Abstract Deaf individuals struggle with accessing mental health services because of language and cultural discordance. Our project’s purpose was to design and pilot an accessible, integrated mental health program for the Deaf population, scalable for other health centers interested in serving these individuals. Our team addressed several identified barriers to care. The addition of a language-concordant mental health clinician and telemental health appointments helped us better manage Deaf patients’ mental health needs. Individual and clinic level data were collected and analyzed. Results demonstrated a significant improvement in the patients’ depression and anxiety scores from their baseline to their last documented visit. Patient satisfaction overall was high. Telemental health appears to be a feasible tool to address some of the mental health gaps in the Deaf community. Further studies are needed to demonstrate how this program can be effective within a larger geographical area. Overview of Deaf Health Individuals with hearing loss are a heterogeneous group with variations in the type and severity of hearing loss, laterality, and frequency range, as well as in language and/or communication preferences (Zazove, Atcherson, Moreland, & McKee, 2015). These individuals have a higher prevalence of mental health disorders linked with a variety of psychosocial factors (Zazove et al., 2015), including low socioeconomic status (Blanchfield, Feldman, Dunbar, & Gardner, 2001), social isolation (Wallhagen, Strawbridge, & Shema, 2008), and difficulties locating accessible mental health programs (Fellinger, Holzinger, & Pollard, 2012). One particular group of high concern is the Deaf American Sign Language (ASL) user community, a population estimated to be about 500,000 individuals in the U.S. (Harrington, 2004). This group of individuals identifies themselves as a minority community, with their own unique language and culture (Barnett, 1999; Padden & Humphries, 2005; Preston, 1995). Deaf ASL users (thenceforth, Deaf) frequently struggle to understand spoken English and may lack proficiency in written English. As a result, they often struggle with significant health care marginalization and health care inequities (McKee, Moreland, Atcherson, & Zazove, 2015; McKee, Paasche-Orlow, et al., 2015; McKee, Winters, Sen, Zazove, & Fiscella, 2015; Moreland, Atcherson, Zazove, & McKee, 2015), including poor access to mental health care services (Fellinger et al., 2012). Deaf signers have higher rates of complex mental health needs, and this issue is compounded by poor mental health access (Fellinger et al., 2012; Pollard, 1996), leaving their issues largely unaddressed (Fellinger et al., 2012). The lack of accessible mental health care for Deaf signers is likely multifactorial. First, communication and language barriers are common in health care settings despite the passage of the Americans with Disabilities Act in 1990 (Zazove et al., 2015). One study discovered that only 17% of Deaf signers receive an interpreter for their health care visits (Alexander, Ladd, & Powell, 2012). It is unknown whether this percentage is any better in mental health settings. Second, Deaf signers are more likely to have Medicaid (Blanchfield et al., 2001; McKee, McKee, Winters, Sutter, & Pearson, 2014) which further reduces access. Third, many clinicians lack training on how to effectively care for Deaf signers, frequently creating cultural conflicts with their Deaf patients (Cabral, Muhr, & Savageau, 2013; Munro, Knox, & Lowe, 2008). Fourth, adherence is lower when there are language and cultural discordance (Graham, Jacobs, Kwan-Gett, & Cover, 2008; Lewis, 1994; MacKinney, Walters, Bird, & Nattinger, 1995; McKee & Paasche-Orlow, 2012; McKee, Barnett, Block, & Pearson, 2011; Paasche-Orlow, Schillinger, Greene, & Wagner, 2006; Regenstein et al., 2008; Sudore et al., 2009). Deaf signers struggle with higher rates of mental disorders (Fellinger et al., 2012; Kvam, Loeb, & Tambs, 2007), making their mental health care gap more acute. Furthermore, with language and communication barriers between clinicians and patients, under- and misdiagnoses are more likely (Cabral et al., 2013; Crump & Hamerdinger, 2017; Fellinger et al., 2012; Landsberger, Sajid, Schmelkin, Diaz, & Weiler, 2013). The National Association for the Deaf identified accessible mental health care as one of their top three priorities (National Association of the Deaf, 2003). This is not surprising given that only 2% of Deaf adults who need mental health services ever receive appropriate mental health care (Pollard, 1996). Due to the scarcity of language and cultural concordant mental health providers for Deaf patients, improving mental health care will require expanding either direct or remote access to these providers. In fact, Crowe (2017) states that there is widespread support for telemental health services as an alternative option to address existing mental health gaps remotely. Also, it has been established that ensuring accessible health care communication for Deaf individuals has been shown to be beneficial for preventive care, and for general health care use (McKee et al., 2011). Deaf patients not only prefer direct access to ASL-fluent mental health care providers, but fare better when given this opportunity (Landsberger et al., 2013; Pollard et al., 2014). Purpose The project was designed to pilot an accessible, integrated mental health program for Deaf signers