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BackgroundComorbid depression is a significant challenge for safety-net primary care systems. Team-based collaborative depression care is effective, but complex system factors in safety-net organizations impede adoption and result in persistent disparities in outcomes. Diabetes-Depression Care-management Adoption Trial (DCAT) evaluated whether depression care could be significantly improved by harnessing information and communication technologies to automate routine screening and monitoring of patient symptoms and treatment adherence and allow timely communication with providers.ObjectiveThe aim of this study was to compare 6-month outcomes of a technology-facilitated care model with a usual care model and a supported care model that involved team-based collaborative depression care for safety-net primary care adult patients with type 2 diabetes.MethodsDCAT is a translational study in collaboration with Los Angeles County Department of Health Services, the second largest safety-net care system in the United States. A comparative effectiveness study with quasi-experimental design was conducted in three groups of adult patients with type 2 diabetes to compare three delivery models: usual care, supported care, and technology-facilitated care. Six-month outcomes included depression and diabetes care measures and patient-reported outcomes. Comparative treatment effects were estimated by linear or logistic regression models that used generalized propensity scores to adjust for sampling bias inherent in the nonrandomized design.ResultsDCAT enrolled 1406 patients (484 in usual care, 480 in supported care, and 442 in technology-facilitated care), most of whom were Hispanic or Latino and female. Compared with usual care, both the supported care and technology-facilitated care groups were associated with significant reduction in depressive symptoms measured by scores on the 9-item Patient Health Questionnaire (least squares estimate, LSE: usual care=6.35, supported care=5.05, technology-facilitated care=5.16; P value: supported care vs usual care=.02, technology-facilitated care vs usual care=.02); decreased prevalence of major depression (odds ratio, OR: supported care vs usual care=0.45, technology-facilitated care vs usual care=0.33; P value: supported care vs usual care=.02, technology-facilitated care vs usual care=.007); and reduced functional disability as measured by Sheehan Disability Scale scores (LSE: usual care=3.21, supported care=2.61, technology-facilitated care=2.59; P value: supported care vs usual care=.04, technology-facilitated care vs usual care=.03). Technology-facilitated care was significantly associated with depression remission (technology-facilitated care vs usual care: OR=2.98, P=.04); increased satisfaction with care for emotional problems among depressed patients (LSE: usual care=3.20, technology-facilitated care=3.70; P=.05); reduced total cholesterol level (LSE: usual care=176.40, technology-facilitated care=160.46; P=.01); improved satisfaction with diabetes care (LSE: usual care=4.01, techn...

Background Nonadherence to HIV medications is a serious unsolved problem and is a major cause of morbidity and mortality in the HIV-positive population. Although treatment efficacy is high if compliance is greater than 90%, about 40% of people with HIV do not meet this threshold. Objective This study aimed to test a novel approach to improve medication adherence by using a low-cost virtual reality (VR) experience to educate people with HIV about their illness. We hypothesized that people with HIV would be more likely to be compliant with the treatment following the 7-minute experience and, therefore, should have decreasing viral load (VL), increasing cluster of differentiation 4 + (CD4 + ) cell counts, and improved self-reported adherence. Methods We showed the VR experience to 107 participants with HIV at a county hospital in Los Angeles, California. Participants were asked to self-report how often they take their medications on a Likert-scale. The self-reported question (SRQ) was given before and at least 2 weeks after the VR experience. We also compared VL and CD4 + cell counts before and on average 101 days after the experience. VL and CD4 + were obtained per the clinic’s standard care protocol. Two-tailed paired t tests were performed on the initial and follow-up SRQ scores, VL, and CD4 + . We restricted the CD4 + analysis to participants who had a pre-CD4 + below normal (defined as 500 cells/mm 3 ). To reduce the possibility that VL were trending down and CD4 + were trending up regardless of the VR experience, 2 serial VL and CD4 + obtained before the experience were also compared and analyzed. Immediately following the VR experience, participants were given a 4-question Likert-type postexperience questionnaire (PEQ) that assessed their opinions about the experience. Results SRQ scores improved from pre to post experience with high significance ( P <.001). VL decreased from pre to post experience by 0.38 log 10 copies/mL (95% CI 0.06-0.70; P =.02). In contrast, the 2 serial VL obtained before the experience showed no statistically significant changes. There was also a statistically significant increase in CD4 + (95% CI –3.4 to –54.3 cells/mm 3 ; P =.03). Analysis of the PEQ revealed that VR was comfortable for almost all of the participants and that most participants believed the experience to be educational and that it would improve their medication adherence. Conclusions The findings suggest that the low-cost VR experience c...

