Access the full text.
Sign up today, get DeepDyve free for 14 days.
Abstract Intensive outpatient care programs (IOCPs) have shown promise for high-risk patients who account for disproportionate acute care utilization and costs. These programs typically address medical, behavioral, and social needs through intensive case management, health care navigation, coordination, and access to a range of social and community services. However, the value of these programs is often limited by patient engagement challenges (i.e., difficulty engaging patients in self-care, decision-making, and follow-up with recommended services). The purpose of this study was to develop a framework for engaging high-risk patients with complex medical, behavioral, and social needs in IOCPs. We conducted a qualitative study with 20 leaders and clinicians (e.g., physicians, nurses, psychologists, case workers) from 12 IOCPs affiliated with diverse settings (academic hospitals, county healthcare systems, Veterans Affairs facilities, community health centers, and private health systems). After completing a brief survey, participants were asked to describe how their program conceptualizes patient engagement and to describe characteristics of highly engaged patients. We used conventional content analysis methods to analyze qualitative data. Three domains of engagement were identified and are summarized in the Engagement Through CARInG Framework: Communication and actions to improve health; Relationships built on trust in IOCP staff; and Insight and goal-setting ability. Qualitative findings illustrate the spectrum and interrelatedness of these domains. The Engagement Through CARInG Framework can guide interventions that aim to enhance self-care and improve care coordination for high-risk patients with complex medical, behavioral, and social needs. Implications Practice: The Engagement Through CARInG Framework can guide intensive care coordination programs that aim to engage high-risk patients with complex medical, behavioral, and social needs. Policy: Policy to support engagement of complex, high-risk patients should: (i) address structural and regulatory barriers to team-based care, and (ii) focus on payment structures and performance measures that reward patient-centered care that is aligned with individuals’ goals. Research: Future research should evaluate the effectiveness of specific patient engagement strategies within the domains of the CARInG Framework. INTRODUCTION Health care spending in the USA is concentrated among a small minority of patients—50% of expenditures are attributable to just 5% of patients [1–4]. The convergence of multiple chronic conditions, co-morbid mental illness, and social stressors in many of these high-risk patients contributes to fragmented care, frequent emergency department visits, and hospitalizations [3, 5–7]. In recent years, intensive outpatient care programs (IOCPs) have been widely implemented to improve chronic care coordination and prevent health deteriorations and costly service use [8–11]. Although designs vary, IOCPs typically offer intensive case management and care coordination, enhanced access to a team of clinicians (e.g., through extended hours and home visits), and a wide range of social and community services [11–14]. Evaluations of IOCPs and other case management approaches have demonstrated increased patient satisfaction, but there is less consistent evidence for improved clinical outcomes and reduced costs [11, 15–17]. During a 2013 IOCP summit, innovators and experts determined that inconsistent patient engagement in these programs is a major barrier to achieving the Triple Aim of enhanced patient experience, improved health, and reduced costs . Patient engagement has been conceptualized in myriad ways in the medical literature, but generally refers to the degree to which patients participate in health-related activities, partner with healthcare providers in clinical decision-making, and interact with the healthcare system [18–23]. This definition of engagement, however, may not be relevant for patients with high-risk profiles who often require unconventional approaches and interventions. To address this gap and to advance understanding of patient engagement in intensive care coordination programs, we conducted a qualitative study with representatives from IOCPs serving patients with complex medical, social, and behavioral needs. Our objective was to synthesize the expertise of clinicians and program leaders, and to develop an engagement framework to assist programs in improving their care for high-risk patients. MATERIALS AND METHODS Study recruitment We used maximum variation purposive sampling  to identify IOCPs in Northern California that were diverse in regard to setting, affiliated healthcare system (e.g., academic, community, Veterans Affairs), payer, and target patient population (e.g., employed individuals, underserved patients, veterans). Eligible IOCPs had a mission to offer care coordination and enhanced services for high-risk patients. We first approached attendees of a 2014 regional meeting on high-risk patients, and supplemented this list by