS Institute, Cary, NC, USA). RESULTS A total of 164,138 CT cases and 27,658 GC cases were identified among active duty personnel during FY 2007 to 2015. Approximately 2% of both CT (1.7%; n = 2,800) and GC (1.8%; n = 490) cases occurred during deployment. Chi-square statistic results provide evidence of an association between data source capture and deployment (p < 0.01). The proportion of cases captured exclusively from laboratory results was higher for deployed personnel with CT and GC (80.5 % and 58.0%) in comparison to those identified outside of a deployment period (62.8% and 41.2%, respectively) (Table I). TABLE I. Proportion of Chlamydia and Gonorrhea Cases Captured During vs. Outside Period of CENTCOM Deployment, by Data Source, FY 2007–2015 Ambulatory (Exclusively) Laboratory (Exclusively) Ambulatory and Laboratory Total N % N % N % N p-Value Chlamydia All cases 18,047 11.0 103,504 63.1 42,587 25.9 164,138 <0.01 During deployment 214 7.6 2,255 80.5 331 11.8 2,800 Outside deployment 17,833 11.1 101,249 62.8 42,256 26.2 161,338 Gonorrhea All cases 6,158 22.3 11,480 41.5 10,020 36.2 27,658 <0.01 During deployment 112 22.9 284 58.0 94 19.2 490 Outside deployment 6,046 22.3 11,196 41.2 9,926 36.5 27,168 Ambulatory (Exclusively) Laboratory (Exclusively) Ambulatory and Laboratory Total N % N % N % N p-Value Chlamydia All cases 18,047 11.0 103,504 63.1 42,587 25.9 164,138 <0.01 During deployment 214 7.6 2,255 80.5 331 11.8 2,800 Outside deployment 17,833 11.1 101,249 62.8 42,256 26.2 161,338 Gonorrhea All cases 6,158 22.3 11,480 41.5 10,020 36.2 27,658 <0.01 During deployment 112 22.9 284 58.0 94 19.2 490 Outside deployment 6,046 22.3 11,196 41.2 9,926 36.5 27,168 TABLE I. Proportion of Chlamydia and Gonorrhea Cases Captured During vs. Outside Period of CENTCOM Deployment, by Data Source, FY 2007–2015 Ambulatory (Exclusively) Laboratory (Exclusively) Ambulatory and Laboratory Total N % N % N % N p-Value Chlamydia All cases 18,047 11.0 103,504 63.1 42,587 25.9 164,138 <0.01 During deployment 214 7.6 2,255 80.5 331 11.8 2,800 Outside deployment 17,833 11.1 101,249 62.8 42,256 26.2 161,338 Gonorrhea All cases 6,158 22.3 11,480 41.5 10,020 36.2 27,658 <0.01 During deployment 112 22.9 284 58.0 94 19.2 490 Outside deployment 6,046 22.3 11,196 41.2 9,926 36.5 27,168 Ambulatory (Exclusively) Laboratory (Exclusively) Ambulatory and Laboratory Total N % N % N % N p-Value Chlamydia All cases 18,047 11.0 103,504 63.1 42,587 25.9 164,138 <0.01 During deployment 214 7.6 2,255 80.5 331 11.8 2,800 Outside deployment 17,833 11.1 101,249 62.8 42,256 26.2 161,338 Gonorrhea All cases 6,158 22.3 11,480 41.5 10,020 36.2 27,658 <0.01 During deployment 112 22.9 284 58.0 94 19.2 490 Outside deployment 6,046 22.3 11,196 41.2 9,926 36.5 27,168 Significant associations were detected for deployment and service, where Army and Navy personnel demonstrated the largest odds of CT of GC case capture during CENTCOM deployment in comparison to Air Force personnel (p < 0.01). A significant association with deployment and sex was detected for GC cases but not CT cases. Two percent of male GC cases were captured during deployment, compared to 1.3% of female GC cases (p < 0.01). For chlamydia cases, significant associations were detected for deployment by age (p < 0.01), where the odds of infection during deployment increased with age category, with the exception for those 40–44 years. For gonorrhea cases, personnel ages 17–19 years demonstrated decreased odds of infection during deployment compared to those 20–24 years (OR = 0.39 95% CI 0.25–0.62) (Table II). TABLE II. Demographics for Chlamydia and Gonorrhea Cases With Odds of Identification During CENTCOM Deployment, FY 2007–2015 During Deployment Outside Deployment All Cases OR Estimate (95% CI) N % N % N Chlamydia Total 2,800 1.7 161,338 98.3 164,138 … Service*  Air Force 336 1.0 32,270 99.0 32,606 (ref)  Army 1,467 1.9 76,443 98.1 77,910 1.84 (1.64–2.08)  Marine Corps 195 1.0 18,999 99.0 19,194 0.99 (0.83–1.18)  Navy 801 2.4 32,735 97.6 33,536 2.35 (2.07–2.67) Sex  Female 1,050 1.7 62,316 98.3 63,366 (ref)  Male 1,749 1.8 98,074 98.2 99,823 1.06 (0.98–1.14) Age (years)*  17–19 164 0.9 18,370 99.1 18,534 0.52 (0.44–0.61)  20–24 1,585 1.7 91,797 98.3 93,382 (ref)  25–29 653 1.9 34,018 98.1 34,671 1.11 (1.01–1.22)  30–34 218 2.1 10,413 97.9 10,631 1.21 (1.05–1.40)  35–39 121 2.9 3,981 97.1 4,102 1.76 (1.46–2.12)  40–44 37 2.5 1,449 97.5 1,486 1.48 (1.06–2.06)  45–49 17 5.5 294 94.5 311 3.35 (2.05–5.48) Gonorrhea Total 490 1.8 27,168 98.2 27,658 … Service*  Air Force 45 1.2 3,602 98.8 3,647 (ref)  Army 294 1.9 15,405 98.1 15,699 1.53 (1.11–2.10)  Marine Corps 26 0.9 2,846 99.1 2,872 0.73 (0.45–1.19)  Navy 125 2.4 4,985 97.6 5,110 2.01 (1.42–2.83) Sex*  Female 83 1.3 6,527 98.7 6,610 (ref)  Male 407 2.0 20,246 98.0 20,653 1.58 (1.25–2.01) Age (years)*  17–19 20 0.7 2,723 99.3 2,743 0.39 (0.25–0.62)  20–24 270 1.8 14,379 98.2 14,649 (ref)  25–29 120 1.9 6,082 98.1 6,202 1.05 (0.85–1.31)  30–34 49 2.2 2,140 97.8 2,189 1.22 (0.90–1.66)  35–39 21 2.2 946 97.8 967 1.18 (0.76–1.85)  40–44 7 1.8 393 98.3 400 0.95 (0.45–2.02) During Deployment Outside Deployment All Cases OR Estimate (95% CI) N % N % N Chlamydia Total 2,800 1.7 161,338 98.3 164,138 … Service*  Air Force 336 1.0 32,270 99.0 32,606 (ref)  Army 1,467 1.9 76,443 98.1 77,910 1.84 (1.64–2.08)  Marine Corps 195 1.0 18,999 99.0 19,194 0.99 (0.83–1.18)  Navy 801 2.4 32,735 97.6 33,536 2.35 (2.07–2.67) Sex  Female 1,050 1.7 62,316 98.3 63,366 (ref)  Male 1,749 1.8 98,074 98.2 99,823 1.06 (0.98–1.14) Age (years)*  17–19 164 0.9 18,370 99.1 18,534 0.52 (0.44–0.61)  20–24 1,585 1.7 91,797 98.3 93,382 (ref)  25–29 653 1.9 34,018 98.1 34,671 1.11 (1.01–1.22)  30–34 218 2.1 10,413 97.9 10,631 1.21 (1.05–1.40)  35–39 121 2.9 3,981 97.1 4,102 1.76 (1.46–2.12)  40–44 37 2.5 1,449 97.5 1,486 1.48 (1.06–2.06)  45–49 17 5.5 294 94.5 311 3.35 (2.05–5.48) Gonorrhea Total 490 1.8 27,168 98.2 27,658 … Service*  Air Force 45 1.2 3,602 98.8 3,647 (ref)  Army 294 1.9 15,405 98.1 15,699 1.53 (1.11–2.10)  Marine Corps 26 0.9 2,846 99.1 2,872 0.73 (0.45–1.19)  Navy 125 2.4 4,985 97.6 5,110 2.01 (1.42–2.83) Sex*  Female 83 1.3 6,527 98.7 6,610 (ref)  Male 407 2.0 20,246 98.0 20,653 1.58 (1.25–2.01) Age (years)*  17–19 20 0.7 2,723 99.3 2,743 0.39 (0.25–0.62)  20–24 270 1.8 14,379 98.2 14,649 (ref)  25–29 120 1.9 6,082 98.1 6,202 1.05 (0.85–1.31)  30–34 49 2.2 2,140 97.8 2,189 1.22 (0.90–1.66)  35–39 21 2.2 946 97.8 967 1.18 (0.76–1.85)  40–44 7 1.8 393 98.3 400 0.95 (0.45–2.02) *Significant Chi-square test statistic p-value. Personnel with unknown service, sex, and age are included in the total frequency but not quantified for the bivariate analysis. Age categories for Chlamydia (50+ years) and Gonorrhea (45–59 years, 50+ years) are also included in the total frequency but not quantified in the bivariate analysis, as the cell values for those identified during deployment were less than five. TABLE II. Demographics for Chlamydia and Gonorrhea Cases With Odds of Identification During CENTCOM Deployment, FY 2007–2015 During Deployment Outside Deployment All Cases OR Estimate (95% CI) N % N % N Chlamydia Total 2,800 1.7 161,338 98.3 164,138 … Service*  Air Force 336 1.0 32,270 99.0 32,606 (ref)  Army 1,467 1.9 76,443 98.1 77,910 1.84 (1.64–2.08)  Marine Corps 195 1.0 18,999 99.0 19,194 0.99 (0.83–1.18)  Navy 801 2.4 32,735 97.6 33,536 2.35 (2.07–2.67) Sex  Female 1,050 1.7 62,316 98.3 63,366 (ref)  Male 1,749 1.8 98,074 98.2 99,823 1.06 (0.98–1.14) Age (years)*  17–19 164 0.9 18,370 99.1 18,534 0.52 (0.44–0.61)  20–24 1,585 1.7 91,797 98.3 93,382 (ref)  25–29 653 1.9 34,018 98.1 34,671 1.11 (1.01–1.22)  30–34 218 2.1 10,413 97.9 10,631 1.21 (1.05–1.40)  35–39 121 2.9 3,981 97.1 4,102 1.76 (1.46–2.12)  40–44 37 2.5 1,449 97.5 1,486 1.48 (1.06–2.06)  45–49 17 5.5 294 94.5 311 3.35 (2.05–5.48) Gonorrhea Total 490 1.8 27,168 98.2 27,658 … Service*  Air Force 45 1.2 3,602 98.8 3,647 (ref)  Army 294 1.9 15,405 98.1 15,699 1.53 (1.11–2.10)  Marine Corps 26 0.9 2,846 99.1 2,872 0.73 (0.45–1.19)  Navy 125 2.4 4,985 97.6 5,110 2.01 (1.42–2.83) Sex*  Female 83 1.3 6,527 98.7 6,610 (ref)  Male 407 2.0 20,246 98.0 20,653 1.58 (1.25–2.01) Age (years)*  17–19 20 0.7 2,723 99.3 2,743 0.39 (0.25–0.62)  20–24 270 1.8 14,379 98.2 14,649 (ref)  25–29 120 1.9 6,082 98.1 6,202 1.05 (0.85–1.31)  30–34 49 2.2 2,140 97.8 2,189 1.22 (0.90–1.66)  35–39 21 2.2 946 97.8 967 1.18 (0.76–1.85)  40–44 7 1.8 393 98.3 400 0.95 (0.45–2.02) During Deployment Outside Deployment All Cases OR Estimate (95% CI) N % N % N Chlamydia Total 2,800 1.7 161,338 98.3 164,138 … Service*  Air Force 336 1.0 32,270 99.0 32,606 (ref)  Army 1,467 1.9 76,443 98.1 77,910 1.84 (1.64–2.08)  Marine Corps 195 1.0 18,999 99.0 19,194 0.99 (0.83–1.18)  Navy 801 2.4 32,735 97.6 33,536 2.35 (2.07–2.67) Sex  Female 1,050 1.7 62,316 98.3 63,366 (ref)  Male 1,749 1.8 98,074 98.2 99,823 1.06 (0.98–1.14) Age (years)*  17–19 164 0.9 18,370 99.1 18,534 0.52 (0.44–0.61)  20–24 1,585 1.7 91,797 98.3 93,382 (ref)  25–29 653 1.9 34,018 98.1 34,671 1.11 (1.01–1.22)  30–34 218 2.1 10,413 97.9 10,631 1.21 (1.05–1.40)  35–39 121 2.9 3,981 97.1 4,102 1.76 (1.46–2.12)  40–44 37 2.5 1,449 97.5 1,486 1.48 (1.06–2.06)  45–49 17 5.5 294 94.5 311 3.35 (2.05–5.48) Gonorrhea Total 490 1.8 27,168 98.2 27,658 … Service*  Air Force 45 1.2 3,602 98.8 3,647 (ref)  Army 294 1.9 15,405 98.1 15,699 1.53 (1.11–2.10)  Marine Corps 26 0.9 2,846 99.1 2,872 0.73 (0.45–1.19)  Navy 125 2.4 4,985 97.6 5,110 2.01 (1.42–2.83) Sex*  Female 83 1.3 6,527 98.7 6,610 (ref)  Male 407 2.0 20,246 98.0 20,653 1.58 (1.25–2.01) Age (years)*  17–19 20 0.7 2,723 99.3 2,743 0.39 (0.25–0.62)  20–24 270 1.8 14,379 98.2 14,649 (ref)  25–29 120 1.9 6,082 98.1 6,202 1.05 (0.85–1.31)  30–34 49 2.2 2,140 97.8 2,189 1.22 (0.90–1.66)  35–39 21 2.2 946 97.8 967 1.18 (0.76–1.85)  40–44 7 1.8 393 98.3 400 0.95 (0.45–2.02) *Significant Chi-square test statistic p-value. Personnel with unknown service, sex, and age are included in the total frequency but not quantified for the bivariate analysis. Age categories for Chlamydia (50+ years) and Gonorrhea (45–59 years, 50+ years) are also included in the total frequency but not quantified in the bivariate analysis, as the cell values for those identified during deployment were less than five. During the cumulative study period from FY 2007 to 2015, five countries of unit assignment outside the USA demonstrated the largest frequency of CT and GC cases, including South Korea, Germany, Japan, Italy, and Guam. A total of 8,334 CT cases were identified among personnel with a country assignment in South Korea, corresponding to a rate almost three times the USA (3,307.9 vs. 1,241.2 per 100,000 p-yrs, respectively). A substantial number of CT cases among personnel assigned to Germany (n = 7,545) and Japan (n = 7,066) were also identified during the study period, both demonstrating rates higher than the USA (1,624.0 and 1,555.7 per 100,000 p-yrs, respectively). Notably, a smaller number of cases were identified among personnel assigned to Guam (n = 958) but corresponded to the second highest CT rate (1,911.1 per 100,000 p-yrs) (Table III). Annual CT rates among personnel assigned to South Korea remained above all other countries throughout the study period, reaching a maximum point of almost 5,000 per 100,000 p-years in 2009, subsequently declining until 2013 (Fig. 1). TABLE III. Chlamydia and Gonorrhea Rates by Unit of Country Assignment, FY 2007–2015 Chlamydia Gonorrhea Unit Country Assignment Cases (N) Rate (per 100,000) Cases (N) Rate (per 100,000) South Korea 8,334 3,307.9 970 385.0 Guam 958 1,911.1 169 337.1 Germany 7,545 1,624.0 1,821 392.0 Bahrain 403 1,559.6 65 251.5 Japan 7,066 1,555.7 934 205.6 Turkey 190 1,326.5 * * Cuba 145 1,263.0 * * USA 132,400 1,241.2 22,362 209.6 Italy 1,231 1,185.8 117 112.7 Portugal 82 1,178.8 * * United Kingdom 953 1,101.7 64 74.0 Spain 163 1,057.2 23 149.2 Greece 36 1,001.1 * * British Indian Ocean Territory 35 917.9 * * Belgium 79 696.1 * * Netherlands 21 495.8 * * Kuwait 30 147.2 * * Iraq 77 92.3 * * Afghanistan 44 68.3 * * Unknown 4,240 * 1,038 * Total 164,138 1,321.7 27,658 222.7 Chlamydia Gonorrhea Unit Country Assignment Cases (N) Rate (per 100,000) Cases (N) Rate (per 100,000) South Korea 8,334 3,307.9 970 385.0 Guam 958 1,911.1 169 337.1 Germany 7,545 1,624.0 1,821 392.0 Bahrain 403 1,559.6 65 251.5 Japan 7,066 1,555.7 934 205.6 Turkey 190 1,326.5 * * Cuba 145 1,263.0 * * USA 132,400 1,241.2 22,362 209.6 Italy 1,231 1,185.8 117 112.7 Portugal 82 1,178.8 * * United Kingdom 953 1,101.7 64 74.0 Spain 163 1,057.2 23 149.2 Greece 36 1,001.1 * * British Indian Ocean Territory 35 917.9 * * Belgium 79 696.1 * * Netherlands 21 495.8 * * Kuwait 30 147.2 * * Iraq 77 92.3 * * Afghanistan 44 68.3 * * Unknown 4,240 * 1,038 * Total 164,138 1,321.7 27,658 222.7 *Table only presents countries with cumulative frequencies greater than or equal to 20. Table is sorted in descending order by the chlamydia case rate. Personnel with an unknown unit country include those with “ZZZ” and “U” in the DMDC record. TABLE III. Chlamydia and Gonorrhea Rates by Unit of Country Assignment, FY 2007–2015 Chlamydia Gonorrhea Unit Country Assignment Cases (N) Rate (per 100,000) Cases (N) Rate (per 100,000) South Korea 8,334 3,307.9 970 385.0 Guam 958 1,911.1 169 337.1 Germany 7,545 1,624.0 1,821 392.0 Bahrain 403 1,559.6 65 251.5 Japan 7,066 1,555.7 934 205.6 Turkey 190 1,326.5 * * Cuba 145 1,263.0 * * USA 132,400 1,241.2 22,362 209.6 Italy 1,231 1,185.8 117 112.7 Portugal 82 1,178.8 * * United Kingdom 953 1,101.7 64 74.0 Spain 163 1,057.2 23 149.2 Greece 36 1,001.1 * * British Indian Ocean Territory 35 917.9 * * Belgium 79 696.1 * * Netherlands 21 495.8 * * Kuwait 30 147.2 * * Iraq 77 92.3 * * Afghanistan 44 68.3 * * Unknown 4,240 * 1,038 * Total 164,138 1,321.7 27,658 222.7 Chlamydia Gonorrhea Unit Country Assignment Cases (N) Rate (per 100,000) Cases (N) Rate (per 100,000) South Korea 8,334 3,307.9 970 385.0 Guam 958 1,911.1 169 337.1 Germany 7,545 1,624.0 1,821 392.0 Bahrain 403 1,559.6 65 251.5 Japan 7,066 1,555.7 934 205.6 Turkey 190 1,326.5 * * Cuba 145 1,263.0 * * USA 132,400 1,241.2 22,362 209.6 Italy 1,231 1,185.8 117 112.7 Portugal 82 1,178.8 * * United Kingdom 953 1,101.7 64 74.0 Spain 163 1,057.2 23 149.2 Greece 36 1,001.1 * * British Indian Ocean Territory 35 917.9 * * Belgium 79 696.1 * * Netherlands 21 495.8 * * Kuwait 30 147.2 * * Iraq 77 92.3 * * Afghanistan 44 68.3 * * Unknown 4,240 * 1,038 * Total 164,138 1,321.7 27,658 222.7 *Table only presents countries with cumulative frequencies greater than or equal to 20. Table is sorted in descending order by the chlamydia case rate. Personnel with an unknown unit country include those with “ZZZ” and “U” in the DMDC record. FIGURE 1. View largeDownload slide Annual Chlamydia Rates for the Countries of Unit Assignment with the Highest Cumulative Case Frequencies, FY 2007–2015. FIGURE 1. View largeDownload slide Annual Chlamydia Rates for the Countries of Unit Assignment with the Highest Cumulative Case Frequencies, FY 2007–2015. Personnel assigned to Germany (392.0 per 100,000 p-yrs), South Korea (385.0 per 100,000 p-yrs), and Guam (337.1 per 100,000 p-yrs) had the highest GC rates from FY 2007 to 2015 (Table III). Annual GC rates for personnel assigned to Germany and South Korea remained elevated above the U.S. rate (209.6 per 100,000 p-yrs) throughout the 9-year period (Fig. 2). A substantial number of gonorrhea cases were also identified from personnel assigned to Japan (n = 934), though the cumulative gonorrhea rate in this country (205.6 per 100,000 p-yrs) was below the USA (Table III). FIGURE 2. View largeDownload slide Annual Gonorrhea Rates for the Countries of Unit Assignment with the Highest Cumulative Case Frequencies, FY 2007–2015. FIGURE 2. View largeDownload slide Annual Gonorrhea Rates for the Countries of Unit Assignment with the Highest Cumulative Case Frequencies, FY 2007–2015. DISCUSSION In these analyses, small proportions of CT and GC cases were identified during a period of CENTCOM deployment. Our methods supplemented laboratory results with ambulatory encounters to account for limitations in case capture, particularly for suspect infections not represented in laboratory data sources. Less than 10 percent of CT cases during deployment were captured exclusively from ambulatory results, demonstrating these data supplementation provided minimal case capture beyond laboratory results, or diagnostic coding was not specific to CT infection. Furthermore, ambulatory encounters during deployment may have been captured in a specific in-theater medical system not reflected in this assessment. This finding did not translate for GC cases during deployment, where almost one-quarter were captured exclusively from ambulatory encounters, suggesting a secondary data source outside of laboratory results can provide expanded surveillance for GC. One study assessed potential sources for STI case capture during deployments, yielding notable comparisons. Stahlman et al supplemented laboratory results with reportable medical events and pharmacy prescriptions, also finding laboratory results captured the majority of CT infections for active duty personnel. Inclusion of these additional data sources in the Stahlman et al study did however yield a larger percentage of CT cases during deployment (4.2%) compared to the 1.7% in the current study.7 While the addition of prescription data in the aforementioned study may account for limitations with identifying CT cases treated empirically, medical encounter data have also been implicated as a means to improve incidence estimates for CT and GC.17 AFHSB maintains CT and GC case definitions for the purpose of epidemiologic surveillance, which include ICD-9 and ICD-10 diagnostic codes from ambulatory encounters.18,19 Together, results from the current assessment and Stahlman et al indicate analyses for CT and GC should contain a range of data sources for more complete case capture and comprehensive surveillance. The demographic profile by age and sex for cases identified during deployment are not consistent with overall U.S. burden. While younger age groups consistently represent the highest CT and GC rates in the USA, this analysis identified larger proportions of older personnel with CT and GC during a deployment period. Furthermore, national CT rates for females are twice that of males, and this assessment demonstrated no significant difference by sex for CT cases identified during deployment.3 Though we did not stratify age results by sex, our findings are noteworthy in comparison to the study by Aldous et al, which found females in older age groups demonstrated higher CT and GC rates than younger males and females deployed to Iraq and Afghanistan.6 Increased healthcare utilization associated with pre-deployment screenings may account for these differences, as Department of Defense policy mandates the completion of pre-deployment health assessments in the 60 days prior to deployment, followed by administration of necessary medical countermeasures or protective measures, and update to medical and deployment health records.20 To date, this is the first publication of STI rates to include a comprehensive, worldwide assessment for unit of country assignment among active duty military personnel. Our results indicated elevated CT and GC rates for personnel assigned to several units outside the USA. Annual rates by unit country were pertinent to present, as the substantial increase in CT rates among personnel assigned to South Korea from 2007 through 2009 correlated with a command-driven initiative to address a large number of clinically symptomatic infections. From November 2007 to January 2010, almost 18,000 soldiers were screened for chlamydia infection at in-processing to Korea; universal screening was implemented for all female soldiers, until November 2008, when the program was expanded to include males. Our results demonstrated a sharp decline in chlamydia rates for personnel assigned to South Korea during 2010, the year in which the universal screening initiative was discontinued.10 This coincidental timing indicates that CT case capture, particularly in South Korea, is widely dependent on screening policy. Substantial numbers of CT and GC cases were identified among personnel assigned to countries such as Germany, Japan, Italy, and Guam, of which Germany and Guam demonstrated both CT and GC rates above the USA. Further assessment is warranted to better understand how personnel assigned to these countries either have an increased likelihood for screening or if these findings represent true morbidity. This method of geographic analysis poses substantial limitations, as the country of unit assignment may not represent the country in which personnel were consistently present or directly represent the risk for CT or GC, particularly for those assigned to a ship. Nonetheless, these findings highlight the presence of pre-existing infection or acquisition of new infections for personnel assigned outside the USA, not just for those with a deployment record. The elevated CT and GC rates demonstrated in this analysis for personnel assigned outside the USA may present an opportunity for targeted screening programs during in-processing to overseas installations, such as the successful initiative in South Korea. Several limitations are worth noting. Our methods potentially underestimate STI cases during deployment, due to incomplete data capture of records from shipboard and in-theater facilities. True incidence may also be higher than observed, potentially due to poor documentation of an STI diagnosis in a medical record, symptom-based diagnostic