in the state of Michigan, scalable for other integrated health centers. A secondary purpose included the incorporation of telemental health services to assess its feasibility to address some of the mental health care gaps for Deaf patients. These were driven by a white paper from the National Association of Social Worker—Michigan Chapter affirming the mental health disparities that Deaf signers face in the state of Michigan (National Association of Social Workers, 2014). Currently, within Southeast Michigan alone, there are 221,480 individuals who are DHH (State of Michigan, 2009), but data is lacking on how many of these individuals identify themselves as Deaf signers. Our model program parallels efforts to integrate medical and behavioral health in a primary care setting, with physicians and mental health clinicians working together to meet the needs of patients in one location, and to partner in designing treatment planning with the patient. The addition of accessible telemental health services proposes an innovative assessment strategy that could potentially help address the absence of Deaf accessible mental health care in large areas across the state of Michigan. This part of the project aimed to assess the feasibility of conducting these services from a health center, and the level of patient acceptance for utilizing telemental health-based appointments. Methodology Participants and Setting All Deaf patients ages 18 years and older who used ASL for communication had family medicine and clinical social work services available to them between March 1, 2016 and February 28, 2017. A total of 50 Deaf patients were screened and offered the opportunity to participate in the integrated program. Forty people saw both a family physician and the social worker during the grant year, with the remainder either seeing only the social worker or the family physician. Services were largely funded by a State of Michigan Medicaid Match Grant as offered by the Department of Health and Human Services. The sample included Deaf patients at a single outpatient health center affiliated with a large academic health institution located in Southeast Michigan. The Deaf Mental Health Clinic consisted of two Deaf, ASL-fluent family medicine physicians, and one hearing ASL-fluent social worker. Additionally, medically trained and qualified ASL/English interpreters from our institution’s Interpreter Services Program were always available to supplement any communication needs for patients and families (family may not be fluent in ASL) at any point in their contact with the clinic. Because direct communication was usually available in the clinic, interpreters were rarely called upon or used. One medical assistant and one check-in staff member also received weekly ASL classes from our institution’s Interpreter Services Department to help improve check-in and check-out communication access for our Deaf signers. Deaf patients were screened for depression and/or anxiety, and the presence of any psychosocial needs. If any needs were identified, Deaf patients were provided the opportunity to work with a clinical social worker to address these concerns. The clinical social worker worked closely with the family physicians to manage their patients’ mental health needs. Interventions were tailored to each individual patient and were broad in the range and scope of social work practice. Case management services, advocacy, care management for maintenance of health conditions, and psychotherapy were available to patients. This is consistent with the social work theory, that an individual’s mental health may be influenced by organic processes, as well as by psychosocial factors in the environment (Kondrat, 2013). This holistic approach provided more thorough assessment and identification of patient needs, and allowed for tailored interventions. Patients without any identified active psychosocial needs were monitored for any changes with intermittent mental health screenings during their routine medical clinic visits. University of Michigan Institutional Review Board approved the project on October 20, 2015. Development of the Integrated Mental Health Program The co-location of medical and behavioral health services in one building allows for high levels of patient care collaboration as defined by Doherty, McDaniel, & Baird (1996); physicians regularly have close collaboration with clinical social workers and other behavioral health specialists. This collaboration parallels institution-wide efforts to improve service delivery and to integrate behavioral health and physical medicine in single clinics. Our integrated team regularly communicates regarding the care needs of patients, and works together to mitigate biopsychosocial barriers to care to improve overall wellness for the patient. As with all patients, insurance barriers are sometimes a challenge to care planning, and the team held regular collaborative team meetings to discuss specific patient needs. Telemental health services have also been a focus of this pilot. This service was provided by the social worker; typical in-person visits continued to be available to all patients at their request. Telemental health interventions can be a convenient treatment option for patients, especially for those with significant transportation barriers. The use of readily available technologies, such as secure videophones that can also be accessed on personal, portable digital devices has been