snowball sampling . We contacted clinical staff or program leaders from 18 IOCPs via e-mail, with a 67% response rate. When possible, we asked the initial contact to recommend another program representative with a different role to participate in a second interview. Interview procedure Guided by a qualitative expert on the research team (A.N.), we developed a semi-structured interview guide based on a review of the patient engagement literature. The framework presented in this paper derives from responses to two core interview questions: (i) “What does patient engagement mean to you or your program?” and (ii) “Imagine what you think of as a highly engaged patient. What might they do, or what characteristics might they have, that would make you think of them as highly engaged?” A team member with a medical background and qualitative research training (C.W.O.) conducted interviews with all program representatives. Interviews took place in person, except in two cases when they were conducted by telephone. Interviews lasted 25–55 minutes, and were digitally recorded and transcribed verbatim. Interviewees received $50 gift cards. The Stanford University Institutional Review Board approved study procedures and participants provided written consent prior to participating in the interviews. Qualitative data analysis Qualitative data were analyzed with the goal of understanding the domains that comprise patient engagement. We analyzed interview data using a conventional content analysis approach adapted from Hsieh and Shannon . This approach uses inductive strategies to analyze qualitative data and is often used when the objective is to have data, rather than pre-existing theory, drive analyses. Transcripts were imported into a qualitative software program to support data management, coding, and coding comparisons (ATLAS.ti7, Scientific Software Development, Berlin, Germany). Two authors (C.W.O. and C.S.) reviewed the text from five randomly selected transcripts to develop a preliminary code book based on the similarities and differences in how participants described engagement. The interdisciplinary research team met to refine the preliminary code book and to discuss applicability, consistency, and validity of the codes. The revised codes included domains that comprised how respondents defined engagement, such as trust and patient insight. Using the revised code book, two authors (C.W.O. and C.S.) independently coded three additional transcripts and then reviewed the coded transcripts together for consistency and to discuss discrepancy in the coding . After achieving coding consistency, the remaining transcripts were coded and any remaining discrepancies were resolved by discussion with a third author (J.Y.B.). Once coding was complete, the research team reviewed the quotations for each code and then grouped the codes into major domains, identifying cross-cutting themes about the domains’ properties and their relationships. The major domains were used to develop a working framework for patient engagement. RESULTS Participant and program characteristics Participants included 20 IOCP staff members from 12 different programs; 15 (75%) were clinicians and 12 (60%) were program leaders and administrators. Clinicians (several of whom also held leadership or administrative roles) included physicians, nurses, clinical psychologists, social workers, recreational therapists, and case managers. The represented IOCPs were affiliated with diverse organizations, including county, community, Veterans Affairs, and private health systems, and a public payer. IOCP patient eligibility criteria varied, but most programs targeted patients with recent or frequent hospitalizations or emergency department use. The Engagement Through CARInG Framework Our synthesis of interviews with IOCP representatives generated the CARInG Framework for engaging high-risk patients that comprises three domains: (i) Communication and actions to improve health; (ii) Relationships built on trust in IOCP staff; and (iii) Insight and goal-setting ability. These domains are summarized in the Engagement Through CARInG Framework (Fig. 1). Fig. 1 View largeDownload slide Engagement Through CARInG Framework Fig. 1 View largeDownload slide Engagement Through CARInG Framework Domain 1: communication and actions to improve health IOCP staff view engaged patients as individuals who perform the discrete behaviors of communicating with staff and participating in self-management actions to improve their health. Because of the medical and social complexity of the patients served by IOCPs, regular and appropriate communication is seen as a prerequisite to fully benefit from the program and its care coordination efforts. One clinician said, “We [work] with really high risk folks, so some of these things might sound really basic but that’s actually a pretty big deal.” Another physician explained: “We can’t coordinate care unless we know they are going to specialists. So, a highly engaged patient, [will] keep us informed of what’s going on and check in with us.” One provider described how patients’ responses to referrals reflect levels of engagement: “I have a handful of those patients who I consider highly engaged because we tell them, ‘It’s time for you to follow up with the neurologist.’ […] By the time they get downstairs, I get an alert that their appointment has been made.” Included in the set of behaviors that indicate patient engagement are self-management actions that take place in between direct communication with IOCP staff, as a provider explained: “Embracing their role of having to bring information to the visit and also [taking] an active role in trying to make their health better between their visits.” One provider summarized these fundamental health behaviors: “A patient that is engaged [attends] appointments with regularity, […] they are in continuous contact with providers and/or they are actively involved in addressing their healthcare needs.” Domain 2: relationships built on trust of IOCP staff For many IOCP staff, a trusting relationship is a critical starting point for productive interactions, as one staff member explained: “[Patient engagement is] completely relationship-based, and it’s about developing a sense of mutual understanding, trust, and learning how we can successfully interact with each other.” This relationship can take time to develop, and one provider explained that many patients are initially dubious about programs: “Patients were skeptical and hesitant: ‘This is too good to be true. How are you going to do this or that?’ We just took it one day at a time and showed them, ‘We want to see you healthier and living a happy life.’” Relationships are seen as critical to developing practical care coordination and treatment plans. A provider explained this as follows: “I think relationship is key. Without having that, it’s more authoritarian, right? ‘Take this! Do this!’ And they will look at you like, ‘Yeah-yeah-yeah.’ They won’t do it.” Ultimately, as patients become more engaged, the goal for many programs is to transition from offering services to collaborating in a partnership, as another provider explained: “I kind of look at it as a two-way street, where we are involved in the patient’s care but then the patient is also involved […] in working with us as well.” Domain 3: insight and goal setting ability A final domain that IOCP staff use to define engagement is patients’ insight about their health, which leads to their ability to set goals, problem solve, and coordinate their own care. Collectively these skills represent a capacity to understand one’s health and what is needed to improve it. As a first step in this process, staff felt that patients need to understand their medical needs and self-management requirements. For example, one clinician noted: “A highly engaged patient is someone who can tell you what their medicines are, what they are for, what the dosage is, when their next appointment is, and why that appointment is important.” This insight can be especially critical in the setting of severe health issues and social circumstances, which require navigation of complex services, as another provider described: “The patient who is fully engaged understands the role that self-management plays in their chronic disease [and] how that paradigm applies to accessing social services; is very system savvy.” Once patients demonstrate this insight, programs help them develop the skills required to define their own health goals, as a provider explained: “It involves not telling the patient what they need to do but […] having the patient try to think out their own problem and their own resolution.” One program administrator summarized how goal-setting and actions in pursuit of goals illustrate a high level of engagement: “So whether it’s blood pressure or their sugar checks, [the patient] would talk about the changes they have made and be able to reflect on how that has made them feel better or not, and be able to ask informed questions about their treatments, and be able to advocate their interests and their goals as we develop the treatment plan.” Additional properties of engagement domains Two themes relating to the engagement domains also emerged during analyses. The first is the interdependence of the domains, and the second is that engagement in each domain exists on a spectrum. Relationships among engagement domains Engagement in one domain often influences engagement in another. For example, one provider noted that patients are more responsive to communication as trust is established, drawing a connection between the first and second domains: “The tone of the conversation changes and they are […] starting to agree to do things, including more follow up: ‘Can I call you tomorrow?’ And they say, ‘Yes, please do.’” A provider in another program also explained the interconnectedness of these domains in describing highly engaged patients: “They are willing to talk with us on the phone. They will let us do home visits. They start to see us as advocates for them, and they see us as part of their team.” Providers also described interrelatedness between the second and third domains—trusting relationships and goal setting ability: “And our methodology is basically to build everything around the patient’s goals and we spend a lot of time with people … the outcome is building a relationship that people can trust, and they feel listened to and cared about.” Participants observed a similar association between the first and third domains, self-management actions and goal-setting ability, in which the skills described by domain three allow patients to accomplish the discrete actions described in domain one. One provider described that as patients are encouraged to set goals and they witness the effects of meeting these goals, they develop insight that strengthens their commitment to further self-management actions: “When they [come] back thinking about a task, it [is] the first step. […] When they start telling me why they want to do it, is when I say, ‘Oh!’ I help them with their own ways to achieve their own goals.” These connections suggest that programs’ efforts to strengthen patient engagement in one domain may have additional value for other domains. The spectrum of engagement The CARInG Framework also illustrates how patient engagement exists on a spectrum. Table 1 outlines examples of low and high engagement in each of the three domains. Importantly, IOCPs do not perceive a patient’s level of engagement as static. Trusting relationships naturally require time to develop, as a nurse coordinator explained: “They might begin to explore it, like, ‘what [are you] offering us, and what’s in it for me,’ and then develop that relationship and that trust. So it’s very step-wise.” Other aspects of engagement, like communication with IOCP staff, also evolve, even for a patient who enters a program completely unengaged. One provider described the moment when she typically recognizes that a patient’s level of engagement has changed: “I think it’s when a patient connects with us enough to start talking to us or there’s some level of trust there. You know, that they are not screening our calls.” Table 1 Examples of the Spectrum of Engagement Across CARInG Framework Domains Domain Engagement Examples Communication and actions Low • Inconsistent attendance at clinic visits and other appointments • Limited response to outreach • Minimal participation in self-care activities High • Regular attendance at scheduled appointments • Proactive contact with providers when needed • Consistent attention to care plans, especially for chronic illness Relationships built on trust Low • Skepticism of program’s efficacy and purpose • Guarded relationship with staff and providers • Distrust of healthcare system High • Belief that participation in program could improve health • Active partnership with staff and providers • Candid discussions about barriers to improved health Insight and goal setting Low • Limited understanding of illnesses • Inability to interpret how self-management behaviors impact symptoms • Reluctance to develop a care plan High • Clearly defined health goals and priorities • Understanding of provider roles and purpose of treatments • Active questioning to improve comprehension about health Domain Engagement Examples Communication and actions Low • Inconsistent attendance at clinic visits and other appointments • Limited response to outreach • Minimal participation in self-care activities High • Regular attendance at scheduled appointments • Proactive contact with providers when needed • Consistent attention to care plans, especially for chronic illness Relationships built on trust Low • Skepticism of program’s efficacy and purpose • Guarded relationship with staff and providers • Distrust of healthcare system High • Belief that participation in program could improve health • Active partnership with staff and providers • Candid discussions about barriers to improved health Insight and goal setting Low • Limited understanding of illnesses • Inability to interpret how self-management behaviors impact symptoms • Reluctance to develop a care plan High • Clearly defined health goals and priorities • Understanding of provider roles and purpose of treatments • Active questioning to improve comprehension about health View Large Table 1 Examples of the Spectrum of Engagement Across CARInG Framework Domains Domain Engagement Examples Communication and actions Low • Inconsistent attendance at clinic visits and other appointments • Limited response to outreach • Minimal participation in self-care activities High • Regular attendance at scheduled appointments • Proactive contact with providers when needed • Consistent attention to care plans, especially for chronic illness Relationships built on trust Low • Skepticism of program’s efficacy and purpose • Guarded relationship with staff and providers • Distrust of healthcare system High • Belief that participation in program could improve health • Active partnership with staff and providers • Candid discussions about barriers to improved health Insight and goal setting Low • Limited understanding of illnesses • Inability to interpret how self-management behaviors impact symptoms • Reluctance to develop a care plan High • Clearly defined health goals and priorities • Understanding of provider roles and purpose of treatments • Active questioning to improve