coding, or a lack of screening procedures. Furthermore, our methods only defined a proportion of cases during a period of deployment and made no assessment between deployment phases (ex. pre-deployment or post-deployment), duration of deployment, or timing of diagnosis/acquisition respective to deployment time elapsed or during periods of rest and relaxation leave. Our methods do not quantify the comparative risk for diagnosis during deployment versus diagnosis during assignment OCONUS and instead provide descriptive statistics as separate measures. Additional database and methodologic limitations are worth noting. Medical encounters among military members accessing non-MTFs are not captured. A large number of individuals who are asymptomatic may not seek care, and others are presumed to seek care outside of the military medical system. Additionally, screening practices may vary across services for demographic groups and geographic units. While AFHSB includes diagnostic codes from hospitalizations in CT and GC case definitions, we did not include records from the Standard Inpatient Data Record (SIDR), as we found relatively few inpatient cases over the cumulative study period and chose to exclude them from our analyses. CONCLUSIONS This assessment identified small proportions of CT and GC cases during a period of deployment but characterized elevated rates in several countries OCONUS. Current literature describing STI risk as it pertains to the mobility of military personnel outside the US is limited to cohorts of shipboard personnel and those deployed to areas of operation within CENTCOM. To our knowledge, this is the first publication of STI rates to include a worldwide assessment for unit of country assignment among active duty military personnel. Results from this assessment point to a potential need for evaluations that encompass the impact of assignment abroad, not just for those deployed to shipboard or in-theater settings. This assessment demonstrated an increasing trend in CT rates for personnel assigned to South Korea, which coincide with literature describing a universal screening program for personnel at in-processing to this country. However, even following discontinuation of the screening program, rates in this country continued to exceed all others. Descriptive demographic assessments for STI rates by unit of country assignment may be warranted. Additionally, comprehensive evaluation of screening practices may provide better evidence of increased CT and GC morbidity for personnel assigned to countries outside the USA. Previous Presentations Presented as an oral plenary at the 2017 Military Health System Research Symposium (#MHSRS-17–0109). Funding This material is based upon work supported by the Defense Technical Information Center under contract number FA8075-14-D-0003 and a grant from Department of Defense (DoD) Global Emerging Infections Surveillance (GEIS) and Systems, #20160470173. This supplement was sponsored by the Office of the Secretary of Defense for Health Affairs. Acknowledgments We would like to thank Charley Martin for her expertise in developing dataset parameters and dataset preparation, the EpiData Center IT staff for dataset query, and Armed Forces Health Surveillance Branch for DMDC denominator population estimates. References 1 Rasnake MS , Conger NH , McAllister K , Holmes KK , Tramont EC : History of U.S. military contributions to the study of sexually transmitted diseases . J Mil Med 2005 ; 170 ( 4 Suppl ): 61 – 65 . Google Scholar Crossref Search ADS 2 Armed Forces Health Surveillance Branch . Reportable Events Monthly Report. July 2016 . Available at https://www.health.mil/ReferenceCenter/Reports/2016/07/01/Reportable-Events-Monthly; accessed July 22, 2017. 3 Centers for Disease Control and Prevention : Sexually Transmitted Disease Surveillance 2015 . Atlanta , U.S. Department of Health and Human Services , 2016 . 4 Gaydos JC , McKee KT , Faix DJ : Sexually transmitted infections in the military: new challenges for an old problem . Sex Transm Infect 2015 ; 91 ( 8 ): 536 – 37 . Google Scholar Crossref Search ADS PubMed 5 Sanchez JL , Agan BK , Tsai AY , et al. : Expanded sexually transmitted infection surveillance efforts in the United States Military: a time for action . J Mil Med 2013 ; 178 ( 12 ): 1271 – 80 . Google Scholar Crossref Search ADS 6 Aldous WK , Robertson JL , Robinson BJ , et al. : Rates of Gonorrhea and Chlamydia in U.S. Military personnel deployed to Iraq and Afghanistan (2004–2009) . J Mil Med 2011 ; 176 ( 6 ): 705 . Google Scholar Crossref Search ADS 7 Stahlman S , Garges EC , Ying S , Clark LL : Rates of Chlamydia trachomatis infections across the deployment cycle, active component, U.S. Armed Forces, 2007–2015 . MSMR 2017 ; 24 ( 1 ): 12 – 18 . 8 Harbertson J , Scott PT , Moore J , et al. : Sexually transmitted infections and sexual behavior of deploying shipboard US military personnel: a cross-sectional analysis . Sex Transm Infect 2015 ; 91 : 581 – 88 . Google Scholar Crossref Search ADS PubMed 9 Torrone E , Papp J , Weinstock H : Prevalence of Chlamydia trachomatis genital infection among persons aged 14–39 years – United States, 2007–2012 . MMWR 2014 ; 63 ( 38 ): 834 – 38 . Google Scholar PubMed 10 Jordan NN , Clemmons NS , Gaydos JC , Lee HC , Yi SH , Klein TA : Chlamydia trachomatis screening initiative among U.S. Army soldiers assigned to Korea . MSMR 2013 ; 20 ( 2 ): 15 – 16 . Google Scholar PubMed 11 A Guide to Female Soldier Readiness , USACHPPM Technical Guide 281. June 2010. Available at http://8tharmy.korea.army.mil/site/assets/doc/army-spotlight/fitness-forum/Guide-to-Female-Soldier-Readiness.pdf; accessed January 18, 2018 . 12 BUMED Instruction 6222.10C – Prevention and Management of STDs. February 2009 . Available at http://www.med.navy.mil/directives/ExternalDirectives/6222.10C.pdf; accessed January 18, 2018. 13 Garges E , Holmes K , MacDonald M : Emerging issues in sexually transmitted diseases: focus on the treatment of STDs in Military populations. 2013 . Available at www.cdc.gov/std/treatment/2010/Military-Webinar-slides.pdf; accessed November 13, 2017. 14 Gaydos JC , McKee KT , Gaydos CA : The changing landscape of controlling sexually transmitted infections in the U.S. Military . MSMR 2013 ; 20 ( 2 ): 2 – 3 . Google Scholar PubMed 15 Nowak G : Description of the MHS health level 7 chemistry laboratory for Public Health Surveillance. 2012 . Available at: http://www.dtic.mil/docs/citations/ADA590932; accessed April 6, 2017. 16 Nowak G : Description of the MHS health level 7 microbiology laboratory for Public Health Surveillance. 2012 . Available at http://www.dtic.mil/docs/citations/ADA590818; accessed April 6, 2017. 17 Armed Forces Health Surveillance Center : Predictive value or reportable medical events for Neisseria gonorrhoeae and Chlamydia trachomatis . MSMR 2013 ; 20 ( 2 ): 11 – 14 . 18 Armed Forces Health Surveillance Center . Surveillance Case Definitions - Chlamydia. November 2015 . Available at https://www.health.mil/Military-Health-Topics/Health-Readiness/Armed-Forces-Health-Surveillance-Branch/Epidemiology-and-Analysis/Surveillance-Case-Definitions; accessed 8 December 2017. 19 Armed Forces Health Surveillance Center . Surveillance Case Definitions - Gonorrhea. June 2016 . Available at https://www.health.mil/Military-Health-Topics/Health-Readiness/Armed-Forces-Health-Surveillance-Branch/Epidemiology-and-Analysis/Surveillance-Case-Definitions; accessed December 8, 2017. 20 Department of Defense Instruction 6490.03 . August 2006 . Available at http://www.esd.whs.mil/Portals/54/Documents/DD/issuances/dodi/649003p.pdf; accessed January 18, 2018. Author notes Approved for public release: distribution unlimited. Any opinions, findings and conclusions or recommendations expressed in this material are those of the authors and do not necessarily represent the official position or policy of the U.S. Government, the Department of Defense, or the Department of the Navy. © Association of Military Surgeons of the United States 2018. All rights reserved. For permissions, please e-mail: [email protected].

Lowndes,, Bethany;Law,, Katherine;Abdelrahman,, Amro;Prytz,, Erik;Jonson,, Carl-Oscar;Sztajnkrycer,, Matthew;Hawthorne,, Hunter;Franz,, Walter;Blocker,, Renaldo;Hallbeck, M, Susan

doi: 10.1093/milmed/usy331pmid:

Rolland-Harris,, Elizabeth

doi: 10.1093/milmed/usy353pmid: 30901452

Abstract Suicide prevention and surveillance are of primary concern to the Canadian Armed Forces (CAF) and to the CAF Health Services (CFHS). Suicide surveillance has been conducted on behalf of the CFHS by the Directorate of Force Health Protection for nearly 30 years. Over time, multiple changes have occurred within CAF: changes in its military role (from a primarily peacekeeping role to one also involving active combat), changes in operational tempo, temporal changes in at-risk subpopulations, as well as increased awareness and concern with suicide and suicide prevention. This has resulted in the annual reporting of CAF suicide rates and the evolution of the report’s content to respond to the needs of its end users. More recently, Regular Force Army and Combat Arms males have been identified as being at significantly higher risk of suicide, relative to their counterparts, as well as to the Canadian general population. However, this trend has been fairly stable. To optimize the use of limited epidemiologic resources and to shift the focus from the rates themselves towards a better understanding of what they represent and how they can be modified, the suicide surveillance portfolio is evolving to include complementary data sources and elements. This paper describes the different data sources that constitute the CAF’s enhanced suicide surveillance portfolio, the value-added evidence generated by the use of complementary data collection methods and sources, and how this evidence is used by CAF leadership in their efforts to prevent suicide amongst those who serve. INTRODUCTION Monitoring suicide rates in the Canadian Armed Forces (CAF) has been a part of the Directorate of Force Health Protection’s (D FHP) mandate since the mid-1990s. The cornerstone of this process is a passive surveillance system that collects basic information on suicides involving CAF personnel, both in garrison and on deployment, and both within Canada and abroad. For over two decades, it has captured all CAF suicide deaths and is the main data repository for CAF senior leadership to direct evidence-based suicide prevention policy and clinical action. Canada’s involvement in the Afghanistan mission (2002–2012) corresponds to an increase in both absolute numbers and age-adjusted suicide rates amongst CAF Regular Force males. Although this was not an unexpected effect of active combat in a volatile war zone (and was consistent with the experience reported by Canada’s allies, particularly the USA), the increase concerned CAF senior leadership. Evaluating possible underlying drivers of these rate increases requires expanded epidemiological suicide surveillance data at a level of detail beyond what is reported in historical CAF Surgeon General annual suicide reports. These data gaps include deployment, army-specific service, and, within army-specific service, Combat Arms service on Regular Force male suicide rates. Deployment as a statistically significant risk factor for suicide was never conclusively established.1 We posit that this may be in part due to the small number of events on which analyses were based. We also suspect that the confounding effects of deployment with age and environmental command are more likely culprits for this. However, Army personnel were found to be at significantly higher risk of death by suicide than their non-Army counterparts. This discordance in risk was even more pronounced in those within the Combat Arms (CA) “Purple Trades” versus those in other trades (everyone else, including non-CA Army personnel). While overall Regular Force male CAF suicide rates remain above pre-Afghanistan levels, they appear to be fairly stable, as do the high-risk groups. Consequently, this stasis begs the following questions: What are some of the risk (negative) and protective (positive) factors contributing to this equipoise? How can we respond to this (and other related) questions, given the limited focus and statistical power of our surveillance data? Given the relative stability of the rates, is the current level of surveillance warranted, or should some of the resources historically allocated to traditional surveillance be reinvested/re-allocated to respond to questions (a) and (b)? These questions and, more specifically, their responses evolve organically over time. Through interest and investment into the mental well-being of those who serve, capacity to supplement and enhance the evidence from the surveillance system has gradually expanded. This paper focuses on describing the different data sources and data collection modalities that now contribute to the Canadian Armed Forces’ Health Services (CFHS) Suicide Surveillance Portfolio (SSP). THE SUICIDE SURVEILLANCE PORTFOLIO The Directorate of Force Health Protection’s epidemiological suicide surveillance system is the most established facet of the SSP and, as such, acts as the keystone for the broader portfolio (Fig. 1). FIGURE 1. View largeDownload slide Framework and facets of the CFHS suicide surveillance portfolio. FIGURE 1. View largeDownload slide Framework and facets of the CFHS suicide surveillance portfolio. As the CAF serves the dual role of both employer and health care provider, all CAF member suicides are systematically reported to the Department of National Defence (DND)/CAF. The responsibility to receive suicide notifications and to inform the relevant parties within the organization has changed over time. However, the current process relies upon the Directorate of Casualty Support Management within DND informing the Directorate of Mental Health (DMH) of all deaths. Once these have been confirmed and cross-referenced by DMH with information also captured by DND’s Directorate Special Examinations and Injuries, they are then passed onto D FHP for annual analysis and dissemination. Prior to 2007, annual reporting was on an ad hoc basis; it is now annually (usually in the autumn of the following year). The report content has evolved during this time period but descriptive epidemiological analyses (crude and age-adjusted rates; standardized mortality ratios that compare the observed CAF suicide rate to the Canadian general population) are a consistent part of the report. Because of statistically small numbers, reports describe Regular Force suicides only, but the underlying surveillance system also collects data on females and Reservists. Durkheim, in his 1897 book “Suicide: A Study in Sociology,”2 identified suicide as the result of “complex interrelationships among a multiplicity of characteristics”.3 A surveillance system like the pre-SSP one is inadequate if the purpose is to monitor suicides over time and to understand CAF-specific suicide characteristics and how the military environment interacts/contributes to them. This inadequacy stems from a lack of sufficient data elements but is also impeded by issues of statistical power related to the small number of annual events. Cognizant of the double challenge created by both statistically small numbers and limited data elements, pre-SSP holdings are being supplemented with data from various sources, using different research methods to remedy these liabilities. Broadly, these data enhancements can be classified into five types: (a) Medical Professional Technical Suicide Reviews (MPTSR); (b) survey data; (c) electronic health record (EHR) data; (d) CF Cancer and Mortality Study II (CF CAMS II); and (e) methodological exercises. The aims of this multifaceted data collection approach are three-fold (Fig. 2): To ensure a broad understanding of each and every suicide, including the factors that may put individuals at increased risk. All five SSP data enhancement types contribute to this aim. To improve understanding of these same risk factors in the broader CAF population. Survey, EHR and CF CAMS II data also contribute to this aim. To improve the statistical power of the findings. CF CAMS II is the only data enhancement type that contributes to this aim. Figure 2. View largeDownload slide Overview of aims addressed by the different data holdings within the CFHS suicide surveillance portfolio. Figure 2. View largeDownload slide Overview of aims addressed by the different data holdings within the CFHS suicide surveillance portfolio. The specifics of the data types and how they contribute to the SSP’s aims are described in more detail below. MEDICAL PROFESSIONAL TECHNICAL SUICIDE REVIEWS The MPTSR is an investigation that is conducted following each probable or confirmed suicide reported to CAF. The MPTSR collects information on demographic and risk factors that is used to describe the population captured by the surveillance system. It is based on the US Department of Defense Suicide Event Report (DoDSER),4 and was implemented following a recommendation of the DND/CAF 2009 Expert Panel on Suicide Prevention.5 The data collection and dissemination process is described in more detail elsewhere.1,6 The MPTSR aims to (1) identify whether any military factors may have contributed to the event; (2) ensure that all suicide prevention-related health protection initiatives are evidence-based; and (3) provide more specific details on each documented event, including prior access to health care, risk factors, and event-specific details (e.g., mechanism of injury). Medical Professional Technical Suicide Review data have been collected since 2010 and have been included in the annual suicide report since 2014. Unlike the core suicide surveillance data that are age-standardized and aggregated (e.g., 5-year standardized mortality ratios), the MPTSR section of the annual suicide report presents descriptive data on the frequency of a number of relevant factors related to suicide, including access to care prior to death, as well as some information on possible pre-enrollment risk factors. Although the generalizability and the interpretation of these findings are limited by the lack of contextual information, they nonetheless provide additional data to what is commonly collected as part of the core surveillance system. This is their main contribution to the SSP. They also illustrate the underlying atomistic and ecological fallacies of suicide evidence; namely, that (1) what happens at the individual level does not necessarily represent the suicide experience at the population level (atomistic fallacy) and (2) the aggregate characteristics identified as part of a study may not be contributing factors to the individual act of death by suicide (ecological fallacy). They do serve the purpose of highlighting potential areas of concern, but that must be evaluated against a more comprehensive population-level understanding of these risk factors and their relative importance within a multifactorial suicide risk factor framework. What they do not provide, however, is context on the prevalence of these factors in the broader CAF population, nor do they positively contribute to the issue of statistical power. SURVEY DATA The Suicide Surveillance Portfolio Primarily through D FHP and DMH, CFHS has conducted, and continues to conduct, a number of surveys. These surveys support the SSP by providing prevalence information on mental health conditions as well as possible risk factors associated with military life, general mental health and general well-being. Of the suite of surveys administered by CFHS, the ones most pertinent to the SSP are DMH’s Canadian Forces Mental Health Survey (CFMHS), D FHP’s Health and Lifestyle Information Survey (HLIS) and Recruit Health Questionnaire (RHQ). Their primary value is contextual in nature, providing CAF-wide prevalence data on factors that may put individuals at higher risk of taking their own lives. Unlike the CFMHS and HLIS, the RHQ also contributes individual-level evidence on CAF suicide risk factors. This is described in more detail below. CFMHS The CFMHS was conducted by DMH, in collaboration with Statistics Canada (STC) in 2013, focusing on mental health status and mental health service needs of CAF personnel deployed in support of the mission to Afghanistan.7,8 The CFMHS is a valuable source of evidence on ideation9 and attempt prevalence.10 It also provides insight into some of the CAF-specific underlying risk factors11,12 and, more specifically, the relationship between these risk factors and/or outcomes and mental health care utilization.13,14 The latter is also useful in the allocation of suicide prevention resources. HLIS The HLIS is a cross-sectional population-based survey that is administered every 4–5 years by D FHP to randomly selected members of the CAF. Its focus is broad and includes self-reported information on health and lifestyle factors, including health care utilization and satisfaction. While there is some overlap between the HLIS and the CFMHS, the former’s focus is broader than mental health alone. It includes all active CAF members (not just those who were deployed in support of Canada’s involvement in Afghanistan) and has been conducted a number of times (2000,15,16 2004,17,18 2008/2009,19,20 2013/201421), supporting temporal trend analyses. As with CFMHS, HLIS data are anonymized and therefore cannot be linked to specific individuals, but also provide contextual, population-wide prevalence information on risk factors, mental health dimensions, and health care utilization. Furthermore, the