shown to increase access to mental health services for ASL users. These devices make ASL-fluent mental health providers accessible to people who may not have a provider in their local area (Crowe, Jani, Jani, Jani, & Jani, 2016; Vernon & Leigh, 2007; Wilson & Wells, 2009), and are especially beneficial for addressing mild to moderate mental health concerns generally treated in an integrated behavioral health/family medicine clinic (Crowe, 2017). The majority of patients were first seen in-person at the clinic by the physicians. Available options to see the social worker were either in-person, or by utilizing telemental health. However, whether to offer the telemental health service option was made following an individual assessment conducted by our clinical social worker. It was deemed inappropriate for some of our patients and not offered. The most frequent reasons for this were lack of access to videophone equipment (n = 2), risk of self-harm (e.g., suicidality) (n = 1), and cognitive challenges (n = 3). Despite these exclusions, the majority of our Deaf patients were offered telemental health services as an option during the project’s timeline. Many patients cite travel cost or lack of transportation as a barrier to seeking mental health services. Some simply do not live within a reasonable distance for weekly or biweekly treatment visits. In this pilot program, the use of telemental health versus in-person visits was left to the discretion of the patient for whom the option was appropriate. In one case, a patient chose to drive 2 h, one-way, for psychotherapy visits based on personal preference to be seen in-person with an ASL-fluent clinician. Adaptation and Translation of Mental Health Tools The Patient Health Questionnaire-9 (PHQ-9) (Kroenke, Spitzer, & Williams, 2001), and the Generalized Anxiety Disorder-7 (GAD-7) (Spitzer, Kroenke, Williams, & Löwe, 2006) are widely used across our health system. We decided to use similar screening tools for consistency and to measure treatment results. There are numerous apps or websites available for the general population to self-screen for mental health disorders, yet no freely available ASL-accessible mental health tools were available for this project. Since, the PHQ-9 and GAD-7 were only available in an English written format, this presented accessibility issues for our Deaf patients. Consequently, we set up a Translation Work Group (TWG) to adapt and translate these two tools into an accessible video-based survey tool available on a tablet PC. The TWG comprised of 4 individuals; 2 native Deaf signers, 1 Deaf medical professional, and 1 medical interpreter that met together for a total of 22 h to complete the translation of the 16 questions in the PHQ and the GAD, as well as the introductions for both of these translated instruments. To adapt the PHQ-9/GAD-7 into ASL, we created a computer interface for administering the ASL versions of these tools to Deaf individuals using the following processes: translation (and back-translation) of the English text in the original tools into ASL (via the use of an ASL gloss to guide film sessions) through the use of a translation work group format used in the past (Graybill et al., 2010; McKee, Paasche-Orlow, et al., 2015); creation of a computer-based survey interface for administration of the questions (see Figure 1); in-depth individual interviews (n = 8) with bilingual individuals to evaluate the computer interface and the translated survey questions with the written version; modifications based on feedback received from the interviews; and assessment of the ASL-PHQ and ASL-GAD instrument when compared to the written version of the PHQ/GAD with 8 bilingual Deaf patients. Figure 1 View largeDownload slide American Sign Language—PHQ-9 question 1 screenshot. Figure 1 View largeDownload slide American Sign Language—PHQ-9 question 1 screenshot. After the initial translation work was completed, a video draft with our signing model was created for each question. This was reviewed by two back-translators and pilot-tested before the final filming session with our signing model. The use of an ASL gloss (Valli & Lucas, 1995) and a video draft guided our signing model during our professional filming session. Video revisions were needed for two questions in the PHQ—questions 5 (“poor appetite or overeating”) and 9 (“thoughts that you were better off dead or hurting yourself”). The computer interface required additional modifications based on the feedback interviews with Deaf individuals. These included auto-play of signing videos instead of having the individual select a “play” button, and enlargement of the “next” button that users press to go to the next question. Score agreement between the PHQ and the ASL-PHQ was nearly identical with the exception of one participant (Pearson correlation = .99; p < .05), and two participants in the case for the GAD and the ASL-GAD scores (Pearson correlation = .98; p < .05). Categorical scores based on the depression and/or anxiety severity were identical with either tool (kappa statistic = 100%). The final ASL-PHQ and ASL-GAD was available with English captioning (for those who prefer to read), and a signing video (for Deaf ASL users) on a touch screen computer (i.e., SurfacePro Tablet). These screening tools were also made available in both an Android and Microsoft app under a development license, and were eventually developed into a website for wider dissemination (University of Michigan, 2017). The ASL-PHQ and ASL-GAD can be accessed for free at the following websites: https://umich.qualtrics.com/jfe/form/SV_dd4A1yYnbSBBJpH and https://umich.qualtrics.com/jfe/form/SV_cIywLcXP1c1GUnz. Other Measures A psychosocial acuity scale (PAS) was administered to our Deaf patients at our clinic over 12 months. The PAS had been previously developed by the Social Work Department within this institution (Klett et al., 2014). Although, the tool was designed to be combined with additional data collection methods to statistically capture and measure the contribution of the daily work of social workers, the PAS can be secondarily used as a means to show the number of psychosocial problems present in a given patient or population. It is able to identify the gap in available resources for patients to meet basic psychosocial needs (Klett et al., 2014). Although the scale was not devised to be an effective method to assess effectiveness of social work intervention, it may be utilized to capture psychosocial data about given samples of patients to be able to make comparison inferences. The PAS allows the social worker to capture daily data regarding the needs of a patient in seven domains, transportation, local lodging, insurance and finances, housing, coping and mental health, and functional status and discharge follow-up. These domains are rated using four levels: low, medium, high, and critical acuity levels. Data are typically reported for a defined patient population showing high or critical acuity, for comparison purposes. The PAS has been in use internally in the institution for several years. Training is ongoing, and it has already been demonstrated to be a reliable and valid tool to measure acuity (Klett et al., 2014). Multi-rater reliability was high for the PAS. The Cronbach alpha scores for domains one through seven of the PAS were as follows: Transportation .945, Insurance .980, Housing .937, Coping .970, Cognitive .894, Social Support .875, and Function .767 (Klett et al., 2014). Patient evaluations were obtained by outside staff fluent in ASL, but who were not involved with the program and remained anonymous. The evaluations assessed patient views of the following aspects of patient care: provider-patient communication quality, access to care, patient respect including privacy and confidentiality, level of comfort with the providers, ability to get help, and videophone quality (e.g., video quality that impacts the ability to see the provider). Statistical Analysis Characteristics of patients in the program are described, and the distributions compared with available clinic population statistics using Fisher’s exact tests. Effectiveness of the intervention in reducing depression and anxiety was assessed through the use of linear mixed models using continuous PHQ and GAD scores as outcomes, and an indicator for baseline or final PHQ and GAD score measured during the study period as a predictor. Marginal means were assessed to evaluate the average baseline and follow-up/end PHQ and GAD levels among participants. Results The Deaf patients had a mean age of 46.4 years; were primarily white, lower educated (HS or less), held public insurance (i.e., Medicaid and/or Medicare), and had some form of SSI assistance associated with their low income when compared to the general clinic population (refer to Table 1). Overall, among 50 Deaf patients, there were 244 visits. Visit numbers ranged between 1 and 37 per patient, with a mean of 4.9 (SD = 6.7) visits. Of those visits 112 (46%) were in-person, 106 (43%) were telemental health, 5 (2%) were phone, and 21 (9%) had missing visit type data. Overall, patient satisfaction was high with 86% being satisfied or very satisfied with all aspects of the program (n = 18). Two participants who had lower satisfaction scores struggled with video quality issues during their telemental appointments. Overall, patients frequently praised the option of having an opportunity to receive telemental health care remotely, as well as having health care being provided by language and cultural concordant providers. This is documented by the different quotes from different patients below which are grouped by their topic. Table 1 Deaf patient demographics Overall N = 50 Clinic population (n = 7,139) Fisher’s exact p-value Age, mean (SD) 46.4 (14.2) 18–30 6 (12.0) 1404 (19.7) .346 31–40 14 (28.0) 1346 (18.9) 41–50 12 (24.0) 1425 (20.0) 51–60 9 (18.0) 1433 (20.0) 61+ 9 (18.0) 1531 (21.4) Gender, n(%) .318 Male 24 (48.0) 2931 (41.1) Female 26 (52.0) 4208 (58.9) Race, n(%) <.001 White 40 (80.0) 6638 (92.9) African American 5 (10.0) 108 (1.5) Other 5 (2.0) 269 (3.8) Missing/Unknown 0 (0.0) 124 (1.7) Insurancea, n(%) Private 19 (38.0) 5785 (81.0) <.001 Medicare 19 (38.0) 1123 (15.7) <.001 Medicaid 14 (28.0) 411 (5.8) <.001 Other 1 (2.0) 126 (1.8) .591 None/Self Pay 0 (.0) 22 (.3) 1.00 Relationship Status, n(%) Single 15 (30.0) Married 22 (44.0) Divorced/Separated/Widow 13 (26.0) Diagnosed Depression/Anxiety/etc. n(%) 23 (46.0) Income, n(%) N = 37 <25K 16 (43.2) 25–50 K 11 (29.7) >50 K 10 (27.0) SSI/SSDI, n(%) n = 38 SSI 7 (18.4) SSDI 15 (39.5) Both 1 (2.6) None 15 (39.5) Education, n(%) N = 36 <HS 4 (11.1) HS 15 (41.7) Some College 11 (30.6) BA+ 6 (16.7) Overall N = 50 Clinic population (n = 7,139) Fisher’s exact p-value Age, mean (SD) 46.4 (14.2) 18–30 6 (12.0) 1404 (19.7) .346 31–40 14 (28.0) 1346 (18.9) 41–50 12 (24.0) 1425 (20.0) 51–60 9 (18.0) 1433 (20.0) 