BACKGROUND Nonadherence to HIV medications is a serious unsolved problem and is a major cause of morbidity and mortality in the HIV-positive population. Although treatment efficacy is high if compliance is greater than 90%, about 40% of people with HIV do not meet this threshold. OBJECTIVE This study aimed to test a novel approach to improve medication adherence by using a low-cost virtual reality (VR) experience to educate people with HIV about their illness. We hypothesized that people with HIV would be more likely to be compliant with the treatment following the 7-minute experience and, therefore, should have decreasing viral load (VL), increasing cluster of differentiation 4+ (CD4+) cell counts, and improved self-reported adherence. METHODS We showed the VR experience to 107 participants with HIV at a county hospital in Los Angeles, California. Participants were asked to self-report how often they take their medications on a Likert-scale. The self-reported question (SRQ) was given before and at least 2 weeks after the VR experience. We also compared VL and CD4+ cell counts before and on average 101 days after the experience. VL and CD4+ were obtained per the clinic’s standard care protocol. Two-tailed paired t tests were performed on the initial and follow-up SRQ scores, VL, and CD4+. We restricted the CD4+ analysis to participants who had a pre-CD4+ below normal (defined as 500 cells/mm3). To reduce the possibility that VL were trending down and CD4+ were trending up regardless of the VR experience, 2 serial VL and CD4+ obtained before the experience were also compared and analyzed. Immediately following the VR experience, participants were given a 4-question Likert-type postexperience questionnaire (PEQ) that assessed their opinions about the experience. RESULTS SRQ scores improved from pre to post experience with high significance (P<.001). VL decreased from pre to post experience by 0.38 log10 copies/mL (95% CI 0.06-0.70; P=.02). In contrast, the 2 serial VL obtained before the experience showed no statistically significant changes. There was also a statistically significant increase in CD4+ (95% CI –3.4 to –54.3 cells/mm3; P=.03). Analysis of the PEQ revealed that VR was comfortable for almost all of the participants and that most participants believed the experience to be educational and that it would improve their medication adherence. CONCLUSIONS The findings suggest that the low-cost VR experience caused an increased rate of antiretroviral therapy adherence that resulted in a decrease of VL and an increase of CD4+. Further studies are required to explore the duration of this effect and whether these results are generalizable to other treatment settings and populations.

BACKGROUND Comorbid depression is a significant challenge for safety-net primary care systems. Team-based collaborative depression care is effective, but complex system factors in safety-net organizations impede adoption and result in persistent disparities in outcomes. Diabetes-Depression Care-management Adoption Trial (DCAT) evaluated whether depression care could be significantly improved by harnessing information and communication technologies to automate routine screening and monitoring of patient symptoms and treatment adherence and allow timely communication with providers. OBJECTIVE The aim of this study was to compare 6-month outcomes of a technology-facilitated care model with a usual care model and a supported care model that involved team-based collaborative depression care for safety-net primary care adult patients with type 2 diabetes. METHODS DCAT is a translational study in collaboration with Los Angeles County Department of Health Services, the second largest safety-net care system in the United States. A comparative effectiveness study with quasi-experimental design was conducted in three groups of adult patients with type 2 diabetes to compare three delivery models: usual care, supported care, and technology-facilitated care. Six-month outcomes included depression and diabetes care measures and patient-reported outcomes. Comparative treatment effects were estimated by linear or logistic regression models that used generalized propensity scores to adjust for sampling bias inherent in the nonrandomized design. RESULTS DCAT enrolled 1406 patients (484 in usual care, 480 in supported care, and 442 in technology-facilitated care), most of whom were Hispanic or Latino and female. Compared with usual care, both the supported care and technology-facilitated care groups were associated with significant reduction in depressive symptoms measured by scores on the 9-item Patient Health Questionnaire (least squares estimate, LSE: usual care=6.35, supported care=5.05, technology-facilitated care=5.16; P value: supported care vs usual care=.02, technology-facilitated care vs usual care=.02); decreased prevalence of major depression (odds ratio, OR: supported care vs usual care=0.45, technology-facilitated care vs usual care=0.33; P value: supported care vs usual care=.02, technology-facilitated care vs usual care=.007); and reduced functional disability as measured by Sheehan Disability Scale scores (LSE: usual care=3.21, supported care=2.61, technology-facilitated care=2.59; P value: supported care vs usual care=.04, technology-facilitated care vs usual care=.03). Technology-facilitated care was significantly associated with depression remission (technology-facilitated care vs usual care: OR=2.98, P=.04); increased satisfaction with care for emotional problems among depressed patients (LSE: usual care=3.20, technology-facilitated care=3.70; P=.05); reduced total cholesterol level (LSE: usual care=176.40, technology-facilitated care=160.46; P=.01); improved satisfaction with diabetes care (LSE: usual care=4.01, technology-facilitated care=4.20; P=.05); and increased odds of taking an glycated hemoglobin test (technology-facilitated care vs usual care: OR=3.40, P<.001). CONCLUSIONS Both the technology-facilitated care and supported care delivery models showed potential to improve 6-month depression and functional disability outcomes. The technology-facilitated care model has a greater likelihood to improve depression remission, patient satisfaction, and diabetes care quality.