comprehension about health Domain Engagement Examples Communication and actions Low • Inconsistent attendance at clinic visits and other appointments • Limited response to outreach • Minimal participation in self-care activities High • Regular attendance at scheduled appointments • Proactive contact with providers when needed • Consistent attention to care plans, especially for chronic illness Relationships built on trust Low • Skepticism of program’s efficacy and purpose • Guarded relationship with staff and providers • Distrust of healthcare system High • Belief that participation in program could improve health • Active partnership with staff and providers • Candid discussions about barriers to improved health Insight and goal setting Low • Limited understanding of illnesses • Inability to interpret how self-management behaviors impact symptoms • Reluctance to develop a care plan High • Clearly defined health goals and priorities • Understanding of provider roles and purpose of treatments • Active questioning to improve comprehension about health View Large Patients’ engagement levels can also vary across domains. For example, one provider described how patients can demonstrate insight (domain 3) while still struggling with self-management (domain 1): “People are still engaged when they respond to the person they are working with and say, ‘I can’t do this right now.’ When they can name that this is not a good time for them, that really shows engagement and progress.” Importantly, many IOCPs consider patients to be engaged even if they are unable to adhere to a treatment plan (domain 1), as long as they maintain a relationship with a provider (domain 2), and/or illustrate awareness about their challenges (domain 3). A program administrator explained this as follows: “A patient can be engaged in our program even if they are not paying a lick of attention to any of their health conditions. That patient [might discuss] challenges with staying clean, off crack, while at the same time not taking any of her medications.” DISCUSSION A recent New England Journal of Medicine commentary described engagement of high-risk, high-cost patients as critical to the success of IOCPs . The Engagement Through CARInG Framework provides a practical conceptualization of engagement from the perspective of IOCP providers who have extensive experience in treating and coordinating care of high-risk patients. The framework illustrates how communication and actions to improve health, relationships built on trust, and insight and goal-setting ability are interconnected domains that exist on a spectrum and collectively reflect patients’ engagement in IOCPs. The Engagement Through CARInG Framework builds on an extensive body of literature describing the concept of patient activation, which was first defined by Judith Hibbard and comprises patient self-reported knowledge, skill, and confidence for self-management of health [28, 29]. One way of conceptualizing the relationship between activation and engagement is that the latter is a manifestation of the former. For example, patients who are activated are more likely to perform recommended health behaviors , including the self-management engagement activities described in the communication and actions domain of the CARInG Framework. We found that several IOCP teams formally or informally assess patient activation levels to determine the level of support and the type of intervention that individuals need; the CARInG Framework can provide guidance about how to operationalize the use of activation assessments (e.g., the Patient Activation Measure [28, 29]) to titrate specific engagement interventions, such as frequency of communication, intensity of support for self-management activities, and coaching around insight and goal-setting. The framework also builds on the literature describing the engagement of patients in the general population across different organizational levels of health care [19–23]. Carman et al.  developed a model that presents how patients can be engaged across the healthcare system, with patient roles progressing from consultation, to involvement, to partnership and shared leadership. The CARInG Framework complements this model by focusing on engagement of uniquely complex and high-risk patients during direct clinical care. Patients enrolled in intensive outpatient programs frequently face severe health issues, often compounded by social and behavioral circumstances. This clinical and social complexity can necessitate prioritization of the more basic elements in the framework (e.g., responding to phone calls, showing up at appointments, trusting), which often need to be established before issues like insight, problem-solving, and goal-setting can be addressed. By outlining the attitudes, skills, and behaviors that comprise engagement for high-risk patients, the Engagement Through CARInG Framework can guide the development of targeted interventions that support communication and self-management actions, build trust and relationships, and facilitate insight and goal-setting skill development. Helping patients overcome barriers to engagement in each