61+ 9 (18.0) 1531 (21.4) Gender, n(%) .318 Male 24 (48.0) 2931 (41.1) Female 26 (52.0) 4208 (58.9) Race, n(%) <.001 White 40 (80.0) 6638 (92.9) African American 5 (10.0) 108 (1.5) Other 5 (2.0) 269 (3.8) Missing/Unknown 0 (0.0) 124 (1.7) Insurancea, n(%) Private 19 (38.0) 5785 (81.0) <.001 Medicare 19 (38.0) 1123 (15.7) <.001 Medicaid 14 (28.0) 411 (5.8) <.001 Other 1 (2.0) 126 (1.8) .591 None/Self Pay 0 (.0) 22 (.3) 1.00 Relationship Status, n(%) Single 15 (30.0) Married 22 (44.0) Divorced/Separated/Widow 13 (26.0) Diagnosed Depression/Anxiety/etc. n(%) 23 (46.0) Income, n(%) N = 37 <25K 16 (43.2) 25–50 K 11 (29.7) >50 K 10 (27.0) SSI/SSDI, n(%) n = 38 SSI 7 (18.4) SSDI 15 (39.5) Both 1 (2.6) None 15 (39.5) Education, n(%) N = 36 <HS 4 (11.1) HS 15 (41.7) Some College 11 (30.6) BA+ 6 (16.7) aInsurance groups not mutually exclusive. View Large Table 1 Deaf patient demographics Overall N = 50 Clinic population (n = 7,139) Fisher’s exact p-value Age, mean (SD) 46.4 (14.2) 18–30 6 (12.0) 1404 (19.7) .346 31–40 14 (28.0) 1346 (18.9) 41–50 12 (24.0) 1425 (20.0) 51–60 9 (18.0) 1433 (20.0) 61+ 9 (18.0) 1531 (21.4) Gender, n(%) .318 Male 24 (48.0) 2931 (41.1) Female 26 (52.0) 4208 (58.9) Race, n(%) <.001 White 40 (80.0) 6638 (92.9) African American 5 (10.0) 108 (1.5) Other 5 (2.0) 269 (3.8) Missing/Unknown 0 (0.0) 124 (1.7) Insurancea, n(%) Private 19 (38.0) 5785 (81.0) <.001 Medicare 19 (38.0) 1123 (15.7) <.001 Medicaid 14 (28.0) 411 (5.8) <.001 Other 1 (2.0) 126 (1.8) .591 None/Self Pay 0 (.0) 22 (.3) 1.00 Relationship Status, n(%) Single 15 (30.0) Married 22 (44.0) Divorced/Separated/Widow 13 (26.0) Diagnosed Depression/Anxiety/etc. n(%) 23 (46.0) Income, n(%) N = 37 <25K 16 (43.2) 25–50 K 11 (29.7) >50 K 10 (27.0) SSI/SSDI, n(%) n = 38 SSI 7 (18.4) SSDI 15 (39.5) Both 1 (2.6) None 15 (39.5) Education, n(%) N = 36 <HS 4 (11.1) HS 15 (41.7) Some College 11 (30.6) BA+ 6 (16.7) Overall N = 50 Clinic population (n = 7,139) Fisher’s exact p-value Age, mean (SD) 46.4 (14.2) 18–30 6 (12.0) 1404 (19.7) .346 31–40 14 (28.0) 1346 (18.9) 41–50 12 (24.0) 1425 (20.0) 51–60 9 (18.0) 1433 (20.0) 61+ 9 (18.0) 1531 (21.4) Gender, n(%) .318 Male 24 (48.0) 2931 (41.1) Female 26 (52.0) 4208 (58.9) Race, n(%) <.001 White 40 (80.0) 6638 (92.9) African American 5 (10.0) 108 (1.5) Other 5 (2.0) 269 (3.8) Missing/Unknown 0 (0.0) 124 (1.7) Insurancea, n(%) Private 19 (38.0) 5785 (81.0) <.001 Medicare 19 (38.0) 1123 (15.7) <.001 Medicaid 14 (28.0) 411 (5.8) <.001 Other 1 (2.0) 126 (1.8) .591 None/Self Pay 0 (.0) 22 (.3) 1.00 Relationship Status, n(%) Single 15 (30.0) Married 22 (44.0) Divorced/Separated/Widow 13 (26.0) Diagnosed Depression/Anxiety/etc. n(%) 23 (46.0) Income, n(%) N = 37 <25K 16 (43.2) 25–50 K 11 (29.7) >50 K 10 (27.0) SSI/SSDI, n(%) n = 38 SSI 7 (18.4) SSDI 15 (39.5) Both 1 (2.6) None 15 (39.5) Education, n(%) N = 36 <HS 4 (11.1) HS 15 (41.7) Some College 11 (30.6) BA+ 6 (16.7) aInsurance groups not mutually exclusive. View Large Language Concordance “In fact, I have met different counselors that I do not feel good with and she is the first counselor who knows ASL is exactly I need and it is worth driving an hour to meet her in-person.” “I am very happy with both Dr. [x] and [counselor],… It is difficult to find the providers like them [who know sign language]. Even though, I am terrible at reading and getting the information through sign language is what I need the most. They are exactly what I need…. It is very comforting.” “I am impressed with [x], they are very accommodating to me. Dr. [x] is very clear in communicating my health issues. I fell in love with it because it is all direct [communication] without the use of an interpreter. I have learned more about myself through him. I thank him.” “I am happy [providers] who knows ASL and deaf culture… I used to have a hard time expressing my feelings… I was able to get out my feelings… which makes communication much easier for me. I think it is very hard to find a counselor that I feel can help me through and understand how I can deal with the emotions I have internally. It is not easy.” Integration of Health Care Providers “I have both [x] and [x], I am amazed to have them in my life because I never thought I would find someone who can access my language. I am in awe with the communication between all of us… it has been helpful for me to understand my health and my emotions that I struggled with…. It has been a long haul because I am old.” “I am very satisfied with Dr. [x] and [x] because I felt like I live in a stressful daily life that can leave my health matters worse and it is disorienting to me. Since I have been attending to their services, I can come out [more] at ease… now I understand my health as well as my depression issues [better].” Videophone Access “I live an hour and half away just to meet [x], it is so hard because I really cannot afford to spend my money on gas, so instead, we communicated through videophone which is better than not having any access to the help I need.” “Videophone saves me more time from driving one hour to get the in-person even though I would like in-person visit.” “I know the [videophone] is better than having an interpreter at a visit. I rather express my feelings directly to [provider] through the videophone. I really do not have a lot of money to pay for gas and I am thankful for the videophone [visits] to help me get what I need to work through it.” We found that 34% of the subjects had high/critical PAS