HLIS purposely oversamples underrepresented subsets of the CAF (females, individuals who deployed in the last 12 months, male non-commissioned members [NCM]), acting as a source of valuable descriptive and contextual information on CAF members for whom information is traditionally lacking. In 2018, the HLIS will be replaced by the Canadian Armed Forces Health Survey (CAFHS). Since there is substantial overlap in the content of the two surveys, and the fact that the CAFHS will continue to randomly select and recruit active CAF members as participants, we anticipate the CAFHS will continue to address the data gaps currently mitigated by the HLIS. RECRUITMENT HEALTH QUESTIONNAIRE (RHQ) Since 2003, new recruits at the very early stages of basic military training (before they are substantially exposed to military culture) are administered a questionnaire that documents pre-enrollment information on a number of health status parameters (including self-perceived health, depression, other mental health disorders), psychological disposition (including the “Big Five” personality dimensions), health behaviors (including alcohol use, physical activity, smoking), and social environment parameters (including adverse childhood experiences, exposure to violence, negative life events, and social support).22 These measures are taken from a number of validated tools and scales; more details on the measures themselves and on their provenance are published elsewhere.22,23 The RHQ’s high participation rates;23,24 its focus on the pre-military phase of a CAF member’s life course; and the capture of service number, facilitating the linkage of the RHQ with other data sources, all contribute to the RHQ’s overall value to the SSP. Preliminary analyses of linked RHQ and pre-SSP data have identified some potential risks worthy of further investigation.25 This may also serve as a proof of concept that the SSP may be value-added, compared to keeping these complementary data sources in silos. ELECTRONIC HEALTH RECORD DATA Since 2010, the CAF has an electronic health record (EHR) system (Canadian Forces Health Information System [CFHIS]) that catalogs all medical and physiotherapist visits (with a diagnosis code); laboratory, X-ray and other diagnostic test results (e.g., mammography, colonoscopy); and medical referrals outside of the military medical system. Since 2016, these holdings have been supplemented with Mental Health Notes, used to enhance collaborative mental health care and communication within the CAF health system. The CFHIS also captures all CAF Periodic Health Assessments (frequency: every 5 years for personnel under age 40 and every 2 years for those aged 40 and older). More details on CFHIS and its specific data holdings are provided elsewhere.26 The EHR holdings enhance the SSP by providing population-level contextual information on the health needs and challenges of all military members during their career within the CAF. In this respect, it is broader in scope than the HLIS and CFMHS as it captures the full CAF population (rather than a randomized sample), and is the sole source for mental health diagnoses, access to care and treatment data. These same data holdings also allow researchers to include health care-related considerations in their analytic work to identify and quantify the risk factors for suicide in the CAF population. CF CANCER AND MORTALITY STUDY I/II One of the main limitations of the pre-SSP was that post-CAF release suicide deaths were not captured. This contributed to the erroneous perception that post-release suicides were of lesser importance to the CAF in service suicides. An additional, but unsubstantiated, concern was that, should a substantial number of suicide deaths occur shortly post-release, the pre-SSP rates would be underestimates of the “true” incidence of suicide in the CAF. The inability to remedy the division of suicide data according to military status (active vs. Veteran) at the time of death is related to jurisdictional purview. The CAF is legally permitted to receive mortality information (of all causes of death, not just suicide) pertaining to active members as employer and health care provider. This permission terminates once a member releases from the CAF, therefore nullifying CAF’s legally sanctioned access to that person’s mortality data (or to any other data not explicitly provided by the person in question). The need to investigate suicide incidence and risk factors from a life course perspective is an argument that is easily made. Events, exposures and risk factors related to an individual’s pre-military life course may be relevant in better understanding an adverse health event occurring in the military and post-military life courses. Similarly, outcomes related to the military stage of a military person’s life course may not manifest themselves until the post-military stage of their life course. Until recently, the main obstacle to DND and VAC collaborating this gap has been to find a legal method to access mortality data of both still serving and released personnel and to follow them over time (longitudinally). The solution was the Canadian Forces Cancer and Mortality Study I (CF CAMS I), which was a record linkage study conducted jointly by DND, VAC and STC. The CF CAMS I cohort was built using human resources data on all individuals who had served in the CAF between 1972 and 2006, inclusively. Statistics Canada probabilistically linked this information to the Canadian Vital Statistics Database, allowing DND and VAC to investigate the all-cause and some cause-specific mortality incidence in this 35-year cohort of still serving and released CAF personnel. This research approach successfully removed the artificial information silos between the two departments responsible for the oversight of still-serving and released CAF personnel, and allowed for more in-depth (and more statistically powerful) research into adverse health outcomes (including suicide) relevant across different stages of a person’s military life course.8 In an effort to maximize the quality and completeness of the data used to create the CF CAMS I cohort, CF CAMS II was initiated in 2016, using compensation data as the cohort file backbone.27 The results from this study are only beginning to emerge,28 but planned deliverables include using these data to conduct survival models to identify risk and protective factors associated with suicide both during and post-military release. The very large sample size in the CF CAMS II cohort (>240,000 discrete individuals) contributing a total of nearly 5 million person years of observation support multivariable analyses that can respond to the need for evidence and evidence-based prevention that CAF’s traditional suicide surveillance system simply could not address. The dynamic nature of this longitudinal study (whereby additional years of mortality data are appended to the cohort, as they become available to STC) supports the monitoring of changes in trends over time. METHODOLOGICAL EXERCISES Complete and accurate data collection is one of the basic tenets of a surveillance system’s success. However, generating evidence from surveillance data requires more than just good data collection. For data to be actionable (from a policy and/or a prevention point of view), they need to be distilled by subject matter experts (SME) for decision-makers (this is the basic precept of knowledge translation). To do so, SMEs need to understand what the data suggest and how the numbers themselves behave (particularly true for temporal trends, rather than short-period incidence and/or prevalence). For example, when comparing suicide rates/evidence between countries, the lack of a uniform definition of suicide needs to be accounted for; this is equally the case between militaries.29,30 More specifically, some countries (e.g., the UK) include open verdicts, whereas others (e.g., Canada and the USA) do not. Furthermore, some methods are reported more accurately than others (e.g., firearm deaths).31–33 In situations where different nations with differential ratios of more accurate: less accurate suicide mechanisms are compared, the overall degree of suicide classification accuracy may be different between nations, complicating the interpretation of differences. Other issues include different definitions used at the death certificate level (Is suicide only in the immediate cause of death field, or only the antecedent cause of death field, or in either field?), changes over time in ICD-coding,34,35 and possible changes in intra-jurisdictional suicide ascertainment over time.32 To confidently comment on suicide risk factors and risk groups within the CAF, and to monitor apparent increases of suicide rates within specific subgroups,1 SMEs must have a secure handle on the complexities and peculiarities of the data that they are working with, so that they can successfully disentangle true changes from artefactual ones. This means that methodological exercises that focus on the behavior of the numbers, rather than the numbers themselves, are needed within an enhanced SSP. In accordance with this, the CAF SSP team have been conducting a number of methodological exercises, including: chairing The Technical Cooperation Panel (TTCP) Special Project investigating the suitability of direct standardization of suicide rates to facilitate inter-military rate comparisons, under the auspices of the TTCP HUM Military Medicine subgroup; engaging in a collaborative project with STC to better understand how changes in suicide ascertainment in the civilian sector influence CAF rates over time. We expect that as these methodological projects are completed, they will contribute to an enhanced understanding of CAF suicide epidemiology. We also anticipate further methodological questions over time. To continue generating accurate evidence, it is our duty to allocate time and resources to address them. DISCUSSION Because suicide has such a far-reaching impact as a cause of death, suicide prevention is one of the CAF’s primary areas of concern. Great strides have been made to ensure that CAF prevention and clinical care efforts are responsive to the evolving needs of its population, and that they are evidence-based. A recent stride was the release of the CAF-VAC Joint Suicide Prevention Strategy36 (JSPS), which is the result of a collaborative effort between CAF and VAC, based on recommendations made by an Expert Panel with both national and international representation.37 Quantifying the pre-recommendation burden and measuring the JSPS’ success cannot be achieved without a sound and far-reaching suicide surveillance infrastructure. To highlight the CAF-VAC JSPS’s Line of Effort #7, an integral part of this strategy’s success is dependent on “continuously improv[ing] through research, analysis and incorporation of lessons learned and best practices.”36 The persistence of the SSP is key in supporting the JSPS’s pursuit of success and excellence, particularly given its ability to provide evidence from all three stages of a military person’s life course. As the data landscape evolves within CAF (in particular CFHS), we expect that the makeup of the SSP will also evolve in response. Its organic genesis, and its ability to respond to an evolving landscape, both in terms of the epidemiology of suicide within the CAF, but also in terms of its data holdings, make the SSP simple, flexible, acceptable, representative, and timely. This account is therefore only a snapshot of a living, evolving and adaptable surveillance system. The SSP is an illustration of the effort, dedication, expertise and resources that DND and the CAF invest daily in protecting those who serve, and of the organization’s ability to quickly adapt to an ever-evolving landscape, in the hopes of “reduc[ing] risks, build[ing] resilience in our CAF and Veteran communities, and prevent[ing] suicide among our military members and Veterans.”36 Presentation Rolland-Harris, E. Suicide Surveillance and Epidemiology in the Canadian Armed Forces. Keynote Presentation, 2017 MHSRS, 30 August 2017, Kissimmee, FL (#MHSRS-17–1280). Funding This supplement was sponsored by the Office of the Secretary of Defense for Health Affairs. References 1 Rolland-Harris E : Report on Suicide Mortality in the Canadian Armed Forces (1995 to 2016). Ottawa (Canada): Department of National Defence; 2017 . 2 Durkheim E : Suicide: A Study in Sociology . London , Routledge , 1970 . 3 Lazarsfeld PF , Rosenberg M : The Language of Social Research . Glencoe, IL , Free Press , 1955 . 4 Pruitt L , Smolenski DJ , Bush N , et al. : DoDSER Department of Defense suicide event report: calendar year 2015 annual report. Washington, D.C., DoD, 2016 . 5 Zamorski MA : Report of the Canadian Forces Expert Panel on suicide prevention. Ottawa (Canada), Department of National Defence, 2010 . 6 Cyr E , Rolland-Harris E , Purdy J : Findings from the Canadian Armed Forces 2010–2015 Medical Professional Technical Suicide Review reports: examining factors that may have contributed to member suicides. Human Factors and Medicine Panel HFM-275: Military Suicide Prevention, Riga, NATO S&T 2017 . 7 Zamorski M , Bennett R , Boulos D , Garber B , Jetly R , Sareen J. : The 2013 Canadian Forces mental health survey: background and methods . Can J Psychiatry 2016 ; 61 ( 1 Suppl ): 10S – 25S . Google Scholar Crossref Search ADS PubMed 8 Pearson C , Zamorski M , Janz T : Mental Health of the Canadian Armed Forces. Ottawa , Minister of Industry , 2014 . 9 Richardson J , Thompson A , King L , et al. : Insomnia, psychiatric disorders and suicidal ideation in a Nationally Representative Sample of active Canadian Forces members . BMC Psychiatry 2017 ; 17 ( 1 ): 211 . Google Scholar Crossref Search ADS PubMed 10 Sareen J , Afifi TO , Taillieu T , et al. : Trends in suicidal behaviour and use of mental health services in Canadian military and civilian populations . CMAJ 2016 ; 188 ( 11 ): E261 – 7 . Google Scholar Crossref Search ADS PubMed 11 Sareen J , Afifi TO , Taillieu T , et al. : Deployment-related traumatic events and suicidal behaviours in a Nationally Representative Sample of Canadian Armed Forces personnel . Can J Psychiatry 2017 ; 62 : 795 – 804 . Google Scholar Crossref Search ADS PubMed 12 Taillieu T , Afifi TO , Turner S , et al. : Risk factors, clinical presentations, and functional impairments for generalized anxiety disorder in military personnel and the general population in Canada . Can J Psychiatry 2018 ; 63 : 610 – 9 . Google Scholar Crossref Search ADS PubMed 13 Boulos D , Zamorski M : Contribution of the mission in Afghanistan to the burden of past-year mental disorders in Canadian Armed Forces personnel, 2013 . Can J Psychiatry 2016 ; 61 ( Suppl. 1 ): 64S – 76S . Google Scholar Crossref Search ADS PubMed 14 Fikretoglu D , Liu A , Zamorski M , Jetly R. : Perceived need for and perceived sufficiency of mental health care in the Canadian Armed Forces: Changes in the past decade and comparisons to the general population. Can J Psychiatry 2016 ; 61 ( Suppl. 1 ): 36S – 45S . Google Scholar Crossref Search ADS PubMed 15 Decima Research Inc. : CF Health and Lifestyle Information Survey: Regular Force Report. Montreal: Decima Research Inc., 2002 . 16 Decima Research Inc. : CF Health and Lifestyle Information Survey: Reserve Force Report. Montreal: Decima Research Inc., 2002 . 17 Directorate of Force Health Protection : Canadian Forces Health and Lifestyle Information Survey: Regular Force Report. Ottawa, DND, 2005 . 18 Directorate of Force Health Protection : Canadian Forces Health and Lifestyle Information Survey: Reserve Force Report. Ottawa, DND, 2006 . 19 Directorate of Force Health Protection : Canadian Forces Health and Lifestyle Information Survey 2008/2009: Reserve Force Report. Ottawa, DND, 2015 . 20 Born J , Bogaert L , Payne E , Wiens M : Results from Health and Lifestyle Information Survey of Canadian Forces Personnel 2008/2009: Regular Force Version . Ottawa , DND , 2011 . 21 Theriault F , Gabler K , Naicker K : Health and Lifestyle Information Survey of the Canadian Armed Forces Personnel 2013/2014: Regular Force Report . Ottawa , DND , 2016 . 22 Lee JEC , Hachey KK : Descriptive Analyses of the Recruit Health Questionnaire: 2007–2009 . Ottawa , DRDC , 2011 . 23 Lee JEC : Psychometric Properties of Psychological Scales in the Recruit Health Questionnaire: Internal Consistency of Scales . Ottawa , DRDC , 2008 . 24 Lee JEC , Whitehead J , Dubiniecki C : Descriptive Analyses of the Recruit Health Questionnaire: 2003–2004 . Ottawa , Department of National Defence , 2010 . 25 Gottschall S , Weeks M , Rolland-Harris E : Non-Service-Related Risk Factors for Suicide Among Canadian Armed Forces Members: Results of a Nested Case-Control Study Using Recruit Health Questionnaire Data. Human Factors and Medicine Panel HFM-275: Military Suicide Prevention . Riga , NATO S&T , 2017 . 26 Hawes RA , Whitehead J : Military Health Informatics to Improve Deployed and In-Garrison Health Surveillance: Epidemiologic Evidence from the Canadian Armed Forces Health Information System. Human Factors and Medicine Panel HFM-251: Military Health Surveillance . Paris , NATO S&T , 2015 . 27 Rolland-Harris E , VanTil L , Zamorski MA , et al. : The Canadian Forces cancer and mortality study II: a longitudinal record-linkage study protocol . CMAJ Open . In Press. 28 Rolland-Harris E , Weeks M , Simkus , K , VanTil L . Overall mortality of Canadian Armed Forces personnel enrolled 1976–2012 . Occ Med 2018 ; 68 ( 1 ): 32 – 37 . Google Scholar Crossref Search ADS 29 O’Carroll P , Berman A , Maris R , et al. : Beyond the tower of babel a nomenclature for suicidology . Suicide Life Threat Behav 1996 ; 26 ( 3 ): 237 – 52 . Google Scholar PubMed 30 IOM : Reducing Suicide: A National Imperative . Washington, D.C. , IOM , 2002 . 31 McIntosh J : Quantitative methods in suicide research: issues associated with official statistics . Arch Suicide Res 2002 ; 6 ( 1 ): 41 – 54 . Google Scholar Crossref Search ADS 32 Skinner R , McFaull S , Rhodes AE , et al. : Suicide in Canada: Is poisoning misclassification an issue? Can J Psychiatry 2016 ; 61 ( 7 ): 405 – 12 . Google Scholar Crossref Search ADS 33 Ajdacic-Gross V , Weiss M , Ring M , et al. : Methods of suicide: international suicide patterns derived from the WHO mortality database . Bull WHO 2008 ; 86 ( 9 ): 657 – 736 . 34 Janssen F , Kunst A : ICD coding changes and discontinuities in trends in cause-specific mortality in six European countries, 1950–99 . Bull WHO 2004 ; 82 ( 12 ): 904 – 13 . Google Scholar PubMed 35 Stewart C , Crawford P , Simon G : Changing in coding of suicide attempts or self-harm with transition from ICD-9 to ICD-10 . Psychiatr Serv 2017 ; 68 ( 3 ): 215 . Google Scholar Crossref Search ADS PubMed 36 Canadian Armed Forces, Veterans Affairs Canada : Joint Suicide Prevention Strategy . Ottawa , Government of Canada , 2017 . 37 Sareen J , Holens P , Turner S : Report of the 2016 Mental Health Expert Panel on Suicide Prevention in the Canadian Armed Forces. Ottawa, DND, 2017 . © Her Majesty the Queen in Right of Canada 2019. Reproduced with the permission of the Minister of Department of National Defense. All rights reserved. For permissions, please e-mail: [email protected]. This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model)

Held, Jenny M; McLendon, Robert B; McEvoy, Christian S; Polk, Travis M

doi: 10.1093/milmed/usy383pmid: 30901456