of these domains will ensure that they derive the greatest benefit from the care coordination and resources offered by IOCPs. For example, a patient with transportation barriers may benefit from virtual care or travel support (domain 1, communication and self-management actions), while patients with distrust in the healthcare system may benefit from gestures that demonstrate respect and awareness of personal challenges (domain 2, relationships and trust). Patients with serious mental illness, meanwhile, may need intensive case management and counseling to support problem-solving (domain 3, insight and goal setting). It should be noted that these qualitative findings are derived from perspectives of program clinical staff and leadership located in one region of the country. The CARInG Framework will require future validation with patients, caregivers, and program representatives from other geographic regions. Future research should evaluate the effectiveness of specific patient engagement strategies aligned with the domains of the CARInG Framework. In conclusion, it is well recognized that there is a critical demand for effective interventions for patients with medical, social, and behavioral complexity . While evidence about optimal care coordination strategies continues to evolve , enhancing patient engagement strategies will maximize the value of efforts to meet the complex needs of these patients. The Engagement Through CARInG Framework provides a structure to guide the ways in which targeted programs can address engagement in their patient assessments, service delivery, and ongoing care. Compliance with ethical standards Conflict of interest: The authors report no conflicts of interest. Primary data: The authors have full control of all primary data and agree to allow the journal to review the data if requested. The findings reported herein have not been previously published and this manuscript is not being considered by any other journals at this time. The framework described in this manuscript was presented at the Society for General Internal Medicine annual meeting in 2016. Ethical approval: All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. This research did not involve any animals. Informed consent: Informed consent was obtained from all individual participants included in the study. Acknowledgements The authors would like to acknowledge the individuals who volunteered their time to participate in this study and provide their insight on patient engagement in IOCPs. C.W.O. was supported by a MedScholars grant from Stanford University School of Medicine. J.Y.B. was supported by the VA Office of Academic Affiliations and a Health Services Research and Development Career Development Award (CDA 15–257). D.M.Z. was supported by a VA HSR&D Career Development Award (CDA 12–173) and received support from the Stanford University Presence Center’s partnership with the Stanford Cyber Initiative. The funding bodies had no role in design, in the collection, analysis, or interpretation of data; in the writing of the manuscript; or in the decision to submit the manuscript for publication. References 1. Riley GF . Long-term trends in the concentration of medicare spending . Health Aff (Millwood) . 2007 ; 26 ( 3 ): 808 – 816 . Google Scholar CrossRef Search ADS PubMed 2. Cohen S , Uberoi N. Differentials in the Concentration in the Level of Health Expenditures Across Population Subgroups in the U.S., 2010. Statistical Brief no. 421 . Rockville, MD : Agency for Healthcare Research and Quality ; 2013 . 3. Zulman DM , Pal Chee C , Wagner TH , et al. Multimorbidity and healthcare utilisation among high-cost patients in the US veterans affairs health care system . BMJ Open . 2015 ; 5 ( 4 ): e007771 . Google Scholar CrossRef Search ADS PubMed 4. Government Accountability Office . Medicaid: A Small Share of Enrollees Consistently Accounted for a Large Share of Expenditures . Washington, DC : U.S. Government Accountability Office ; 2015 : 39 . 5. Boult C , Leff B , Boyd CM , et al. A matched-pair cluster-randomized trial of guided care for high-risk older patients . J Gen Intern Med . 2013 ; 28 ( 5 ): 612 – 621 . Google Scholar CrossRef Search ADS PubMed 6. Coughlin TA , Long SK . Health care spending and service use among high-cost Medicaid beneficiaries, 2002–2004 . Inquiry . 2009 ; 46 ( 4 ): 405 – 417 . Google Scholar CrossRef Search ADS PubMed 7. Boyd C , Leff B , Weiss C , Wolff J , Hamblin A , Martin L. Faces of Medicaid: Clarifying Multimorbidity Patterns to Improve Targeting and Delivery of Clinical Services for Medicaid Populations . Hamilton, NJ: Center for Health Care Strategies ; 2010 . 8. Blumenthal D , Chernof B , Fuller T , Pumpkin J , Selberg J . Caring for high-need, high-cost patients—an urgent priority . N Engl J Med . 2017 ; 375 ( 10 ): 909 – 911 . Google Scholar CrossRef Search ADS 9. Bodenheimer T . Strategies to reduce costs and improve care for high-utilizing medicaid patients: Reflections on pioneering programs . Hamilton, NJ: Center for Health Care Strategies ; 2013 . 