scores versus only 16.4% of the non-Deaf patients seen at the same clinic. We additionally found that per patient, Deaf patients had more scored acuity domains than non-Deaf patients, indicating a broader scope of psychosocial concerns. The program significantly decreased PHQ scores (p-value = .005) among 39 patients with available data, with average baseline PHQ values of 7.7 (SE = .97) reducing to the last visit’s estimated mean of 4.84 (SE = 1.1) (Table 2). There was also a significant decrease in the mean GAD scores (p-value = .003) from 6.3 (SE = .84) to 3.4 (SE = .99) (Table 2). Table 2 Marginal mean (SE) of ASL-PHQ and ASL-GAD scores at baseline and final measurement taken (n = 39) Baseline Last measure p-value PHQ 7.7 (.97) 4.8 (1.1) .005 GAD 6.3 (.84) 3.4 (.99) .003 Baseline Last measure p-value PHQ 7.7 (.97) 4.8 (1.1) .005 GAD 6.3 (.84) 3.4 (.99) .003 aMarginal means from a linear mixed model with score as outcome and indictor for time (baseline vs last) as predictor. View Large Table 2 Marginal mean (SE) of ASL-PHQ and ASL-GAD scores at baseline and final measurement taken (n = 39) Baseline Last measure p-value PHQ 7.7 (.97) 4.8 (1.1) .005 GAD 6.3 (.84) 3.4 (.99) .003 Baseline Last measure p-value PHQ 7.7 (.97) 4.8 (1.1) .005 GAD 6.3 (.84) 3.4 (.99) .003 aMarginal means from a linear mixed model with score as outcome and indictor for time (baseline vs last) as predictor. View Large Moreover, we found that 68% (n = 34) of our Deaf patients carry some behavioral health diagnosis (with or without current treatment), while 22% (n = 11) had no behavioral health diagnosis, and 10% (n = 5) had missing data. The breakdown of behavioral health diagnoses are as follows in order of most common in the sample, and total more than the number of patients in the sample due to some people carrying more than one diagnosis: depression 38% (n = 19), anxiety/panic disorders 20% (n = 10), PTSD 10% (n = 5), adjustment disorder 12% (n = 6), other 12% (n = 6), substance abuse disorders 8% (n = 4), and ADD/ADHD 6% (n = 3). Other behavioral health diagnoses/concerns were either not found in this sample of patients, or n = 1 and thus were reported collectively as “other” to protect the privacy of people in this small sample. A surprising finding, 50% of patients in this sample (n = 25) reported current chronic pain (e.g., fibromyalgia, chronic low back pain) requiring management. Discussion Deaf patients seen in our program struggled with significant mental health burdens of multiple types. Our program pilot was able to both provide typical family medicine services to 50 Deaf patients, and also assist with their psychosocial and mental health needs through a variety of novel approaches. The program integrated the expertise of three clinicians who were able to deliver language and cultural concordant care to Deaf patients. The integration helped to not only better coordinate care but to also facilitate needed treatments and/or interventions (e.g., medications, therapy, support assistance with tangible needs). Additionally, the program provided an opportunity to demonstrate the feasibility of a telemental health program for areas that lack accessible local mental health care for Deaf patients. The program overall received high ratings in overall satisfaction, largely in part due to accessible communication, and the option of receiving ongoing care through telemental health platforms. Language concordance and cultural competency are key components to ensuring good patient-provider relationships. Deaf individuals have known behavioral health gaps, likely associated with language and communication barriers, as well as social marginalization (Fellinger et al., 2012). Effective communication is a crucial element in mental health care, not only for history gathering and accurate diagnosis but also to ensure good treatment adherence and to obtain desired treatment goals and outcomes (McKee, Moreland, et al., 2015). Furthermore, concordance is critical since this helps overcome potential medical mistrust. The Deaf community has a long history of mistrust of health care institutions, and especially with the mental health community (Fellinger et al., 2012; Hauser, O’ Hearn, McKee, Steider, & Thew, 2010; McKee, Schlehofer, & Thew, 2013; Moreland et al., 2015). The presence of clinicians who either were Deaf and/or worked closely with the Deaf community likely helped to improve the comfort level with the health care our Deaf patients received. This helped facilitate good communication that contributed to accurate diagnoses, as well as identification of significant psychosocial concerns. Lastly, the physicians and social worker emphasized a cultural model over a medical model. The focus of care was patient-centered, with a focus on the whole individual rather than on the correction of, or focus on, their hearing deficits (i.e., the traditional medical model). While clinical population demographics were missing for educational attainment, income, and employment status, our Deaf patients were much more likely to have public insurance. This generated challenges to ongoing care. In one particular situation, a Deaf patient with Medicaid sought needed substance abuse treatment. He failed to enroll into local rehabilitation programs due to one program refusing to provide ASL interpreters for his treatment, and another program not accepting his Medicaid insurance. The Minnesota Chemical Dependency program has a Deaf accessible