Abstract Objectives Today’s surgical trainees have less exposure to open vascular and trauma procedures. Lightly embalmed cadavers may allow a reusable model that maximizes resources and allows for repeat surgical training over time. Methods This was a three-phased study that was conducted over several months. Segments of soft-embalmed cadaver vessels were harvested and perfused with tap water. To test durability, vessels were clamped, then an incision was made and repaired with 5-0 polypropylene. Tolerance to suturing and clamping was graded. In a second phase, both an arterial-synthetic graft and an arterial-venous anastomosis were performed and tested at 90 mmHg perfusion. In the final phase, lower extremity regional perfusion was performed and vascular control of a simulated injury was achieved. Results Seven arteries and six veins from four cadavers were explanted. All vessels accommodated suture repair over 6 weeks. There was minor leaking at all previous clamp sites. In the anastomotic phase, vessels tolerated grafting, clamping, and perfusion without tearing or leaking. Regional perfusion provided a life-like training scenario. Conclusions Explanted vessels of soft-embalmed cadavers show adequate durability over time with realistic vascular surgery handling characteristics. This shows promise as initial proof of concept for a reusable perfused cadaver model. Further study with serial regional and whole-body perfusion is warranted. soft-embalmed cadaver, perfused cadaver, surgical training model, trauma training INTRODUCTION Medical simulation technology in recent years has had an exponential advancement in quality, realism, and fidelity. In the field of surgery, certain procedures such as minimally invasive techniques lend themselves particularly well to some of this technology. However, high-fidelity surgical simulation, particularly for complex open procedures, remains elusive. New high-fidelity simulators have begun to bridge this gap,1 but still lack the fidelity for advanced skill development and sustainment of the individual surgeon. Studies have shown that cadaver-based training, and dynamic training in particular, are superior to standard simulation training.1,2 Traditionally, animal models have been utilized in this regard, but the use of live tissue training is becoming increasingly difficult to justify.3,4 Additionally, recent studies and surveys of military surgeons have disclosed significant disparities with regards to their comfort level, preparation, experience and skill-sustainment of critical wartime procedures. Major deficits identified include lack of adequate exposure to major cavitary trauma and injuries to the genitourinary tract and vasculature.5 Courses such as the American College of Surgeons Advanced Surgical Skills for the Exposure of Trauma and the Department of Defense’s Emergency War Surgery Course have attempted to mitigate these deficits with focused cadaveric dissection. In recent years, a few centers have begun to utilize perfused fresh cadaver models to simulate live human surgery in the fields of trauma,6 cardiothoracic,7 vascular,8–10 neurosurgery,11 and plastics12–17 since when perfused, fresh cadavers provide tissue handling characteristics that mimic that of live tissue.18 These studies have been mostly isolated to centers with readily available fresh or frozen fresh cadavers; however, the limitations of this technique are that the quality of these fresh cadavers frequently varies and the fresh nature only allows for a single training evolution. Historically, cadavers embalmed using a traditional formaldehyde technique are not ideal for surgical simulation due to changes in appearance, increased tissue rigidity and loss of normal tissue planes. However, longer-lasting (up to 6 weeks) soft-embalmed cadavers that have realistic appearance and tissue handling characteristics are now available due to recent advances in the science of cadaveric preservation.19,20 With the use of less preservation, these Thiel-method soft-embalmed cadavers maintain more life-like tissue handling but do not decay as quickly as completely un-embalmed cadavers; as such, they have led to a dramatic increase in human cadaveric surgical simulation worldwide.20–23 At least one animal and one human study have demonstrated some success with limited procedures and repeat perfusions with fresh or fresh frozen cadavers.9,24 Therefore, a reliable, reusable, and preserved model of cadaver perfusion for surgical simulation is likely now possible with resultant decreased cost, less infectious risk and wider availability compared to existing fresh cadaver perfusion models or animal models. With the end-goal of developing a full-body perfused soft-embalmed cadaver model, we first sought to investigate the durability and tissue handling of explanted vessels over time. We hypothesized that the tissue would only remain durable for a finite number of weeks. These data can then be extrapolated to determine how many regional or full-body perfusions a single soft-embalmed cadaver can withstand. METHODS This research was supported through the Department of Navy Bureau of Medicine and Surgery Clinical Investigations Program. Grant # NMCP 2015-0032. This three-phased study was conducted over several months. The first phase tested the durability of explanted blood vessels over time. The second phase testing the ability of the explanted vessels to withhold bypass grafting. The last phase utilized lower extremity regional perfusion to achieved vascular control of a simulated injury. Four soft-embalmed “Theil” cadavers were obtained from the state of Virginia anatomical program. The cadavers were stored in a cooler at a temperature of 38 °F. There were three males and one female. The cadavers utilized were of varying post-mortem age, ranging from one to seven months. The average age at death was 64 years (SD 7.7) and BMI was 26 (SD 3.8). In total, 13 vessels were explanted. This included two iliac arteries, two iliac veins, four femoral arteries, four femoral veins, and one brachial artery. Phase 1 – Benchtop Feasibility Study Materials Empty, one-liter normal saline bags were filled with tap water. A pressure cuff was applied to the bag, and the bag of fluid was attached to an elevated IV pole. The bags were spiked such that the distal end of the tubing could be connected to the catheter tubing connected to each vessel (see below). A work surface was then created which utilized a screen to enable fluid to filter without collecting on the table. Initial Vessel Preparation Femoral, iliac, and brachial vessels were explanted from the cadavers. They were maintained oriented in their anatomic position and a catheter tubing was secured to the proximal (for arteries) or distal (for veins) end using a 3-0 silk purse-string suture. A laminated, numeric tag was fixed to the opposite end of the tubing to identify each vessel. A separate key which contained cadaver demographics and vessel identification was kept. A Babcock clamp was used to secure the catheter tubing to the screen work surface in a non-occlusive manner. The intravascular catheter tubing was then connected to the IV tubing and tap water was run through each vessel at a pressure of approximately 90 mmHg for arteries (Fig. 1A) and 15 mmHg for veins. The distal end was clamped with a hemostat and the vessel was inspected for leakage from small side-branches and rents. Side branches were occluded using small and medium clips and rents were repaired using 5-0 polypropylene suture. Each vessel was tested until there were no remaining leaks, at which time the vessel was deemed suitable for experimentation. FIGURE 1. Open in new tabDownload slide Artery pressurized to 90 mmHg with pressure bag/tap water (A) and vessel demonstrating crush injury (B). FIGURE 1. Open in new tabDownload slide Artery pressurized to 90 mmHg with pressure bag/tap water (A) and vessel demonstrating crush injury (B). Vessel Durability Testing The vessels were tested weekly for 6 weeks. Each week the vessels were attached to the pressurized tap water bags at the aforementioned settings. The distal end was clamped with a hemostat and the vessel was left pressurized for ten minutes. During this time, the vessel was inspected for prior damage, which was defined as leaking of water from the vessel wall (typically from prior clamp sites). An 11-blade scalpel was used to make a 2 cm incision at the distal end of the vessel. It was then repaired with a running 5-0 polypropylene suture using standard vascular surgical techniques. The ability of the vessel to tolerate clamping, suturing, and knot tying was graded according to the scale in Table I. TABLE I. Grading Criteria for Vessel Tolerance of Suturing Grading Criteria . Suturing tolerance Prior clamp site durability Vessel is not torn Vessel torn by needle Vessel torn by suture No injury present Crush injury noted without leak Crush injury noted, leaks Vessel is severed Clamping tolerance Tying tolerance Vessel is not injured Vessel is injured but remains intact Vessel sustains full-thickness injury Vessel completely severed Vessel is not injured Vessel is injured but remains intact Vessel sustains full-thickness injury Vessel completely severed Grading Criteria . Suturing tolerance Prior clamp site durability Vessel is not torn Vessel torn by needle Vessel torn by suture No injury present Crush injury noted without leak Crush injury noted, leaks Vessel is severed Clamping tolerance Tying tolerance Vessel is not injured Vessel is injured but remains intact Vessel sustains full-thickness injury Vessel completely severed Vessel is not injured Vessel is injured but remains intact Vessel sustains full-thickness injury Vessel completely severed Open in new tab TABLE I. Grading Criteria for Vessel Tolerance of Suturing Grading Criteria . Suturing tolerance Prior clamp site durability Vessel is not torn Vessel torn by needle Vessel torn by suture No injury present Crush injury noted without leak Crush injury noted, leaks Vessel is severed Clamping tolerance Tying tolerance Vessel is not injured Vessel is injured but remains intact Vessel sustains full-thickness injury Vessel completely severed Vessel is not injured Vessel is injured but remains intact Vessel sustains full-thickness injury Vessel completely severed Grading Criteria . Suturing tolerance Prior clamp site durability Vessel is not torn Vessel torn by needle Vessel torn by suture No injury present Crush injury noted without leak Crush injury noted, leaks Vessel is severed Clamping tolerance Tying tolerance Vessel is not injured Vessel is injured but remains intact Vessel sustains full-thickness injury Vessel completely severed Vessel is not injured Vessel is injured but remains intact Vessel sustains full-thickness injury Vessel completely severed Open in new tab Vessel Storage Between evaluations, the cadavers were stored in an industrial freezer in the bioskills lab set to a temperature of 38 °F. The vessels were stored in a subcutaneous flank pocket of the most recently embalmed cadaver. The overlying skin was re-approximated using a running silk suture. Once removed from the pocket for the duration of the weekly experiment, the vessels were placed in a kidney basin that contained a mix of tap water and the preservation fluid that accumulated from the storage cadaver. Phase 2 – Bypass Grafting Feasibility After Phase 1 was complete, three vessels were selected for grafting. Vessel 9 (femoral artery) was chosen for synthetic grafting. A five-centimeter portion of synthetic graft was sutured proximally and distally to a portion of the explanted vessel using 5-0 silk suture. The portion of vessel between the graft was tied off using 3-0 silk. The vessel was then infused with tap water at 90 mmHg and inspected for flow through the graft without leaking at either anastomosis. Next, a vein graft was simulated by suturing vessel 8 (femoral vein) to vessel 5 (iliac artery). Again, the intervening segment of the iliac artery was ligated using silk ties and tap water was infused at 15 mmHg. The graft was inspected for flow without anastomotic leak. Phase 3 – Regional Perfusion Feasibility The final phase utilized in situ vasculature. Vascular cut down was performed over the right-sided femoral vessels. The femoral artery was isolated using vessel loops. An incision was made in the femoral artery. Tubing was inserted and secured using a modified Rumel tourniquet. The opposite end of the tubing was attached to a Harvard pulsatile pump. “Blood” was created by mixing five gallons of tap water, a half cup of red colored tempura paint, and a half cup of table salt. This formula was chosen as the water to paint ratio created a color similar to blood, and the salt was added to increase the osmolarity of the fluid. A distal thigh injury was simulated by making a large incision. The pump was turned on to simulate pulsatile blood flow from the thigh injury. An investigator, playing the role of “trainee” was then tasked with achieving hemorrhage control (first with a hasty tourniquet and then surgically) while another investigator evaluated the feasibility of this training model. RESULTS Phase 1 – Benchtop Feasibility Study During the first 2 weeks, all vessels handled the suture and clamping well without any injury. All did sustain minor trauma from clamping (Fig. 1B) but there was no break in the integrity of the vessel wall. At week three, leaking at the prior clamp site from two of the femoral veins was observed; the respective cadavers were 6 and 7 months post-embalmment. At week 4, there was a full-thickness tear in the prior clamp site of femoral artery explanted from a 6-month post-embalmment cadaver. By week 6, there was leaking at the prior clamp site from an iliac vein (1-month post-embalmment). Despite the presence of a leak at the prior clamp site, the vessels were still able to tolerate suturing such that the rent was repaired and the experiment was successfully continued. During the course of this experiment, all vessels accommodated suturing and tying without tearing. There was no noticeable difference in the durability of the vessels over time, nor was there a difference based on the site of vessel or the age of the cadaver. Phase 2 – Bypass Grafting Feasibility A segment of explanted femoral artery from Phase 1 (cadaver was six months post-embalmment) was chosen for synthetic grafting due to the adequate length it provided. A 5 cm piece of Dacron graft was sutured proximally and distally to the vessel and the intervening segment was occluded with silk ties to allow preferential flow through the graft (Fig. 2A). The vessel was perfused with tap water to 90 mmHg and water flowed through the graft and out the proximal end of the artery without leaking at either anastomosis (Fig. 2B). FIGURE 2. Open in new tabDownload slide Regional Perfusion with femoral artery connected to pump (A), simulated injury (B), and proximal (C), and distal (D) vascular control of bleeding. FIGURE 2. Open in new tabDownload slide Regional Perfusion with femoral artery connected to pump (A), simulated injury (B), and proximal (C), and distal (D) vascular control of bleeding. Next, a segment of femoral vein was sutured to explanted iliac artery (from different cadavers, both were 6 months post-embalmment) to simulate a vein graft. Both vessels tolerated the suture well without tearing of the vessel from the needle or suture material. Pressurized flow was achieved without anastomotic leak. Phase 3 – Regional Perfusion Feasibility In the final phase, the femoral artery was successfully cannulated and the lower extremity was perfused using the Harvard pump (Fig. 3A). A large incision was made inferior and medial to the knee, after which profuse, pulsatile flow was observed (Fig. 3B). The investigator was able to achieve initial “hemorrhage control” using a tourniquet. Surgical control of the bleeding was then achieved. Proximal control was much easier (Fig. 3C), as the femoral vessels were already exposed due to cannulation. Distal control of the popliteal artery was also obtained (Fig. 3D). FIGURE 3. Open in new tabDownload slide Synthetic graft placed (A) and perfused without anastomotic leak (B). FIGURE 3. Open in new tabDownload slide Synthetic graft placed (A) and perfused without anastomotic leak (B). DISCUSSION AND CONCLUSIONS The results from this initial feasibility study indicate that explanted vessels of soft-embalmed cadavers provide adequate durability over at least a 6-week time period with realistic vascular surgery handling characteristics. During the 6-week time period of this study, all vessels were able to accommodate suturing and tying without tearing. While some vessels did show damage from prior clamp sites, these injuries were able to be repaired and the integrity of the vessels at that site was maintained thereafter. In addition, we found that regional perfusion of a soft-embalmed cadaver, in this case the lower extremity via the femoral vessels, is obtainable and provides a realistic simulation for vascular injury and control. Based on these findings, our laboratory has elected to continue on with a proof of concept study using systemic whole-body perfusion of soft-embalmed cadavers for vascular and trauma surgery simulation. Such a model will include a single body that is perfused weekly over a period of approximately two months. Compared to the current fresh model, which does not last for such a long time period, this novel model may be longitudinally incorporated into general, trauma, and vascular surgery training program curricula. Overall, this may potentially translate to decreased cost, less risk, and wider availability compared to existing animal and fresh cadaver perfusion models. Previous Presentations This study was presented at the 2017 Military Health System Research Symposium held August 27–30, 2017 in Kissimmee, FL, USA. Funding This research was supported through the Department of Navy Bureau of Medicine and Surgery Clinical Investigations Program. Grant # Naval Medical Center Portsmouth (NMCP) 2015-0032. Acknowledgments The authors would like to thank the staff of the Visual Information Department of Naval Medical Center Portsmouth for the photography. Additionally, we thank the NMCP Healthcare Simulation and Bioskills Training Center for the use of its facilities and the tireless assistance of its technical staff in the performance of this study. References 1 Carden AJ , Salcedo ES, Leshikar DE, Utter GH, Wilson MD, Galante JM: Randomized controlled trial comparing dynamic simulation with static simulation in trauma . J Trauma Acute Care Surg 2016 ; 80 ( 5 ): 748 – 53 . discussion 753-4. Google Scholar Crossref Search ADS PubMed WorldCat 2 Takayesu JK , Peak D, Stearns D: Cadaver-based training is superior to simulation training for cricothyrotomy and tube thoracostomy . Intern Emerg Med 2017 ; 12 ( 1 ): 99 – 102 . Google Scholar Crossref Search ADS PubMed WorldCat 3 Davies J , Khatib M, Bello F: Open surgical simulation – a review . J Surg Educ 2013 ; 70 ( 5 ): 618 – 27 . Google Scholar Crossref Search ADS PubMed WorldCat 4 Conyac TM : Do simulator training and duty hour restrictions lead to safer surgery? Bull Am Coll Surg 2011 ; 96 ( 8 ): 40 – 1 . Google Scholar PubMed OpenURL Placeholder Text WorldCat 5 Schwab CW. Further messages about combat surgeons. AAST grand rounds-28 Jan 2015. Available at http://www.aast.org; accessed April 23, 2018 . 6 Aboud ET , Krisht AF, O’Keeffe T, et al. : Novel simulation for training trauma surgeons . J Trauma 2011 ; 71 ( 6 ): 1484 – 90 . Google Scholar PubMed OpenURL Placeholder Text WorldCat 7 Bouma W , Kuijpers M, Bijleveld A, et al. : A new beating-heart off-pump coronary artery bypass grafting training model . Interact Cardiovasc Thorac Surg 2015 ; 20 ( 1 ): 7 – 9 . Google Scholar Crossref Search ADS PubMed WorldCat 8 Palter VN , Grantcharov TP: Development and validation of a comprehensive curriculum to teach an advanced minimally invasive procedure: a randomized controlled trial . Ann Surg 2012 ; 256 ( 1 ): 25 – 32 . Google Scholar Crossref Search ADS PubMed WorldCat 9 Garrett HE Jr: A human cadaveric circulation model . J Vasc Surg 2001 ; 33 ( 5 ): 1128 – 30 . Google Scholar Crossref Search ADS PubMed WorldCat 10 Chevallier C , Willaert W, Kawa E, et al. : Postmortem circulation: a new model for testing endovascular devices and training clinicians in their use . Clin Anat 2014 ; 27 ( 4 ): 556 – 62 . Google Scholar Crossref Search ADS PubMed WorldCat 11 Aboud E , Al-Mefty O, Yasargil MG: New laboratory model for neurosurgical training that simulates live surgery . J Neurosurg 2002 ; 97 ( 6 ): 1367 – 72 . Google Scholar Crossref Search ADS PubMed WorldCat 12 Brosious JP , Tsuda ST, Menezes JM, et al. : Objective evaluation of skill acquisition in novice microsurgeons . J Reconstr Microsurg 2012 ; 28 ( 8 ): 539 – 42 . Google Scholar Crossref Search ADS PubMed WorldCat 13 Douglas HE , Mackay IR: Microvascular surgical training models . J Plast Reconstr Aesthet Surg 2011 ; 64 ( 8 ): e210 – 2 . Google Scholar Crossref Search ADS PubMed WorldCat 14 Rosen JM , Long SA, McGrath DM, Greer SE: Simulation in plastic surgery training and education: the path forward . Plast Reconstr Surg 2009 ; 123 ( 2 ): 729 – 38 . discussion 739-40. Google Scholar Crossref Search ADS PubMed WorldCat 15 Satterwhite T , Son J, Carey J, et al. : Microsurgery education in residency training: validating an online curriculum . Ann Plast Surg 2012 ; 68 ( 4 ): 410 – 4 . Google Scholar Crossref Search ADS PubMed WorldCat 16 Selber JC , Chang EI, Liu J, et al. : Tracking the learning curve in microsurgical skill acquisition . Plast Reconstr Surg 2012 ; 130 ( 4 ): 550e – 7e . Google Scholar Crossref Search ADS PubMed WorldCat 17 Sheckter CC , Kane JT, Minneti M, et al. : Incorporation of fresh tissue surgical simulation into plastic surgery education: maximizing extraclinical surgical experience . J Surg Educ 2013 ; 70 ( 4 ): 466 – 74 . Google Scholar Crossref Search ADS PubMed WorldCat 18 Carey JN , Minneti M, Leland HA, Demetriades D, Talving P: Perfused fresh cadavers: method for application to surgical simulation . Am J Surg 2015 ; 210 ( 1 ): 179 – 87 . Google Scholar Crossref Search ADS PubMed WorldCat 19 Jaung R , Cook P, Blyth P: A comparison of embalming fluids for use in surgical workshops . Clin Anat 2011 ; 24 ( 2 ): 155 – 61 . Google Scholar Crossref Search ADS PubMed WorldCat 20 Anderson SD : Practical light embalming technique for use in the surgical fresh tissue dissection laboratory . Clin Anat 2006 ; 19 ( 1 ): 8 – 11 . Google Scholar Crossref Search ADS PubMed WorldCat 21 Eisma R , Wilkinson T: From “silent teachers” to models . PLoS Biol 2014 ; 12 ( 10 ): e1001971 . Google Scholar Crossref Search ADS PubMed WorldCat 22 Hayashi S , Homma H, Naito M, et al. : Saturated salt solution method: a useful cadaver embalming for surgical skills training . Medicine (Baltimore) 2014 ; 93 ( 27 ): e196 . Google Scholar Crossref Search ADS PubMed WorldCat 23 Thiel W : [An arterial substance for subsequent injection during the preservation of the whole corpse] . Ann Anat 1992 ; 174 ( 3 ): 197 – 200 . Google Scholar Crossref Search ADS PubMed WorldCat 24 Inglez de Souza MC , Matera JM: Bleeding simulation in embalmed cadavers: bridging the gap between simulation and live surgery . ALTEX 2015 ; 32 ( 1 ): 59 – 63 . Google Scholar Crossref Search ADS PubMed WorldCat Author notes The views expressed are those of the authors and do not necessarily reflect the official policy of the Department of the Navy, Department of Defense, or the U.S. Government. Published by Oxford University Press on behalf of the Association of Military Surgeons of the United States 2019. This work is written by (a) US Government employee(s) and is in the public domain in the US. Published by Oxford University Press on behalf of the Association of Military Surgeons of the United States 2019.