10. Peterson K , Helfand M , Humphrey L , Christensen V , Carson S. Evidence Brief: Effectiveness of Intensive Primary Care Programs . Evidence-based synthesis program. Portland, OR : Portland VA Medical Center ; 2013 . 11. Hong C , Siegel A , Ferris T . Caring for high-need, high-cost patients: What makes for a successful care management program ? Issue Brief. New York, NY: Commonwealth Fund ; 2014 , 1 – 19 . 12. Powers BW , Chaguturu SK , Ferris TG . Optimizing high-risk care management . JAMA . 2015 ; 313 ( 8 ): 795 – 796 . Google Scholar CrossRef Search ADS PubMed 13. Bodenheimer T , Berry-Millett R . Follow the money—controlling expenditures by improving care for patients needing costly services . N Engl J Med . 2009 ; 361 ( 16 ): 1521 – 1523 . Google Scholar CrossRef Search ADS PubMed 14. Hasselman D. Super-Utilizer Summit: Common Themes from Innovative Complex Care Management Programs . Hamilton, NJ : Center for Health Care Strategies ; 2013 . 15. Berwick DM , Nolan TW , Whittington J . The triple aim: Care, health, and cost . Health Aff (Millwood) . 2008 ; 27 ( 3 ): 759 – 769 . Google Scholar CrossRef Search ADS PubMed 16. Stokes J , Panagioti M , Alam R , Checkland K , Cheraghi-Sohi S , Bower P . Effectiveness of case management for ‘At Risk’ patients in primary care: A systematic review and meta-analysis . PLoS One . 2015 ; 10 ( 7 ): e0132340 . Google Scholar CrossRef Search ADS PubMed 17. Brown RS , Peikes D , Peterson G , Schore J , Razafindrakoto CM . Six features of Medicare coordinated care demonstration programs that cut hospital admissions of high-risk patients . Health Aff (Millwood) . 2012 ; 31 ( 6 ): 1156 – 1166 . Google Scholar CrossRef Search ADS PubMed 18. Bright FA , Kayes NM , Worrall L , McPherson KM . A conceptual review of engagement in healthcare and rehabilitation . Disabil. Rehabil . 2015 ; 37 ( 8 ): 643 – 654 . Google Scholar CrossRef Search ADS PubMed 19. Gruman J , Rovner MH , French ME , et al. From patient education to patient engagement: Implications for the field of patient education . Patient Edu Counsel . 2010 ; 78 ( 3 ): 350 – 356 . Google Scholar CrossRef Search ADS 20. Mittler JN , Martsolf GR , Telenko SJ , Scanlon DP . Making sense of “consumer engagement” initiatives to improve health and health care: A conceptual framework to guide policy and practice . Milbank Q . 2013 ; 91 ( 1 ): 37 – 77 . Google Scholar CrossRef Search ADS PubMed 21. Maurer M , Dardess P , Carman K , Frazier K , Smeeding L. Guide to Patient and Family Engagement: Environmental Scan Report . Rockville, MD : Agency for Healthcare Research and Quality ; 2012 . 22. Conway J . Public and patient strategies to improve health system performance . In: Olsen L , Saunders RS , McGinnis JM . Patients Charting the Course: Citizen Engagement and the Learning Health System . Washington, DC : Institute of Medicine ; 2011 : 103 – 109 . 23. Carman KL , Dardess P , Maurer M , et al. Patient and family engagement: A framework for understanding the elements and developing interventions and policies . Health Aff (Millwood) . 2013 ; 32 ( 2 ): 223 – 231 . Google Scholar CrossRef Search ADS PubMed 24. Palinkas LA , Horwitz SM , Green CA , Wisdom JP , Duan N , Hoagwood K . Purposeful sampling for qualitative data collection and analysis in mixed method implementation research . Adm Policy Ment Health . 2015 ; 42 ( 5 ): 533 – 544 . Google Scholar CrossRef Search ADS PubMed 25. Gile KJ , Handcock MS . Respondent-driven sampling: An assessment of current methodology . Sociol Methodol . 2010 ; 40 ( 1 ): 285 – 327 . Google Scholar CrossRef Search ADS PubMed 26. Hsieh HF , Shannon SE . Three approaches to qualitative content analysis . Qual Health Res . 2005 ; 15 ( 9 ): 1277 – 1288 . Google Scholar CrossRef Search ADS PubMed 27. Saldaña J. The Coding Manual for Qualitative Researchers . Los Angeles, CA: Sage ; 2005 . 28. Hibbard JH , Stockard J , Mahoney ER , Tusler M . Development of the patient activation measure (PAM): Conceptualizing and measuring activation in patients and consumers . Health Serv Res . 2004 ; 39 ( 4 Pt 1 ): 1005 – 1026 . Google Scholar CrossRef Search ADS PubMed 29. Hibbard JH , Mahoney ER , Stockard J , Tusler M . Development and testing of a short form of the patient activation measure . Health Serv Res . 2005 ; 40 ( 6 Pt 1 ): 1918 – 1930 . Google Scholar CrossRef Search ADS PubMed 30. Hibbard JH , Mahoney ER , Stock R , Tusler M . Do increases in patient activation result in improved self-management behaviors ? Health Serv Res . 2007 ; 42 ( 4 ): 1443 – 1463 . Google Scholar CrossRef Search ADS PubMed 31. Emanuel EJ . Where are the health care cost savings ? JAMA . 2012 ; 307 ( 1 ): 39 – 40 . Google Scholar CrossRef Search ADS PubMed 32. Bodenheimer T , Fernandez A . High and rising health care costs. Part 4: Can costs be controlled while preserving quality ? Ann Intern Med . 2005 ; 143 ( 1 ): 26 – 31 . Google Scholar CrossRef Search ADS PubMed Published by Oxford University Press on behalf of the Society of Behavioral Medicine 2018. This work is written by (a) US Government employee(s) and is in the public domain in the US.
Translational Behavioral Medicine – Oxford University Press
Published: May 23, 2018
Access the full text.
Sign up today, get DeepDyve free for 14 days.