program, but the patient was unable to enroll in it due to state Medicaid limitations, and his own lack of funds to pay for the program out of pocket. The combination of communication barriers, along with insurance limitations and poverty, places Deaf patients at extreme risk for fragmented health care and inadequate remediation of their psychosocial needs. Common areas of concern encountered were homelessness or tenuous housing, challenges navigating adequate insurance coverage (e.g., selecting Medigap plans, or ensuring ongoing active Medicaid coverage), and finding adequate community resources that are accessible and appropriate for Deaf patients when needs fell outside the scope of service available in the clinic. Working with the various, and often complex, social support systems required multiple follow-up visits to facilitate services on behalf of our patients. The lack of navigation skills and/or experience prevented several of our patients from independently getting help from social services. The involvement of a social worker who not only provides mental health services, but also addresses underlying social issues and barriers to care, was critical to better managing our Deaf patients’ overall health. Chronic pain (e.g., fibromyalgia, chronic low back pain) requiring management was higher than expected and to our understanding, not reported in the literature previously. We suspect that this may be partially a reflection of both the ongoing stress that many of these Deaf individuals experienced in conjunction with their prior traumatic experiences. Deaf individuals’ report higher level of stress and trauma, possibly resulting in higher levels of somatoform and stress-related disorders (Anderson, Wolf Craig, Hall, & Ziedonis, 2016; Fellinger et al., 2012). Unfortunately, validated ASL-accessible trauma or stress assessments are lacking and very much need to be developed to better understand the mechanisms of these pathologies (Anderson et al., 2016). Due to the surprisingly high rate of chronic pain burden in our sample, our team spent a significant amount of time addressing pain issues through behavioral modifications (e.g., cognitive behavioral therapy), physical therapy (when appropriate), and non-narcotic medications, when feasible. One of the innovative aspects of the program was the ability for Deaf patients to see their behavioral health specialist either in-person or by videophone. Videophones are compliant with the Privacy Rule of the Health Insurance Portability and Accountability Act (HIPAA). The Federal Communications Commission released a public notice stating HIPAA covered entities such as health care professionals can engage Deaf patients through these platforms (Federal Communications Commission, 2004). Among the 50 Deaf patients, ownership of videophones was high (96%). Our program did offer a free HIPAA compliant BlueJeans videoconference software for Deaf patients who may not have a videophone yet wish to receive telemental health services. Yet, it appears that videophone was the preferred and more convenient platform over the BlueJeans videoconference-based platform. No Deaf patients utilized the BlueJeans software. The videophone provides an efficacious solution for marginalized Deaf populations, even in the most remote locations. It provides an opportunity to access behavioral health directly rather than indirectly through an interpreter or, worse, with no accommodations for communication. Yet, it is important to recognize that this approach is not ideal for everyone. We had some Deaf patients, living as far as 1–2 h away, who preferred to meet with our mental health provider in-person. It is possible that these patients equate in-person visits as being “better” or the “traditional” way of delivering health care. Program sustainability is a significant barrier for many novel programs that address specific at-risk populations. The direct cost of integrating a social worker into our program was $20,100 for .4 FTE. Despite her part time effort, her involvement was effective in lowering expected health care-related interpreter costs, anticipated approximately $17,696 among the 50 DHH patients served from 2/1/16 to 9/1/16. We anticipate greater efficiency as the enrollment of Deaf patients increase at our clinic, and with a possible expansion of the program to other health centers. The project’s sustainability depends on an appropriate reimbursement model for telehealth services for this population. Fortunately, there appears to be movement towards this. First, mental health can be initiated and delivered solely through a telemental health program, unlike other aspects of health care where telemedicine can only be done with established patients (i.e., those at least seen in-person for their first visit). Second, insurers are recognizing the importance of telemental health coverage to provide equitable medical and/or mental health care in low resource areas. Third, there appears to be both interest in and acceptance of the use of telehealth by patients (F.A. Wilson, Rampa, Trout, & Stimpson, 2017). Strengths and Limitations of the Study This is one of few studies that reports specific outcomes on an integrated mental health program tailored for Deaf patients that incorporates telemental health services. The incorporation of accessible mental health tools provides an advantage in patient engagement, in respect to the group’s cultural and language affiliation, and in improved