Waibel, Kirk H; Cain, Steven M; Huml-VanZile, Michelle; Kreciewski, Nicolette; Hall, Todd E; Nelson, Keely; Everitt-Johnson, Lauren; Black, Irma; Keen, Ronald S

doi: 10.1093/milmed/usy349pmid: 30901439

Abstract Background Section 718 of the Fiscal Year 2017 (FY17) National Defense Authorization Act (NDAA) outlines many reportable telemedicine outcomes. While the Military Health System Data Repository (MDR) and the Management and Reporting Tool M2 provide some telemedicine analyses, there are many outcomes that neither the MDR nor M2 provide. Understanding patient and provider attitudes towards telehealth and specialty-specific usage may assist initial or ongoing telehealth lines of effort within Defense Health Agency Medical Treatment Facilities (DHA MTFs). Methods A retrospective descriptive analysis of synchronous virtual health (VH) encounters and results from three internally developed telehealth surveys for calendar year (CY) 2016 was conducted. Results Three thousand seven hundred and seventy-eight synchronous VH visits for 2,962 unique patients were completed by 142 providers located within 27 distinct specialty clinics. 89.8% of patients were adults and 75.9% were Active Duty. Skill type I and II medical providers conducted 1,827 new consultations, 1,187 follow-up visits, and 371 readiness exams. Overall, specialty-specific VH use ranged from less than 1% to 39.9%. Patient satisfaction was 98% while provider satisfaction ranged from 91% to 93%. Additionally, significant intangible savings were recognized. Conclusion Regional medical centers conducting synchronous VH will require both internal and external data sources to report Section 718 outcomes required by Congress. As the anticipated demand for direct provider-to-patient telehealth increases, understanding these outcomes may aid initial and ongoing efforts in other military treatment facilities conducting synchronous VH. telehealth, synchronous, specialty, military, virtual health BACKGROUND Virtual health (VH) has been identified as a healthcare priority for the Military Health System (MHS) within the Army Campaign 2020 and the military’s selection of Brooke Army Medical Center (BAMC) as the Army’s first virtual medical center with dedicated Program Objective Memorandum (POM) funding.1 However, BAMC and other VH hubs will be required to report congressionally mandated, telehealth-specific outcomes outlined in Section 718 (Telemedicine) of the Fiscal Year 2017 (FY17) National Defense Authorization Act (NDAA).2 Recently, a Government Accountability Office report highlighted some telemedicine outcomes obtained from the MHS Data Repository (MDR) and the Management and Reporting Tool M2, but many outcomes, which can only be performed by detailed internal analyses and surveys, are still needed.3 Within Regional Health Command Europe (RHCE), Landstuhl Regional Medical Center (LRMC) is the only Role 4 United States military treatment facility (MTF). LRMC supports approximately 200,000 beneficiaries within United States European Command (USEUCOM), United States Central Command (USCENTCOM), and United States Africa Command (USAFRICOM) (Fig. 1). The majority of these beneficiaries are enrolled in Army, Air Force, and Navy health clinics located in Germany, Italy, and Belgium. FIGURE 1. Open in new tabDownload slide RHCE Commander’s Area of Responsibility Combatant commands covered by Landstuhl Regional Medical Center (dashed line). FIGURE 1. Open in new tabDownload slide RHCE Commander’s Area of Responsibility Combatant commands covered by Landstuhl Regional Medical Center (dashed line). Prior to 2014, telehealth efforts in RHCE focused on behavioral health and a few surgical subspecialties; however, in late 2014 the European Advancement for Regional Telehealth (EARTH) project was launched hiring specialty-trained telehealth presenters who directly supported multispecialty synchronous telehealth expansion.4 However, we are aware of only one publication reporting multispecialty synchronous telehealth outcomes from a role 4 or 5 MTF.5 Despite this information, many aspects of multispecialty synchronous VH remain unknown. Recognizing Section 718 requirements and the future expansion of synchronous VH, the LRMC VH team continued its analysis of synchronous VH in calendar year 2016 (CY16) and also developed two internal surveys to address other reportable aspects of Section 718. Herein, we report the outcomes required by the FY17 NDAA for LRMC based on CY16 synchronous VH encounters. In addition, understanding tangible and intangible outcomes from both originating and distant site locations will not only meet congressional requirements but will enhance planned synchronous telehealth implementation across the MHS. METHODS The primary objective of this 1-year retrospective review was to determine the number, type, and complexity of synchronous VH encounters conducted per specialty. Secondary objectives included reporting elements required by the FY17NDAA Section 718 and assessing tangible and intangible telehealth revenue and savings, respectively. Patient satisfaction was measured using an anonymous patient satisfaction survey which patients complete immediately following their VH visit (Appendix 1). A second fillable pdf survey was developed by the LRMC telehealth staff to understand healthcare provider’s opinions and attitudes regarding synchronous VH. The survey was refined through three cognitive interview sessions with 6–8 providers who conducted synchronous VH visits at LRMC (Appendix 2). Once finalized, the survey was emailed through the hospital’s enterprise email system to all LRMC providers who had conducted at least one synchronous VH visit in the past three years. The survey was resent once a week for 2 additional weeks to garner additional responses from initial non-responders. The LRMC VH team also developed a survey for medical assistants (MAs) who were responsible for booking all synchronous telehealth appointments within their respective clinics. These written surveys were dropped off at each clinic who had MAs who booked synchronous VH visits. A secure, HIPAA-compliant telehealth appointment booking tool which was developed by LRMC Clinical Operations staff allowed MAs to simultaneously view both the originating site telehealth cart availability and the provider’s clinic schedule when booking a patient VH appointment. Once the appointment was booked, the RHCE Telehealth support team generated an email to both the patient’s preferred email address and the specialty provider’s enterprise email with an appointment reminder. Recognizing this unique scheduling platform (i.e., patients did not call the usual central appointment booking cell), the regional telehealth team’s service coordinators developed a 9-question MA-specific survey. Data regarding total VH and in-person outpatient encounters for each specialty were provided by the LRMC telehealth hub team and the LRMC Clinical Operations Division, respectively. Descriptive statistics were used for patient demographics, specialty details, and intangible outcomes. Descriptive statistics, factor analysis, multivariate analysis of variance, and one-way analysis of variance were performed on patient and provider satisfaction results using SPSS statistical software (IBM, Armonk, NY, USA). A paired t-test using free web-based statistical software (www.socscistatistics.com) was utilized to compare in-person versus telehealth outcomes for scheduling requirements. An α < 0.05 was considered statistically significant. Study approval was obtained by the LRMC Human Research Protection Program and all patients provided written consent to conduct a telehealth appointment. RESULTS From January to December 2016, a total of 3,778 synchronous VH visits were completed for 2,962 unique patients. The majority of patients were adults (89.8%), Active Duty (75.9%), and only participated in one synchronous VH visit (58.7%). Median (range) visits for patients were 1(1–9) while median (range) number of encounters per location was 27.5 (1–734). Synchronous VH visits were conducted by 142 distinct healthcare providers located within 27 distinct specialty clinics who connected to 22 unique originating patient locations. The Virtual Integrated Patient Readiness and Remote (VIPRR) care clinic, staffed by one MA and one 0.8 FTE physician assistant, performed readiness exams to individual Soldiers located in one of 16 remote locations within USEUCOM, USCENTCOM, and USAFRICOM (Table I). TABLE I. Originating Site Telehealth Usage and Estimated Intangible Savings Originating Site . Number of encounters . % Usage by Local Pop. . Miles (roundtrip)a . Days (roundtrip)b . Time Savings (days) . Travel Savings (miles) . Per Diem Savingsc . Correctional Facility, Sembach, Germany 9 NP 0 0 0 0 0.0 Baumholder AHC 7 0.2 55.8 0.5 3.5 390.6 210.9 Brussels AHC 29 3.7 421.2 2 58 12,214.8 6,596.0 Eskan Village, Saudi Arabia 15 NP 6,100.8 7 105 91,512 49,416.5 Grafenwoehr AHC 325 4.0 537.6 2 650 174,720 94,348.8 Hohenfels AHC 79 3.5 452.4 1 79 35,739.6 19,299.4 In-home 26 NP 210 1 26 5,460 2,948.4 Izmir, Turkey 1 NP 3,192 7 7 3,192 1,723.7 Katterbach AHC 132 3.1 326.4 1 132 43,084.8 23,265.8 Lakenhealth Air Base 1 NP 1,017.6 3 3 1,017.6 549.5 Livorno AHC 1 0.2 1,260 5 5 1,260 680.4 Mihail Kogalniceanu, Romania 5 NP 2,510.4 4 20 12,552 6,778.1 Naples Naval Air Station 1 NP 1,687.2 4 4 1,687.2 911.1 Stavanger, Norway 1 NP 1,806 5 5 1,806 975.2 Shape AHC 470 13.5 452.4 2 940 212,628 114,819.1 Sigonella Naval Air Station 2 NP 2,408 5 10 4,816 2,600.6 Spangdahlem Air Base 94 1.9 200.4 1 94 18,837.6 10,172.3 Stuttgart AHC (2 locations) 539 5.6 232.8 1 539 125,479.2 67,758.8 Vicenza AHC 339 4.0 1,012.8 5 1695 343,339.2 185,403.2 VilseckAHC 734 9.2 463.2 2 1468 339,988.8 183,594.0 Wiesbaden AHC 594 10.1 128.4 1 594 76,269.6 41,185.6 VIPRR Clinic (16 countries) 371 NP Varies 5 1870 NP 1,302,000 Total 3,778 8,307.5 1,505,995 2,115,237.3 Originating Site . Number of encounters . % Usage by Local Pop. . Miles (roundtrip)a . Days (roundtrip)b . Time Savings (days) . Travel Savings (miles) . Per Diem Savingsc . Correctional Facility, Sembach, Germany 9 NP 0 0 0 0 0.0 Baumholder AHC 7 0.2 55.8 0.5 3.5 390.6 210.9 Brussels AHC 29 3.7 421.2 2 58 12,214.8 6,596.0 Eskan Village, Saudi Arabia 15 NP 6,100.8 7 105 91,512 49,416.5 Grafenwoehr AHC 325 4.0 537.6 2 650 174,720 94,348.8 Hohenfels AHC 79 3.5 452.4 1 79 35,739.6 19,299.4 In-home 26 NP 210 1 26 5,460 2,948.4 Izmir, Turkey 1 NP 3,192 7 7 3,192 1,723.7 Katterbach AHC 132 3.1 326.4 1 132 43,084.8 23,265.8 Lakenhealth Air Base 1 NP 1,017.6 3 3 1,017.6 549.5 Livorno AHC 1 0.2 1,260 5 5 1,260 680.4 Mihail Kogalniceanu, Romania 5 NP 2,510.4 4 20 12,552 6,778.1 Naples Naval Air Station 1 NP 1,687.2 4 4 1,687.2 911.1 Stavanger, Norway 1 NP 1,806 5 5 1,806 975.2 Shape AHC 470 13.5 452.4 2 940 212,628 114,819.1 Sigonella Naval Air Station 2 NP 2,408 5 10 4,816 2,600.6 Spangdahlem Air Base 94 1.9 200.4 1 94 18,837.6 10,172.3 Stuttgart AHC (2 locations) 539 5.6 232.8 1 539 125,479.2 67,758.8 Vicenza AHC 339 4.0 1,012.8 5 1695 343,339.2 185,403.2 VilseckAHC 734 9.2 463.2 2 1468 339,988.8 183,594.0 Wiesbaden AHC 594 10.1 128.4 1 594 76,269.6 41,185.6 VIPRR Clinic (16 countries) 371 NP Varies 5 1870 NP 1,302,000 Total 3,778 8,307.5 1,505,995 2,115,237.3 aCalculated using Google Maps (https://maps.google.com). bEstimated based on driving distance and country; c2016 Joint Travel Regulation reimbursement of $0.54 per mile (does not include lodging and M + IE); NP, not performed. Open in new tab TABLE I. Originating Site Telehealth Usage and Estimated Intangible Savings Originating Site . Number of encounters . % Usage by Local Pop. . Miles (roundtrip)a . Days (roundtrip)b . Time Savings (days) . Travel Savings (miles) . Per Diem Savingsc . Correctional Facility, Sembach, Germany 9 NP 0 0 0 0 0.0 Baumholder AHC 7 0.2 55.8 0.5 3.5 390.6 210.9 Brussels AHC 29 3.7 421.2 2 58 12,214.8 6,596.0 Eskan Village, Saudi Arabia 15 NP 6,100.8 7 105 91,512 49,416.5 Grafenwoehr AHC 325 4.0 537.6 2 650 174,720 94,348.8 Hohenfels AHC 79 3.5 452.4 1 79 35,739.6 19,299.4 In-home 26 NP 210 1 26 5,460 2,948.4 Izmir, Turkey 1 NP 3,192 7 7 3,192 1,723.7 Katterbach AHC 132 3.1 326.4 1 132 43,084.8 23,265.8 Lakenhealth Air Base 1 NP 1,017.6 3 3 1,017.6 549.5 Livorno AHC 1 0.2 1,260 5 5 1,260 680.4 Mihail Kogalniceanu, Romania 5 NP 2,510.4 4 20 12,552 6,778.1 Naples Naval Air Station 1 NP 1,687.2 4 4 1,687.2 911.1 Stavanger, Norway 1 NP 1,806 5 5 1,806 975.2 Shape AHC 470 13.5 452.4 2 940 212,628 114,819.1 Sigonella Naval Air Station 2 NP 2,408 5 10 4,816 2,600.6 Spangdahlem Air Base 94 1.9 200.4 1 94 18,837.6 10,172.3 Stuttgart AHC (2 locations) 539 5.6 232.8 1 539 125,479.2 67,758.8 Vicenza AHC 339 4.0 1,012.8 5 1695 343,339.2 185,403.2 VilseckAHC 734 9.2 463.2 2 1468 339,988.8 183,594.0 Wiesbaden AHC 594 10.1 128.4 1 594 76,269.6 41,185.6 VIPRR Clinic (16 countries) 371 NP Varies 5 1870 NP 1,302,000 Total 3,778 8,307.5 1,505,995 2,115,237.3 Originating Site . Number of encounters . % Usage by Local Pop. . Miles (roundtrip)a . Days (roundtrip)b . Time Savings (days) . Travel Savings (miles) . Per Diem Savingsc . Correctional Facility, Sembach, Germany 9 NP 0 0 0 0 0.0 Baumholder AHC 7 0.2 55.8 0.5 3.5 390.6 210.9 Brussels AHC 29 3.7 421.2 2 58 12,214.8 6,596.0 Eskan Village, Saudi Arabia 15 NP 6,100.8 7 105 91,512 49,416.5 Grafenwoehr AHC 325 4.0 537.6 2 650 174,720 94,348.8 Hohenfels AHC 79 3.5 452.4 1 79 35,739.6 19,299.4 In-home 26 NP 210 1 26 5,460 2,948.4 Izmir, Turkey 1 NP 3,192 7 7 3,192 1,723.7 Katterbach AHC 132 3.1 326.4 1 132 43,084.8 23,265.8 Lakenhealth Air Base 1 NP 1,017.6 3 3 1,017.6 549.5 Livorno AHC 1 0.2 1,260 5 5 1,260 680.4 Mihail Kogalniceanu, Romania 5 NP 2,510.4 4 20 12,552 6,778.1 Naples Naval Air Station 1 NP 1,687.2 4 4 1,687.2 911.1 Stavanger, Norway 1 NP 1,806 5 5 1,806 975.2 Shape AHC 470 13.5 452.4 2 940 212,628 114,819.1 Sigonella Naval Air Station 2 NP 2,408 5 10 4,816 2,600.6 Spangdahlem Air Base 94 1.9 200.4 1 94 18,837.6 10,172.3 Stuttgart AHC (2 locations) 539 5.6 232.8 1 539 125,479.2 67,758.8 Vicenza AHC 339 4.0 1,012.8 5 1695 343,339.2 185,403.2 VilseckAHC 734 9.2 463.2 2 1468 339,988.8 183,594.0 Wiesbaden AHC 594 10.1 128.4 1 594 76,269.6 41,185.6 VIPRR Clinic (16 countries) 371 NP Varies 5 1870 NP 1,302,000 Total 3,778 8,307.5 1,505,995 2,115,237.3 aCalculated using Google Maps (https://maps.google.com). bEstimated based on driving distance and country; c2016 Joint Travel Regulation reimbursement of $0.54 per mile (does not include lodging and M + IE); NP, not performed. Open in new tab Licensed independent providers conducted 1,827 new consultations, 1,187 follow-up visits, and 371 readiness exams. The remaining encounters were performed by credentialed providers such as nutritionists, psychologists, and therapists. VH visit E + M complexity ranged from 99211 to 99205 with an average work relative value unit (wRVU) for new and follow-up visits of 1.46 and 1.02, respectively. Overall service utilization ranged from less than 1% to 39.9%. Eight clinics, to include sleep medicine, outpatient nutrition, the VIPRR clinic, orthopedics, general surgery, behavioral health, allergy, and otolaryngology accounted for 80.1% of all telehealth visits (Table II). LRMC Clinical Operations provided total outpatient visits for 26 (96.4%) specialties engaged in synchronous VH in CY16. One specialty, pre-op/anesthesia, did not have a defined Medical Expense and Performance Reporting System code but only accounted for 24 (0.6%) VH visits. Individual specialty VH usage as a percentage of the specialty’s total outpatient visits varied greatly with a median (range) of 2.1% (0.1–39.9%) (Table II). Excluding the VIPRR clinic, nineteen (70.4%) specialties utilized telehealth for at least 1% of their outpatient visits while five (18.5%) specialties utilized VH for more than 5% of outpatient encounters (Table II). The 3,778 telehealth visits represented 3.5% (3,778/107,887) of all outpatient visits for these 27 specialties. Mean monthly provider documentation compliance with “GT” synchronous telehealth modifier in the AHLTA disposition section was 80.6 ± 3.9%. Mean monthly originating site compliance with the Q3014 Originating Site Fee code was 92.8 ± 2.6%. TABLE II. January–December 2016 Synchronous Telehealth (sTH) Encounters Specialty . # TH Visits . % all sTH . % All Servicea . % SPECb . Sleep medicine 1,296 34.3 28.4 67.0 Nutrition 405 10.7 14.1 52.6 Virtual Integrated Patient Readiness and Recapture (VIPRR) clinic 371 9.8 39.9 100.0 Orthopedic surgery 284 7.5 1.5 26.1 General surgery 205 5.4 4.5 44.9 Behavioral health 185 4.9 1.5 18.0 Allergy 157 4.2 9.8 61.8 Otolaryngology 126 3.3 2.5 66.1 Pain management 85 2.2 1.7 3.9 Pediatric developmental 80 2.1 19.1 71.8 Pediatric gastroenterology 75 2.0 24.3 61.6 Podiatry 74 2.0 2.5 20.0 Neurosurgery 63 1.7 2.7 37.9 mTBI 51 1.3 2.8 25.0 Urology 51 1.3 2.3 76.6 Occupational therapy 40 1.1 1.3 0.0 Pulmonary 39 1.0 3.0 34.3 OB/GYN 36 1.0 0.3 44.1 Cardiology 31 0.8 0.8 46.7 Rheumatology 24 0.6 1.6 8.7 Pre-op/anesthesia 24 0.6 NP 100.0 Endocrinology 20 0.5 1.7 42.1 Physical medicine and rehabilitation 19 0.5 0.2 70.6 Hematology/oncology 12 0.3 1.0 75.0 Plastic surgery 10 0.3 0.9 33.3 Speech pathology 9 0.2 0.5 0.0 Infectious disease 3 0.1 0.3 33.3 Neurology 3 0.1 0.1 0.0 Total 3,778 Specialty . # TH Visits . % all sTH . % All Servicea . % SPECb . Sleep medicine 1,296 34.3 28.4 67.0 Nutrition 405 10.7 14.1 52.6 Virtual Integrated Patient Readiness and Recapture (VIPRR) clinic 371 9.8 39.9 100.0 Orthopedic surgery 284 7.5 1.5 26.1 General surgery 205 5.4 4.5 44.9 Behavioral health 185 4.9 1.5 18.0 Allergy 157 4.2 9.8 61.8 Otolaryngology 126 3.3 2.5 66.1 Pain management 85 2.2 1.7 3.9 Pediatric developmental 80 2.1 19.1 71.8 Pediatric gastroenterology 75 2.0 24.3 61.6 Podiatry 74 2.0 2.5 20.0 Neurosurgery 63 1.7 2.7 37.9 mTBI 51 1.3 2.8 25.0 Urology 51 1.3 2.3 76.6 Occupational therapy 40 1.1 1.3 0.0 Pulmonary 39 1.0 3.0 34.3 OB/GYN 36 1.0 0.3 44.1 Cardiology 31 0.8 0.8 46.7 Rheumatology 24 0.6 1.6 8.7 Pre-op/anesthesia 24 0.6 NP 100.0 Endocrinology 20 0.5 1.7 42.1 Physical medicine and rehabilitation 19 0.5 0.2 70.6 Hematology/oncology 12 0.3 1.0 75.0 Plastic surgery 10 0.3 0.9 33.3 Speech pathology 9 0.2 0.5 0.0 Infectious disease 3 0.1 0.3 33.3 Neurology 3 0.1 0.1 0.0 Total 3,778 aPercent all encounters conducted via sTH for that specialty. bPercent of sTH visits that are new visits. Open in new tab TABLE II. January–December 2016 Synchronous Telehealth (sTH) Encounters Specialty . # TH Visits . % all sTH . % All Servicea . % SPECb . Sleep medicine 1,296 34.3 28.4 67.0 Nutrition 405 10.7 14.1 52.6 Virtual Integrated Patient Readiness and Recapture (VIPRR) clinic 371 9.8 39.9 100.0 Orthopedic surgery 284 7.5 1.5 26.1 General surgery 205 5.4 4.5 44.9 Behavioral health 185 4.9 1.5 18.0 Allergy 157 4.2 9.8 61.8 Otolaryngology 126 3.3 2.5 66.1 Pain management 85 2.2 1.7 3.9 Pediatric developmental 80 2.1 19.1 71.8 Pediatric gastroenterology 75 2.0 24.3 61.6 Podiatry 74 2.0 2.5 20.0 Neurosurgery 63 1.7 2.7 37.9 mTBI 51 1.3 2.8 25.0 Urology 51 1.3 2.3 76.6 Occupational therapy 40 1.1 1.3 0.0 Pulmonary 39 1.0 3.0 34.3 OB/GYN 36 1.0 0.3 44.1 Cardiology 31 0.8 0.8 46.7 Rheumatology 24 0.6 1.6 8.7 Pre-op/anesthesia 24 0.6 NP 100.0 Endocrinology 20 0.5 1.7 42.1 Physical medicine and rehabilitation 19 0.5 0.2 70.6 Hematology/oncology 12 0.3 1.0 75.0 Plastic surgery 10 0.3 0.9 33.3 Speech pathology 9 0.2 0.5 0.0 Infectious disease 3 0.1 0.3 33.3 Neurology 3 0.1 0.1 0.0 Total 3,778 Specialty . # TH Visits . % all sTH . % All Servicea . % SPECb . Sleep medicine 1,296 34.3 28.4 67.0 Nutrition 405 10.7 14.1 52.6 Virtual Integrated Patient Readiness and Recapture (VIPRR) clinic 371 9.8 39.9 100.0 Orthopedic surgery 284 7.5 1.5 26.1 General surgery 205 5.4 4.5 44.9 Behavioral health 185 4.9 1.5 18.0 Allergy 157 4.2 9.8 61.8 Otolaryngology 126 3.3 2.5 66.1 Pain management 85 2.2 1.7 3.9 Pediatric developmental 80 2.1 19.1 71.8 Pediatric gastroenterology 75 2.0 24.3 61.6 Podiatry 74 2.0 2.5 20.0 Neurosurgery 63 1.7 2.7 37.9 mTBI 51 1.3 2.8 25.0 Urology 51 1.3 2.3 76.6 Occupational therapy 40 1.1 1.3 0.0 Pulmonary 39 1.0 3.0 34.3 OB/GYN 36 1.0 0.3 44.1 Cardiology 31 0.8 0.8 46.7 Rheumatology 24 0.6 1.6 8.7 Pre-op/anesthesia 24 0.6 NP 100.0 Endocrinology 20 0.5 1.7 42.1 Physical medicine and rehabilitation 19 0.5 0.2 70.6 Hematology/oncology 12 0.3 1.0 75.0 Plastic surgery 10 0.3 0.9 33.3 Speech pathology 9 0.2 0.5 0.0 Infectious disease 3 0.1 0.3 33.3 Neurology 3 0.1 0.1 0.0 Total 3,778 aPercent all encounters conducted via sTH for that specialty. bPercent of sTH visits that are new visits. Open in new tab Forty-eight (33.8% survey response) providers returned a survey from 22 specialty clinics. Two providers indicated they had not performed any synchronous telehealth encounters and were not included in the analysis. Median (range) survey response per specialty was 2 (1–8). Eight surveys were completed for behavioral health providers, 13 for medicine specialties, 15 for surgical services, and 10 for primary care providers. 89.1% were either Skill Type I (i.e., M.D./D.O.) or Skill Type 2 (i.e., Nurse Practitioner or Physician Assistant). Providers from four different disciplines differed significantly for 15 of the 42 questions (Table III). Generally, medicine specialties and primary care had a more favorable opinion of synchronous telehealth compared to behavioral health and surgical subspecialties. Overall, 42 (91%) providers felt that patients appreciated being able to see them through telehealth and 43 (93%) providers responded that telehealth was a valuable resource for patients. TABLE III. Provider Responses Towards Synchronous Telehealth* . Behavioral health . Medicine subspecialties . Surgical specialties . Primary care . p* . # surveys returned 8 13 15 10 The training I received was appropriate 3.88 (0.6) 4.31 (0.5) 4.47 (0.6) 4.5 (0.7) 0.30 Using the desktop computer application for telehealth is easy 3.75 (1.1) 4.46 (0.6) 4.33 (0.6) 4.5 (0.7) 0.33 My patients appreciate being able to see me via telehealth 4.13 (0.6) 4.69 (0.5) 4.8 (0.4) 4.2 (0.9) 0.06 How often does the patient presenter understand my specialty needs during the visit? 3.13 (0.8) 3.92 (0.8) 3.9 (0.7) 4.1 (0.9) 0.31 How often do NEW patients who I see via telehealth still have to see me IN-PERSON for a follow-up visit? 1.88 (1.3) 3.23 (0.7) 2.8 (1.1) 2.5 (1.4) 0.27 How often do patients who I see via telehealth for a FOLLOW-UP visit still have to see me IN-PERSON for an additional follow-up visit? 1.75 (0.7) 2.54 (0.6) 2.13 (1.0) 2.1 (0.9) 0.62 Telehealth visits are incorporated into my normal clinic template 3.63 (1.0) 4.08 (0.7) 3.87 (0.8) 3.80 (1.3) 0.84 How often is evaluating patients IN-PERSON MORE personally satisfying than seeing patients via telehealth? 4.75 (0.7) 3.31 (0.7) 3.93 (1.1) 3.2 (1.1) <0.01 Telehealth saves the patient time 3.75 (0.4) 4.92 (0.3) 4.6 (0.7) 4.6 (0.5) 0.01 Telehealth saves the patient or their unit money 3.63 (0.5) 4.85 (0.5) 4.8 (0.4) 4.6 (0.5) <0.001 Telehealth is a valuable resource for patients 4.13 (0.6) 4.92 (0.3) 4.47 (0.9) 4.7 (0.5) 0.08 My overall interest in using telehealth has decreased since I first starting using it 2.5 (1.0) 1.92 (1.1) 2.07 (1.2) 1.90 (1.0) 0.34 I need additional technical training on using the computer telehealth application 2.13 (0.8) 1.85 (0.9) 1.87 (1.0) 1.8 (0.4) 0.51 It was cumbersome to be credentialed for telehealth at other locations 2.0 (0) 2.0 (0.9) 2.27 (1.1) 3.0 (1.0) 0.31 Telehealth is integrated into my normal clinic schedule 3.75 (0.7) 4.15 (0.8) 3.93 (0.6) 3.9 (1.0) 0.76 Scheduling telehealth visits seems easy for my staff 3.25 (0.7) 3.46 (1.1) 3.64 (0.7) 3.9 (1.0) 0.47 How often would conducting a NEW telehealth visit to the patient’s home be as good as a NEW telehealth visit to a clinic site? 2.43 (1.5) 2.77 (1.0) 3.07 (1.3) 3.5 (0.8) 0.24 How often would conducting a FOLLOW-UP telehealth visit to the patient’s home be as good as a telehealth visit to a clinic site? 2.86 (1.5) 3.46 (0.8) 3.5 (1.1) 3.5 (0.8) 0.49 How often does it take MORE time to see a NEW patient via telehealth compared to an IN-PERSON visit? 3.25 (1.2) 2.15 (0.5) 2.93 (1.3) 2.63 (1.2) 0.28 How often does it take MORE time to see a FOLLOW-UP patient via telehealth compared to an IN-PERSON visit? 2.88 (1.3) 2.08 (0.5) 2.5 (1.3) 2.4 (0.9) 0.62 I have a favorable opinion of telehealth as an option for patients 3.63 (0.7) 4.69 (0.5) 4.33 (0.5) 4.5 (0.7) <0.001 My clinical leadership supports telehealth 4.0 (0) 4.85 (0.4) 4.53 (0.7) 4.7 (0.5) <0.01 My clinical leadership wants me to do more telehealth 3.75 (0.7) 3.69 (0.8) 3.87 (0.8) 4.0 (0.9) 0.45 I prefer to see patients only at specific clinic sites 2.75 (0.8) 2.62 (0.7) 2.4 0(1.1) 1.89 (0.9) 0.35 How often is telehealth well-suited to evaluate NEW patients? 2.13 (0.6) 3.38 (0.9) 3.2 (0.9) 4.0 (0.6) <0.001 How often is telehealth well-suited to evaluate FOLLOW-UP patients? 3.5 (0.9) 4.0 (0.6) 3.8 (0.9) 4.2 (0.7) 0.14 How often is the audio connection clear? 4.0 (0.5) 4.31 (0.8) 4.53 (0.7) 4.5 (0.7) 0.10 How often is the video connection clear? 4.13 (0.6) 4.31 (0.8) 4.53 (0.5) 4.6 (0.7) 0.13 How often is the patient presenter technically competent when using the telehealth equipment? 3.75 (0.8) 4.23 (0.6) 4.2 (0.8) 4.7 (0.5) 0.11 How often are you able to connect within 15 minutes of the appointment time? 4.25 (0.8) 4.77 (0.4) 4.67 (0.6) 4.9 (0.3) 0.03 How often are you on-time (<15 min from appointment time) to see your IN-PERSON clinic patients? 4.5 (0.7) 4.15 (0.7) 4.4 (0.7) 4.8 (0.4) 0.30 How often do you add the “GT” modifier to the AHLTA note? 4.63 (0.5) 4.77 (0.4) 3.67 (1.7) 4.5 (0.5) 0.11 A telehealth visit is better than a telephone call for FOLLOW-UP visits 4.0 (0.9) 4.31 (0.8) 3.73 (0.9) 4.6 (0.8) 0.09 How often do you use the Share Content feature? 1.38 (0.7) 2.38 (1.3) 1.87 (1.2) 3.9 (0.9) <0.01 How often are service-specific screening/intake forms completed by the time of the telehealth appointment? 2.88 (1.4) 3.0 (0.9) 2.71 (0.9) 2.70 (1.7) 0.95 What percentage of NEW patients do you think you would like to see via telehealth? 12.2 (16) 32.1 (27) 8.5 (5) 36.6 (29) 0.02 What percentage of FOLLOW-UP patients do you think you would like to see via telehealth? 24.3 (23) 46.7 (30) 43.8 (32) 47.5 (28) 0.4 On average, a NEW telehealth visit takes how many minutes? 71.3 (12) 34.4 (9) 28.5 (11) 50.5 (12) <0.001 On average a FOLLOW-UP telehealth visit takes how many minutes? 40.4 (11) 21.7 (6) 18.8 (8) 38.6 (11) <0.001 On average, a NEW IN-PERSON visit takes how many minutes? 77.5 (13) 41.7 (13) 30.2 (13) 54.8 (14) <0.001 On average, a FOLLOW-UP IN-PERSON visit takes how many minutes 48.3 (13) 23.9 (7) 16.9 (8) 38.6 (11) <0.001 How often do you use the following telehealth cart features?  Otoscope for EAR exam 1.0 (0) 1.62 (1) 1.87 (1) 1.0 (0) 0.11  Otoscope for NASAL exam 1.0 (0) 1.69 (1) 1.87 (1) 1.0 (0) 0.10  HD camera for ORAL exam 1.0 (0) 2.38 (1.5) 2.40 (2) 1.0 (0) 0.01  Stethescope 1.0 (0) 1.77 (0.8) 1.6 (1) 1.0 (0) 0.049  Bladder scanner 1.0 (0) 1.0 (0) 1.2 (0.5) 1.0 (0) 0.51 . Behavioral health . Medicine subspecialties . Surgical specialties . Primary care . p* . # surveys returned 8 13 15 10 The training I received was appropriate 3.88 (0.6) 4.31 (0.5) 4.47 (0.6) 4.5 (0.7) 0.30 Using the desktop computer application for telehealth is easy 3.75 (1.1) 4.46 (0.6) 4.33 (0.6) 4.5 (0.7) 0.33 My patients appreciate being able to see me via telehealth 4.13 (0.6) 4.69 (0.5) 4.8 (0.4) 4.2 (0.9) 0.06 How often does the patient presenter understand my specialty needs during the visit? 3.13 (0.8) 3.92 (0.8) 3.9 (0.7) 4.1 (0.9) 0.31 How often do NEW patients who I see via telehealth still have to see me IN-PERSON for a follow-up visit? 1.88 (1.3) 3.23 (0.7) 2.8 (1.1) 2.5 (1.4) 0.27 How often do patients who I see via telehealth for a FOLLOW-UP visit still have to see me IN-PERSON for an additional follow-up visit? 1.75 (0.7) 2.54 (0.6) 2.13 (1.0) 2.1 (0.9) 0.62 Telehealth visits are incorporated into my normal clinic template 3.63 (1.0) 4.08 (0.7) 3.87 (0.8) 3.80 (1.3) 0.84 How often is evaluating patients IN-PERSON MORE personally satisfying than seeing patients via telehealth? 4.75 (0.7) 3.31 (0.7) 3.93 (1.1) 3.2 (1.1) <0.01 Telehealth saves the patient time 3.75 (0.4) 4.92 (0.3) 4.6 (0.7) 4.6 (0.5) 0.01 Telehealth saves the patient or their unit money 3.63 (0.5) 4.85 (0.5) 4.8 (0.4) 4.6 (0.5) <0.001 Telehealth is a valuable resource for patients 4.13 (0.6) 4.92 (0.3) 4.47 (0.9) 4.7 (0.5) 0.08 My overall interest in using telehealth has decreased since I first starting using it 2.5 (1.0) 1.92 (1.1) 2.07 (1.2) 1.90 (1.0) 0.34 I need additional technical training on using the computer telehealth application 2.13 (0.8) 1.85 (0.9) 1.87 (1.0) 1.8 (0.4) 0.51 It was cumbersome to be credentialed for telehealth at other locations 2.0 (0) 2.0 (0.9) 2.27 (1.1) 3.0 (1.0) 0.31 Telehealth is integrated into my normal clinic schedule 3.75 (0.7) 4.15 (0.8) 3.93 (0.6) 3.9 (1.0) 0.76 Scheduling telehealth visits seems easy for my staff 3.25 (0.7) 3.46 (1.1) 3.64 (0.7) 3.9 (1.0) 0.47 How often would conducting a NEW telehealth visit to the patient’s home be as good as a NEW telehealth visit to a clinic site? 2.43 (1.5) 2.77 (1.0) 3.07 (1.3) 3.5 (0.8) 0.24 How often would conducting a FOLLOW-UP telehealth visit to the patient’s home be as good as a telehealth visit to a clinic site? 2.86 (1.5) 3.46 (0.8) 3.5 (1.1) 3.5 (0.8) 0.49 How often does it take MORE time to see a NEW patient via telehealth compared to an IN-PERSON visit? 3.25 (1.2) 2.15 (0.5) 2.93 (1.3) 2.63 (1.2) 0.28 How often does it take MORE time to see a FOLLOW-UP patient via telehealth compared to an IN-PERSON visit? 2.88 (1.3) 2.08 (0.5) 2.5 (1.3) 2.4 (0.9) 0.62 I have a favorable opinion of telehealth as an option for patients 3.63 (0.7) 4.69 (0.5) 4.33 (0.5) 4.5 (0.7) <0.001 My clinical leadership supports telehealth 4.0 (0) 4.85 (0.4) 4.53 (0.7) 4.7 (0.5) <0.01 My clinical leadership wants me to do more telehealth 3.75 (0.7) 3.69 (0.8) 3.87 (0.8) 4.0 (0.9) 0.45 I prefer to see patients only at specific clinic sites 2.75 (0.8) 2.62 (0.7) 2.4 0(1.1) 1.89 (0.9) 0.35 How often is telehealth well-suited to evaluate NEW patients? 2.13 (0.6) 3.38 (0.9) 3.2 (0.9) 4.0 (0.6) <0.001 How often is telehealth well-suited to evaluate FOLLOW-UP patients? 3.5 (0.9) 4.0 (0.6) 3.8 (0.9) 4.2 (0.7) 0.14 How often is the audio connection clear? 4.0 (0.5) 4.31 (0.8) 4.53 (0.7) 4.5 (0.7) 0.10 How often is the video connection clear? 4.13 (0.6) 4.31 (0.8) 4.53 (0.5) 4.6 (0.7) 0.13 How often is the patient presenter technically competent when using the telehealth equipment? 3.75 (0.8) 4.23 (0.6) 4.2 (0.8) 4.7 (0.5) 0.11 How often are you able to connect within 15 minutes of the appointment time? 4.25 (0.8) 4.77 (0.4) 4.67 (0.6) 4.9 (0.3) 0.03 How often are you on-time (<15 min from appointment time) to see your IN-PERSON clinic patients? 4.5 (0.7) 4.15 (0.7) 4.4 (0.7) 4.8 (0.4) 0.30 How often do you add the “GT” modifier to the AHLTA note? 4.63 (0.5) 4.77 (0.4) 3.67 (1.7) 4.5 (0.5) 0.11 A telehealth visit is better than a telephone call for FOLLOW-UP visits 4.0 (0.9) 4.31 (0.8) 3.73 (0.9) 4.6 (0.8) 0.09 How often do you use the Share Content feature? 1.38 (0.7) 2.38 (1.3) 1.87 (1.2) 3.9 (0.9) <0.01 How often are service-specific screening/intake forms completed by the time of the telehealth appointment? 2.88 (1.4) 3.0 (0.9) 2.71 (0.9) 2.70 (1.7) 0.95 What percentage of NEW patients do you think you would like to see via telehealth? 12.2 (16) 32.1 (27) 8.5 (5) 36.6 (29) 0.02 What percentage of FOLLOW-UP patients do you think you would like to see via telehealth? 24.3 (23) 46.7 (30) 43.8 (32) 47.5 (28) 0.4 On average, a NEW telehealth visit takes how many minutes? 71.3 (12) 34.4 (9) 28.5 (11) 50.5 (12) <0.001 On average a FOLLOW-UP telehealth visit takes how many minutes? 40.4 (11) 21.7 (6) 18.8 (8) 38.6 (11) <0.001 On average, a NEW IN-PERSON visit takes how many minutes? 77.5 (13) 41.7 (13) 30.2 (13) 54.8 (14) <0.001 On average, a FOLLOW-UP IN-PERSON visit takes how many minutes 48.3 (13) 23.9 (7) 16.9 (8) 38.6 (11) <0.001 How often do you use the following telehealth cart features?  Otoscope for EAR exam 1.0 (0) 1.62 (1) 1.87 (1) 1.0 (0) 0.11  Otoscope for NASAL exam 1.0 (0) 1.69 (1) 1.87 (1) 1.0 (0) 0.10  HD camera for ORAL exam 1.0 (0) 2.38 (1.5) 2.40 (2) 1.0 (0) 0.01  Stethescope 1.0 (0) 1.77 (0.8) 1.6 (1) 1.0 (0) 0.049  Bladder scanner 1.0 (0) 1.0 (0) 1.2 (0.5) 1.0 (0) 0.51 *Results are presented as the mean (standard deviation) based on a 5-point Likert scale. Open in new tab TABLE III. Provider Responses Towards Synchronous Telehealth* . Behavioral health . Medicine subspecialties . Surgical specialties . Primary care . p* . # surveys returned 8 13 15 10 The training I received was appropriate 3.88 (0.6) 4.31 (0.5) 4.47 (0.6) 4.5 (0.7) 0.30 Using the desktop computer application for telehealth is easy 3.75 (1.1) 4.46 (0.6) 4.33 (0.6) 4.5 (0.7) 0.33 My patients appreciate being able to see me via telehealth 4.13 (0.6) 4.69 (0.5) 4.8 (0.4) 4.2 (0.9) 0.06 How often does the patient presenter understand my specialty needs during the visit? 3.13 (0.8) 3.92 (0.8) 3.9 (0.7) 4.1 (0.9) 0.31 How often do NEW patients who I see via telehealth still have to see me IN-PERSON for a follow-up visit? 1.88 (1.3) 3.23 (0.7) 2.8 (1.1) 2.5 (1.4) 0.27 How often do patients who I see via telehealth for a FOLLOW-UP visit still have to see me IN-PERSON for an additional follow-up visit? 1.75 (0.7) 2.54 (0.6) 2.13 (1.0) 2.1 (0.9) 0.62 Telehealth visits are incorporated into my normal clinic template 3.63 (1.0) 4.08 (0.7) 3.87 (0.8) 3.80 (1.3) 0.84 How often is evaluating patients IN-PERSON MORE personally satisfying than seeing patients via telehealth? 