data collection and quality. Another strength of this program was the ability for physicians to engage in warm hand-offs to the social worker during a medical appointment. This practice, at least anecdotally, increased the likelihood of patients’ willingness to follow through with recommended behavioral health services. Having a social work clinician available in the clinic allowed for a broad-range of services to be available to patients: insurance inquiries, to case management/care coordination, and traditional psychotherapy were options that were available as needed for all patients. Even in settings where there is not an ASL-fluent physician, we believe—based on our experience—that simply having a social worker fluent in ASL could result in significant mental health improvements for Deaf patients. As the clinic continues to expand efforts and collaborations, both internal and external, the team envisions increasing access to behavioral health services across large geographic areas. There are only a handful of ASL-fluent behavioral health providers in the State, almost all concentrated in southeast Michigan, near Detroit. There are no known ASL-fluent mental health providers in northern Lower Michigan or in the entire Upper Peninsula. Limitations of our pilot include the lack of external generalizability given the program’s implementation at a single clinic. We had ASL-fluent physicians and social workers which is uncommon. The scarcity of ASL-fluent providers will greatly limit the ability for this type of program to be implemented at many other centers. However, the number of medical and mental health providers who are fluent in ASL appears to be growing (Kohrman, 2017), thereby increasing the likelihood for other similarly implemented programs to become successful. Despite this, we believe programs like ours should be considered centers of excellence committed to addressing the existing health inequities for Deaf patients since they can care for Deaf patients from a wider geographical range than their typical hearing patients. Patients were not randomized and had the opportunity to decline participating in the program; thus, those involved in the pilot study may not necessarily represent the Deaf population in general. Deaf patients clearly varied in the frequency and intensity of the visits, both in-person and telemental sessions, and it is unclear what the respective use of both of these options may be in a larger sample. In addition, a relatively small sample limited our ability to analyze different predictors of success or failure within the program. Finally, the prevalence of mental health disorders (e.g., PTSD) in our Deaf sample was lower than other published studies (Anderson et al., 2016; Fellinger et al., 2012; Kvam et al., 2007), yet many of these smaller scale studies had similarly significant sampling biases. The authors are not aware of any publications reporting reliable statistics on the prevalence of specific mental health disorders in a large adult deaf population samples in the U.S. Challenges, Future Considerations The above program was designed for Deaf patients with depression and/or anxiety. The team continues to look for creative solutions to meet the need of providing a broader scope of behavioral health services, specifically for patients who present with chronic pain and substance abuse/dependence that includes opioids, and for patients with chronic, severe mental illness or developmental disability. Yet, we do feel that the program provides a model for other centers to emulate. There is a dearth of services and programs that currently exist within the country that are culturally competent and affirming for ASL using patients. It is hoped that developing partnerships and collaborations within and across systems will address this challenge. Perhaps the biggest challenge foreseen for the future is developing solutions for ongoing continuity of care. As this clinic was established with the use of grant funds, most patients have not had to grapple with potential insurance barriers to access our program. The team continues to work on developing partnerships with local community mental health agencies, external Deaf service agencies, and other affiliated health systems with the goal of ensuring that Deaf individuals in need of mental health services will be able to access our program in the future. Conclusions With the increase in telepsychiatry and telemental health services for the general population, programs such as this could prevent further inequities among the Deaf population, reduce barriers to care, and perhaps even significantly close the gap in available mental health care services in this population. The telemental health program described above provides a unique opportunity to study language and culture-matching between mental health care providers and patients. It is critically important to identify centers of excellence to sustainably carry out the aims of the project which should be situated at high-density Deaf locations across the country. Funding The work was supported by a Medicaid Match grant through the Michigan Department of Health and Human Services (#20161070-001/05U05M15ADM). Conflict of Interest No conflicts of interest were reported. 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The Journal of Deaf Studies and Deaf Education – Oxford University Press
Published: Mar 17, 2018
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