4.75 (0.7) 3.31 (0.7) 3.93 (1.1) 3.2 (1.1) <0.01 Telehealth saves the patient time 3.75 (0.4) 4.92 (0.3) 4.6 (0.7) 4.6 (0.5) 0.01 Telehealth saves the patient or their unit money 3.63 (0.5) 4.85 (0.5) 4.8 (0.4) 4.6 (0.5) <0.001 Telehealth is a valuable resource for patients 4.13 (0.6) 4.92 (0.3) 4.47 (0.9) 4.7 (0.5) 0.08 My overall interest in using telehealth has decreased since I first starting using it 2.5 (1.0) 1.92 (1.1) 2.07 (1.2) 1.90 (1.0) 0.34 I need additional technical training on using the computer telehealth application 2.13 (0.8) 1.85 (0.9) 1.87 (1.0) 1.8 (0.4) 0.51 It was cumbersome to be credentialed for telehealth at other locations 2.0 (0) 2.0 (0.9) 2.27 (1.1) 3.0 (1.0) 0.31 Telehealth is integrated into my normal clinic schedule 3.75 (0.7) 4.15 (0.8) 3.93 (0.6) 3.9 (1.0) 0.76 Scheduling telehealth visits seems easy for my staff 3.25 (0.7) 3.46 (1.1) 3.64 (0.7) 3.9 (1.0) 0.47 How often would conducting a NEW telehealth visit to the patient’s home be as good as a NEW telehealth visit to a clinic site? 2.43 (1.5) 2.77 (1.0) 3.07 (1.3) 3.5 (0.8) 0.24 How often would conducting a FOLLOW-UP telehealth visit to the patient’s home be as good as a telehealth visit to a clinic site? 2.86 (1.5) 3.46 (0.8) 3.5 (1.1) 3.5 (0.8) 0.49 How often does it take MORE time to see a NEW patient via telehealth compared to an IN-PERSON visit? 3.25 (1.2) 2.15 (0.5) 2.93 (1.3) 2.63 (1.2) 0.28 How often does it take MORE time to see a FOLLOW-UP patient via telehealth compared to an IN-PERSON visit? 2.88 (1.3) 2.08 (0.5) 2.5 (1.3) 2.4 (0.9) 0.62 I have a favorable opinion of telehealth as an option for patients 3.63 (0.7) 4.69 (0.5) 4.33 (0.5) 4.5 (0.7) <0.001 My clinical leadership supports telehealth 4.0 (0) 4.85 (0.4) 4.53 (0.7) 4.7 (0.5) <0.01 My clinical leadership wants me to do more telehealth 3.75 (0.7) 3.69 (0.8) 3.87 (0.8) 4.0 (0.9) 0.45 I prefer to see patients only at specific clinic sites 2.75 (0.8) 2.62 (0.7) 2.4 0(1.1) 1.89 (0.9) 0.35 How often is telehealth well-suited to evaluate NEW patients? 2.13 (0.6) 3.38 (0.9) 3.2 (0.9) 4.0 (0.6) <0.001 How often is telehealth well-suited to evaluate FOLLOW-UP patients? 3.5 (0.9) 4.0 (0.6) 3.8 (0.9) 4.2 (0.7) 0.14 How often is the audio connection clear? 4.0 (0.5) 4.31 (0.8) 4.53 (0.7) 4.5 (0.7) 0.10 How often is the video connection clear? 4.13 (0.6) 4.31 (0.8) 4.53 (0.5) 4.6 (0.7) 0.13 How often is the patient presenter technically competent when using the telehealth equipment? 3.75 (0.8) 4.23 (0.6) 4.2 (0.8) 4.7 (0.5) 0.11 How often are you able to connect within 15 minutes of the appointment time? 4.25 (0.8) 4.77 (0.4) 4.67 (0.6) 4.9 (0.3) 0.03 How often are you on-time (<15 min from appointment time) to see your IN-PERSON clinic patients? 4.5 (0.7) 4.15 (0.7) 4.4 (0.7) 4.8 (0.4) 0.30 How often do you add the “GT” modifier to the AHLTA note? 4.63 (0.5) 4.77 (0.4) 3.67 (1.7) 4.5 (0.5) 0.11 A telehealth visit is better than a telephone call for FOLLOW-UP visits 4.0 (0.9) 4.31 (0.8) 3.73 (0.9) 4.6 (0.8) 0.09 How often do you use the Share Content feature? 1.38 (0.7) 2.38 (1.3) 1.87 (1.2) 3.9 (0.9) <0.01 How often are service-specific screening/intake forms completed by the time of the telehealth appointment? 2.88 (1.4) 3.0 (0.9) 2.71 (0.9) 2.70 (1.7) 0.95 What percentage of NEW patients do you think you would like to see via telehealth? 12.2 (16) 32.1 (27) 8.5 (5) 36.6 (29) 0.02 What percentage of FOLLOW-UP patients do you think you would like to see via telehealth? 24.3 (23) 46.7 (30) 43.8 (32) 47.5 (28) 0.4 On average, a NEW telehealth visit takes how many minutes? 71.3 (12) 34.4 (9) 28.5 (11) 50.5 (12) <0.001 On average a FOLLOW-UP telehealth visit takes how many minutes? 40.4 (11) 21.7 (6) 18.8 (8) 38.6 (11) <0.001 On average, a NEW IN-PERSON visit takes how many minutes? 77.5 (13) 41.7 (13) 30.2 (13) 54.8 (14) <0.001 On average, a FOLLOW-UP IN-PERSON visit takes how many minutes 48.3 (13) 23.9 (7) 16.9 (8) 38.6 (11) <0.001 How often do you use the following telehealth cart features?  Otoscope for EAR exam 1.0 (0) 1.62 (1) 1.87 (1) 1.0 (0) 0.11  Otoscope for NASAL exam 1.0 (0) 1.69 (1) 1.87 (1) 1.0 (0) 0.10  HD camera for ORAL exam 1.0 (0) 2.38 (1.5) 2.40 (2) 1.0 (0) 0.01  Stethescope 1.0 (0) 1.77 (0.8) 1.6 (1) 1.0 (0) 0.049  Bladder scanner 1.0 (0) 1.0 (0) 1.2 (0.5) 1.0 (0) 0.51 . Behavioral health . Medicine subspecialties . Surgical specialties . Primary care . p* . # surveys returned 8 13 15 10 The training I received was appropriate 3.88 (0.6) 4.31 (0.5) 4.47 (0.6) 4.5 (0.7) 0.30 Using the desktop computer application for telehealth is easy 3.75 (1.1) 4.46 (0.6) 4.33 (0.6) 4.5 (0.7) 0.33 My patients appreciate being able to see me via telehealth 4.13 (0.6) 4.69 (0.5) 4.8 (0.4) 4.2 (0.9) 0.06 How often does the patient presenter understand my specialty needs during the visit? 3.13 (0.8) 3.92 (0.8) 3.9 (0.7) 4.1 (0.9) 0.31 How often do NEW patients who I see via telehealth still have to see me IN-PERSON for a follow-up visit? 1.88 (1.3) 3.23 (0.7) 2.8 (1.1) 2.5 (1.4) 0.27 How often do patients who I see via telehealth for a FOLLOW-UP visit still have to see me IN-PERSON for an additional follow-up visit? 1.75 (0.7) 2.54 (0.6) 2.13 (1.0) 2.1 (0.9) 0.62 Telehealth visits are incorporated into my normal clinic template 3.63 (1.0) 4.08 (0.7) 3.87 (0.8) 3.80 (1.3) 0.84 How often is evaluating patients IN-PERSON MORE personally satisfying than seeing patients via telehealth? 4.75 (0.7) 3.31 (0.7) 3.93 (1.1) 3.2 (1.1) <0.01 Telehealth saves the patient time 3.75 (0.4) 4.92 (0.3) 4.6 (0.7) 4.6 (0.5) 0.01 Telehealth saves the patient or their unit money 3.63 (0.5) 4.85 (0.5) 4.8 (0.4) 4.6 (0.5) <0.001 Telehealth is a valuable resource for patients 4.13 (0.6) 4.92 (0.3) 4.47 (0.9) 4.7 (0.5) 0.08 My overall interest in using telehealth has decreased since I first starting using it 2.5 (1.0) 1.92 (1.1) 2.07 (1.2) 1.90 (1.0) 0.34 I need additional technical training on using the computer telehealth application 2.13 (0.8) 1.85 (0.9) 1.87 (1.0) 1.8 (0.4) 0.51 It was cumbersome to be credentialed for telehealth at other locations 2.0 (0) 2.0 (0.9) 2.27 (1.1) 3.0 (1.0) 0.31 Telehealth is integrated into my normal clinic schedule 3.75 (0.7) 4.15 (0.8) 3.93 (0.6) 3.9 (1.0) 0.76 Scheduling telehealth visits seems easy for my staff 3.25 (0.7) 3.46 (1.1) 3.64 (0.7) 3.9 (1.0) 0.47 How often would conducting a NEW telehealth visit to the patient’s home be as good as a NEW telehealth visit to a clinic site? 2.43 (1.5) 2.77 (1.0) 3.07 (1.3) 3.5 (0.8) 0.24 How often would conducting a FOLLOW-UP telehealth visit to the patient’s home be as good as a telehealth visit to a clinic site? 2.86 (1.5) 3.46 (0.8) 3.5 (1.1) 3.5 (0.8) 0.49 How often does it take MORE time to see a NEW patient via telehealth compared to an IN-PERSON visit? 3.25 (1.2) 2.15 (0.5) 2.93 (1.3) 2.63 (1.2) 0.28 How often does it take MORE time to see a FOLLOW-UP patient via telehealth compared to an IN-PERSON visit? 2.88 (1.3) 2.08 (0.5) 2.5 (1.3) 2.4 (0.9) 0.62 I have a favorable opinion of telehealth as an option for patients 3.63 (0.7) 4.69 (0.5) 4.33 (0.5) 4.5 (0.7) <0.001 My clinical leadership supports telehealth 4.0 (0) 4.85 (0.4) 4.53 (0.7) 4.7 (0.5) <0.01 My clinical leadership wants me to do more telehealth 3.75 (0.7) 3.69 (0.8) 3.87 (0.8) 4.0 (0.9) 0.45 I prefer to see patients only at specific clinic sites 2.75 (0.8) 2.62 (0.7) 2.4 0(1.1) 1.89 (0.9) 0.35 How often is telehealth well-suited to evaluate NEW patients? 2.13 (0.6) 3.38 (0.9) 3.2 (0.9) 4.0 (0.6) <0.001 How often is telehealth well-suited to evaluate FOLLOW-UP patients? 3.5 (0.9) 4.0 (0.6) 3.8 (0.9) 4.2 (0.7) 0.14 How often is the audio connection clear? 4.0 (0.5) 4.31 (0.8) 4.53 (0.7) 4.5 (0.7) 0.10 How often is the video connection clear? 4.13 (0.6) 4.31 (0.8) 4.53 (0.5) 4.6 (0.7) 0.13 How often is the patient presenter technically competent when using the telehealth equipment? 3.75 (0.8) 4.23 (0.6) 4.2 (0.8) 4.7 (0.5) 0.11 How often are you able to connect within 15 minutes of the appointment time? 4.25 (0.8) 4.77 (0.4) 4.67 (0.6) 4.9 (0.3) 0.03 How often are you on-time (<15 min from appointment time) to see your IN-PERSON clinic patients? 4.5 (0.7) 4.15 (0.7) 4.4 (0.7) 4.8 (0.4) 0.30 How often do you add the “GT” modifier to the AHLTA note? 4.63 (0.5) 4.77 (0.4) 3.67 (1.7) 4.5 (0.5) 0.11 A telehealth visit is better than a telephone call for FOLLOW-UP visits 4.0 (0.9) 4.31 (0.8) 3.73 (0.9) 4.6 (0.8) 0.09 How often do you use the Share Content feature? 1.38 (0.7) 2.38 (1.3) 1.87 (1.2) 3.9 (0.9) <0.01 How often are service-specific screening/intake forms completed by the time of the telehealth appointment? 2.88 (1.4) 3.0 (0.9) 2.71 (0.9) 2.70 (1.7) 0.95 What percentage of NEW patients do you think you would like to see via telehealth? 12.2 (16) 32.1 (27) 8.5 (5) 36.6 (29) 0.02 What percentage of FOLLOW-UP patients do you think you would like to see via telehealth? 24.3 (23) 46.7 (30) 43.8 (32) 47.5 (28) 0.4 On average, a NEW telehealth visit takes how many minutes? 71.3 (12) 34.4 (9) 28.5 (11) 50.5 (12) <0.001 On average a FOLLOW-UP telehealth visit takes how many minutes? 40.4 (11) 21.7 (6) 18.8 (8) 38.6 (11) <0.001 On average, a NEW IN-PERSON visit takes how many minutes? 77.5 (13) 41.7 (13) 30.2 (13) 54.8 (14) <0.001 On average, a FOLLOW-UP IN-PERSON visit takes how many minutes 48.3 (13) 23.9 (7) 16.9 (8) 38.6 (11) <0.001 How often do you use the following telehealth cart features?  Otoscope for EAR exam 1.0 (0) 1.62 (1) 1.87 (1) 1.0 (0) 0.11  Otoscope for NASAL exam 1.0 (0) 1.69 (1) 1.87 (1) 1.0 (0) 0.10  HD camera for ORAL exam 1.0 (0) 2.38 (1.5) 2.40 (2) 1.0 (0) 0.01  Stethescope 1.0 (0) 1.77 (0.8) 1.6 (1) 1.0 (0) 0.049  Bladder scanner 1.0 (0) 1.0 (0) 1.2 (0.5) 1.0 (0) 0.51 *Results are presented as the mean (standard deviation) based on a 5-point Likert scale. Open in new tab Nine-hundred and fifty-nine (25.4% response rate) anonymous patient surveys were completed. Reported patient satisfaction with their telehealth visit was 97.9% (939/959) while 98.0% (940/959) would also use telehealth again. Nine-hundred fourteen patients answered the final question regarding whether they would need to see the provider in person; 396 (43.3%) responded “no,” 198 (21.7%) answered “maybe,” and 320 (35.0%) reported “yes.” The patient survey demonstrated excellent consistency with a Cronbach’s alpha of 0.91. Further, when comparing patient satisfaction with the need to be seen in-person there was no difference between the reported and expected count regarding the need to be seen in-person and patient satisfaction. The RHCE telehealth team received 28 MA responses from 19 distinct clinics. MAs reported significantly longer time required to book a telehealth appointment compared to an in-person clinic appointment (10.3 ± 6.6 vs 2.8 ± 1.4 minutes, P < 0.001) (Table IV). Seventeen (61%) MAs only reported having to book up to one telehealth appointment per week while 9 (32%) booked 2–5 telehealth appointments per week. Interestingly, the remaining two MAs who were assigned to the busiest telehealth service, sleep medicine, reported booking more than 10 telehealth appointments per week but had a mean time required for booking of 3.75 minutes compared to all other clinic MAs (11 ± 7 minutes). TABLE IV. Clinic Booking Staff Attitudes and Opinions # unique clinics surveyed 19 # MAs surveyed 28 On an average day, how many virtual visits do you book 2–5 I feel comfortable in my ability to schedule a telehealth appointmenta 4.4 (0.9) Scheduling a telehealth appointment is harder than a regular clinic appointmenta 3.5 (1.1) It is a problem to schedule telehealth visits while I am performing other expected work dutiesa 3.5 (1.1) I think our clinic needs another person to help with scheduling virtual health visitsa 2.5 (1.2) I think scheduling virtual health appointments should be done centrally instead of in my clinica 2.4 (1.2) Patients I schedule for virtual health are happy they can use virtual health to see the specialista 4.3 (0.7) What is the average # of minutes it takes to schedule a virtual health visit 10.3 (6.6) What is the average # of minutes it takes to schedule an IN-PERSON visit 2.8 (1.4)* # unique clinics surveyed 19 # MAs surveyed 28 On an average day, how many virtual visits do you book 2–5 I feel comfortable in my ability to schedule a telehealth appointmenta 4.4 (0.9) Scheduling a telehealth appointment is harder than a regular clinic appointmenta 3.5 (1.1) It is a problem to schedule telehealth visits while I am performing other expected work dutiesa 3.5 (1.1) I think our clinic needs another person to help with scheduling virtual health visitsa 2.5 (1.2) I think scheduling virtual health appointments should be done centrally instead of in my clinica 2.4 (1.2) Patients I schedule for virtual health are happy they can use virtual health to see the specialista 4.3 (0.7) What is the average # of minutes it takes to schedule a virtual health visit 10.3 (6.6) What is the average # of minutes it takes to schedule an IN-PERSON visit 2.8 (1.4)* aReponses are based on a 5-point Likert scale from 1 (strongly disagree) to 5 (strongly agree) *p < 0.001. Open in new tab TABLE IV. Clinic Booking Staff Attitudes and Opinions # unique clinics surveyed 19 # MAs surveyed 28 On an average day, how many virtual visits do you book 2–5 I feel comfortable in my ability to schedule a telehealth appointmenta 4.4 (0.9) Scheduling a telehealth appointment is harder than a regular clinic appointmenta 3.5 (1.1) It is a problem to schedule telehealth visits while I am performing other expected work dutiesa 3.5 (1.1) I think our clinic needs another person to help with scheduling virtual health visitsa 2.5 (1.2) I think scheduling virtual health appointments should be done centrally instead of in my clinica 2.4 (1.2) Patients I schedule for virtual health are happy they can use virtual health to see the specialista 4.3 (0.7) What is the average # of minutes it takes to schedule a virtual health visit 10.3 (6.6) What is the average # of minutes it takes to schedule an IN-PERSON visit 2.8 (1.4)* # unique clinics surveyed 19 # MAs surveyed 28 On an average day, how many virtual visits do you book 2–5 I feel comfortable in my ability to schedule a telehealth appointmenta 4.4 (0.9) Scheduling a telehealth appointment is harder than a regular clinic appointmenta 3.5 (1.1) It is a problem to schedule telehealth visits while I am performing other expected work dutiesa 3.5 (1.1) I think our clinic needs another person to help with scheduling virtual health visitsa 2.5 (1.2) I think scheduling virtual health appointments should be done centrally instead of in my clinica 2.4 (1.2) Patients I schedule for virtual health are happy they can use virtual health to see the specialista 4.3 (0.7) What is the average # of minutes it takes to schedule a virtual health visit 10.3 (6.6) What is the average # of minutes it takes to schedule an IN-PERSON visit 2.8 (1.4)* aReponses are based on a 5-point Likert scale from 1 (strongly disagree) to 5 (strongly agree) *p < 0.001. Open in new tab Provider wRVU generation and Integrated Resourcing and Incentive System (IRIS) funding were also determined. Based on the 2016 CMS reimbursement of $35.8279 per wRVU, the 3,885.9 wRVUs generated $139,224 in direct care workload. Of the 38 originating sites, only 3 (the Army Correctional Facility, Spangdahlem Air Base, and Wiesbaden Army Health clinic) reside within 100 miles of LRMC. Thus, the 371 VIPRR clinic visits and the 2,741/3,407 specialty visits conducted to locations outside of this radius would likely have resulted in network deferral resulting in 3,115 (82.5%) visits which could be considered “recaptured” or purchased care avoided. Based on provider and originating site modifier compliance of 80.6% and 92.8% for the GT and Q3014 modifiers, respectively, IRIS reimbursement generated $87,650 for the Q3014 originating site fee ($25/encounter) and $60,900 from the GT modifier ($20/encounter). Finally, intangible savings were estimated. Based on the number and location of telehealth encounters, Soldiers and beneficiaries saved an estimated 8,307.5 days in travel, 1,505,995 million miles not driven, and USD $813,237.20 in mileage reimbursement alone for the 3,407 EARTH multispecialty clinic appointments. Further, the 271 VIPRR clinic readiness evaluations resulted in a potential savings of USD $1.3 million as the estimated cost to return a remotely-located Soldier to LRMC is $3,500 per Soldier (Table I). Of note, network providers in USEUCOM, USCENTCOM, and USAFRICOM are currently not conducting synchronous telehealth encounters with LRMC beneficiaries. DISCUSSION Virtual health encompasses a number of modalities, but synchronous, also called direct-to-consumer or “real time” VH, provides the best patient satisfaction – not only a key aspect of interactive telemedicine but also the primary modality used by the majority of commercial telehealth platforms.6 With an estimated 6–10% of primary care visits resulting in specialty referral, VH leverages technology to reach distant patients.7 However, we are aware of only one previous publication from a United States military MTF that reports multiple telemedicine outcomes although this report does not address all elements of Section 718.5 When reviewing Section 718 of the FY17 NDAA, we observed that only some requirements can be directly pulled either the MDR or M2.3 Other data such as beneficiary population for each MTF location, patient and provider satisfaction, and indirect savings require data from other sources cannot be determined through these resources. A recent GAO report observed that “In an internal audit, the Army found that about 30% of telehealth encounters were underreported.”8 This “underreported” data would not be obtained through MDR or M2 as the only mechanism at present time to link a clinical encounter as a synchronous VH visit is the GT modifier. Thus, when a provider does not add this modifier, which was observed in 19.4% of the 3,778 encounters in this study, there is no way to accurately assess Section 718 outcomes. In RHCE, each synchronous encounter is available for later review and analysis from a secure, HIPAA-compliant appointing scheduling tool. Presently, any VH encounter that lacks the GT modifier is sent for coder review and, when appropriate documentation is present, the modifier is added thus allowing capture by M2. Similar to other studies, we observed significant patient satisfaction.6,7 In this study, 98% of patients either “strongly agreed” or “agreed” to use telehealth again as well as being satisfied with their visit. Coupled with most VH visits being new consultations, this high satisfaction is very encouraging and dispels the notion that telehealth should only be utilized after an in-person visit. Further, not only did the patient satisfaction survey tool demonstrated excellent consistency but patient satisfaction was not dependent on whether the patient was required to be seen in-person. We feel this is significant as patient satisfaction is a key driver for telehealth success and one of the top three telemedicine program objectives identified in a 2018 U.S. Telemedicine Industry Benchmark Survey.11 Unfortunately, at present time, scheduling a synchronous virtual health visit is more complicated than a usual clinic appointment as noted by survey results from MAs (Table IV). While the booking staff had access to a unique telehealth calendar developed as an access database, staff needed to “triangulate” the appointment since the desired appointment time was based on the patient’s preference, the provider availability, and the cart availability at the originating site. Since each originating site cart could only support one appointment at a time, 27 unique specialties would have to “vie” for cart time often resulting in appointment schedulers needing to repeat the process if one of the three aspects did not fit with the other two. We hypothesized that secondary to a learning curve for the access database calendar appointing system, MAs booking more appointments were more “fluent,” and evidenced by the clinic scheduling the most VH appointments (sleep medicine) having the shortest booking time. As observed with varied provider adoption and attitudes, we also hypothesized that booking staff had similar differences towards the more complicated VH scheduling tool. While not a primary objective, the importance of VH supporting military readiness cannot be ignored. Based on patient location and the 2016 Joint Travel Regulation reimbursement of $0.54 per mile, these 2,692 unique patients would have driven approximately 1.5 million miles spending 8,307 days to complete their travel which equates to driving 61.7 times around the Earth and 23.3 years of time lost, respectively. Active Duty travel also results in a per diem mileage cost. Even considering reimbursement would only occur for Active Duty patients (75.9%), this would have amounted to USD $646,523 for mileage alone, excluding the VIPPR clinic. Adding the estimated cost of $3,500 to return a remote Soldier to LRMC instead of utilizing the VIPRR clinic would increase that travel cost to USD $2.11 million (Table I). We recognize that a full business case analysis of these 3,778 telehealth encounters should include all costs (i.e., equipment, staff salaries, etc.), but all cost aspects were not available and was not a primary or secondary goal of this study. In total, 27 specialties connected with 3.7% (2,962/63,348) of the beneficiaries located in an Army, Navy, or Air Force location with a telehealth cart and patient presenter. This a small increase from 3.4% previous year; however, the number of unique VH patients seen by a LRMC provider increased 57% from 1,886 in CY15 to 2,962 in CY16. This difference was most likely due to the addition of a new originating site in CY16 with approximately 5,000 Airman and beneficiaries but became one of the top VH originating sites. Also, we observed wide telehealth patient utilization rate between originating sites of 0.2–13.5%. (Table V).5,12 Finally, total year-to-year VH activity as a measure of total LRMC outpatient visits increased from 2.4% (2,354/100,094) in CY15 to 3.5% (3,778/107,887) in CY16, and is significantly greater than previous reports.5,9 TABLE V. Section 718 (Telemedicine) FY17 National Defense Authorization Act Reportable Outcome . RHCE Reportable Outcome (CY2016) . Satisfaction of covered beneficiary 98% Provider satisfaction 91–93% Frequency of telehealth use  Unique patients 3.7% of beneficiaries (2,321/63,348)  % local clinic population 0.2–13.5%  % virtual health appointments per clinic 1.0–39.9% Productivity of healthcare providers  Number of appointments (total) 3,778   Newa 1,827   Establisheda 1,187   Non-skill type I or II 764   wRVUs 3,359.1 Reduction (if any) of services in the private sector 3,115 visits (82.5%) not deferred to the network Allow covered beneficiaries to schedule appointments Yes, through specialty and primary care clinics Improve access to care  Primary care Yes – in-home appointments  Urgent care Pilot study published12  Behavioral health ↑ 29% appointments in CY16  Specialty care Yes Provide diagnosis, interventions, and supervisions Yes, Direct-to-patient real-time assessment and evaluation with dedicated and trained patient presenter4 To monitor individual health outcomes of covered beneficiaries with chronic disease and conditions Yes. 26 distinct medical, surgical, and behavioral health specialties Improve communication between healthcare providers and patients Yes, “real-time” telehealth with email appointment notification reducing no-show rate by 50% Maximize use of secure messaging Yes, RelayHealth Reportable Outcome . RHCE Reportable Outcome (CY2016) . Satisfaction of covered beneficiary 98% Provider satisfaction 91–93% Frequency of telehealth use  Unique patients 3.7% of beneficiaries (2,321/63,348)  % local clinic population 0.2–13.5%  % virtual health appointments per clinic 1.0–39.9% Productivity of healthcare providers  Number of appointments (total) 3,778   Newa 1,827   Establisheda 1,187   Non-skill type I or II 764   wRVUs 3,359.1 Reduction (if any) of services in the private sector 3,115 visits (82.5%) not deferred to the network Allow covered beneficiaries to schedule appointments Yes, through specialty and primary care clinics Improve access to care  Primary care Yes – in-home appointments  Urgent care Pilot study published12  Behavioral health ↑ 29% appointments in CY16  Specialty care Yes Provide diagnosis, interventions, and supervisions Yes, Direct-to-patient real-time assessment and evaluation with dedicated and trained patient presenter4 To monitor individual health outcomes of covered beneficiaries with chronic disease and conditions Yes. 26 distinct medical, surgical, and behavioral health specialties Improve communication between healthcare providers and patients Yes, “real-time” telehealth with email appointment notification reducing no-show rate by 50% Maximize use of secure messaging Yes, RelayHealth aSkill type I or II provider. Open in new tab TABLE V. Section 718 (Telemedicine) FY17 National Defense Authorization Act Reportable Outcome . RHCE Reportable Outcome (CY2016) . Satisfaction of covered beneficiary 98% Provider satisfaction 91–93% Frequency of telehealth use  Unique patients 3.7% of beneficiaries (2,321/63,348)  % local clinic population 0.2–13.5%  % virtual health appointments per clinic 1.0–39.9% Productivity of healthcare providers  Number of appointments (total) 3,778   Newa 1,827   Establisheda 1,187   Non-skill type I or II 764   wRVUs 3,359.1 Reduction (if any) of services in the private sector 3,115 visits (82.5%) not deferred to the network Allow covered beneficiaries to schedule appointments Yes, through specialty and primary care clinics Improve access to care  Primary care Yes – in-home appointments  Urgent care Pilot study published12  Behavioral health ↑ 29% appointments in CY16  Specialty care Yes Provide diagnosis, interventions, and supervisions Yes, Direct-to-patient real-time assessment and evaluation with dedicated and trained patient presenter4 To monitor individual health outcomes of covered beneficiaries with chronic disease and conditions Yes. 26 distinct medical, surgical, and behavioral health specialties Improve communication between healthcare providers and patients Yes, “real-time” telehealth with email appointment notification reducing no-show rate by 50% Maximize use of secure messaging Yes, RelayHealth Reportable Outcome . RHCE Reportable Outcome (CY2016) . Satisfaction of covered beneficiary 98% Provider satisfaction 91–93% Frequency of telehealth use  Unique patients 3.7% of beneficiaries (2,321/63,348)  % local clinic population 0.2–13.5%  % virtual health appointments per clinic 1.0–39.9% Productivity of healthcare providers  Number of appointments (total) 3,778   Newa 1,827   Establisheda 1,187   Non-skill type I or II 764   wRVUs 3,359.1 Reduction (if any) of services in the private sector 3,115 visits (82.5%) not deferred to the network Allow covered beneficiaries to schedule appointments Yes, through specialty and primary care clinics Improve access to care  Primary care Yes – in-home appointments  Urgent care Pilot study published12  Behavioral health ↑ 29% appointments in CY16  Specialty care Yes Provide diagnosis, interventions, and supervisions Yes, Direct-to-patient real-time assessment and evaluation with dedicated and trained patient presenter4 To monitor individual health outcomes of covered beneficiaries with chronic disease and conditions Yes. 26 distinct medical, surgical, and behavioral health specialties Improve communication between healthcare providers and patients Yes, “real-time” telehealth with email appointment notification reducing no-show rate by 50% Maximize use of secure messaging Yes, RelayHealth aSkill type I or II provider. Open in new tab We also observed a lower no-show rate for VH visits compared to in-person visits – 2.7% compared to 4.9% – a similar observation described by others.8 We hypothesize that this lower no-show rate was due to the specialty clinic first contacting the patient by phone, then once the appointment was scheduled the LRMC telehealth team sent an email appointment reminder to the patient’s preferred email.8 Another potential factor was patients were motivated to be evaluated by a LRMC specialty provider as equivalent specialties through the local economy were often lacking or limited. We recognize that there are a number of limitations with this study. First, this was a retrospective review. Ideally, telehealth outcomes for a specific specialty should compare equivalent outcomes for in-person visits with telehealth visits. Also, there was no command-directed “quota” for telehealth use. Thus, individual specialty telehealth activity may be due to a number of factors which were not explored as part of this study. For instance, specialties with limited providers may have been unable to expand their clinical reach due to requirements to meet local access standards while other clinic providers with more telehealth experience may have conducted more synchronous visits. While the provider survey asked 42 questions, we found this number of questions coupled with a limited number of responses resulted in a multivariate analysis of variance analysis that could not be validated; thus, further exploratory analyses and provider surveys are needed. On the other hand, a one-way analysis of variance analysis between the four main disciplines demonstrated fifteen (35.7%) survey questions with a significant difference. Mainly, behavioral health and surgical specialties reported less “enthusiasm” compared to medicine and primary care specialties to see new patients or that VH was a valuable resource. (Table III) However, further study is required to validate these initial pilot observations and even when validated at one location, these outcomes may not be reproducible at other MTFs. Finally, while we observed telehealth growth from 2015 to 2016, conducting and supporting telehealth within a MTF faces significant challenges. While not assessed in this study, known barriers include changes in leadership priorities and vision, delays in personnel hiring and budget constraints, information technology barriers to include lengthy Defense Business Certification (DBC) and Risk Management Framework (RMF) cybersecurity validation, and provider and patient adoption among others. Due to the standard 3-year overseas tour in USEUCOM, approximately one-third of providers at both distant and originating sites have a permanent change of station (PCS) resulting in a yearly requirement to credential and educate new providers and clinic leaders. Further, the marked decrease in VH encounters during the 2016 Summer and Fall were directly related to the loss of three VH patient presenters who supported the most VH encounters (unpublished data) (Fig. 2). FIGURE 2. Open in new tabDownload slide Overall synchronous telehealth encounters in Regional Health Command Europe from January 2014 to December 2017 based on the location of provider. LRMC specialty clinic encounters (blue); Virtual Integrated Patient Readiness and Remote(VIPRR) Care Clinic (green); Bavaria Medical Activity Command encounters (red). FIGURE 2. Open in new tabDownload slide Overall synchronous telehealth encounters in Regional Health Command Europe from January 2014 to December 2017 based on the location of provider. LRMC specialty clinic encounters (blue); Virtual Integrated Patient Readiness and Remote(VIPRR) Care Clinic (green); Bavaria Medical Activity Command encounters (red). Success of multispecialty synchronous VH not only lies in a detailed costs-benefit analysis but also on developing a centralized hub which develops, supervises, and coordinates training, credentialing, coding, and technical support while identifying opportunities and threats associated with telehealth.10 While we feel this report describes previously unreported outcomes related to synchronous telehealth in the Military Healthcare System, there are still significant knowledge gaps – first and foremost is a comprehensive return on investment (ROI) analysis for a local or regional telehealth platform. Second, the specialties observed herein who conducted the most telehealth appointments may not be representative of the entire MHS, rather could represent local telehealth “champions” or “early adopters.” Many will also continue to compare telehealth to the usual “brick-and-mortar” in-person visit. Thus, while observed patient and provider and provider satisfaction were high, those conducting telehealth should also report clinic-specific outcomes, quality of care, overall healthcare utilization, and cost savings to the patient and MTF. These primary framework domains, applicable framework subdomains, and potential measurable concepts have been outlined by the National Quality Forum’s “Creating a Framework to Support Measure Development for Telehealth.” 2017 report and should be incorporated into any telehealth planning phase or research.11 Finally, core objectives should be established for a telehealth program. In a recent industry survey of 411 healthcare executives, physicians, nurses, and healthcare professionals in the USA, the top six objectives identified including (1) improving patient outcomes, (2) providing remote patients with access to specialists, (3) increasing patient engagement and satisfaction, (4) improving patient convenience, (5) improving leverage of limited physician resources, and (6) reducing unnecessary ED visits.13 CONCLUSION Virtual Health remains a top MEDCOM endeavor and has the ability to leverage technology to provide services and access to specialists that otherwise are limited or require extensive travel to reach. However, now the NDAA requires the MHS to provide interval congressional reports regarding Section 718. Herein, we report the outcomes for multispecialty synchronous VH for RHCE and CY16 outcomes which directly address Section 718 elements (Table V). With the priority of “readiness” and NDAA Section 718 requirements, synchronous VH offers military members and their families located in distant clinics a direct, real-time engagement with specialty providers. We observed a 98% patient satisfaction, a 91–93% provider satisfaction, and significant realized savings for the patient. These outcomes and specific survey tools should be considered when initiating regional and enterprise-level multispecialty synchronous telehealth efforts while measuring identified quality outcomes. Supplementary Material Supplementary material is available at Military Medicine online. Previous Presentations Presented as a poster (MHSRS17_1648) at the 2017 Military Health System Research Symposium. Funding This supplement was sponsored by the Office of the Secretary of Defense for Health Affairs. Acknowledgments We thank Dr Tina Dong at the Uniformed Services University of Health Sciences for her statistical input and analysis. 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