Digital Medicine System in Veterans With Severe Mental Illness: Feasibility and Acceptability Study.
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2022-12
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Abstract
Background
Suboptimal medication adherence is a significant problem for patients with serious mental illness. Measuring medication adherence through subjective and objective measures can be challenging, time-consuming, and inaccurate.Objective
The primary purpose of this feasibility and acceptability study was to evaluate the impact of a digital medicine system (DMS) among Veterans (patients) with serious mental illness as compared with treatment as usual (TAU) on medication adherence.Methods
This open-label, 2-site, provider-randomized trial assessed aripiprazole refill adherence in Veterans with schizophrenia, schizoaffective disorder, bipolar disorder, or major depressive disorder. We randomized 26 providers such that their patients either received TAU or DMS for a period of 90 days. Semistructured interviews with patients and providers were used to examine the feasibility and acceptability of using the DMS.Results
We enrolled 46 patients across 2 Veterans Health Administration sites: 21 (46%) in DMS and 25 (54%) in TAU. There was no difference in the proportion of days covered by medication refill over 3 and 6 months (0.82, SD 0.24 and 0.75, SD 0.26 in DMS vs 0.86, SD 0.19 and 0.82, SD 0.21 in TAU, respectively). The DMS arm had 0.85 (SD 0.20) proportion of days covered during the period they were engaged with the DMS (mean 144, SD 100 days). Interviews with patients (n=14) and providers (n=5) elicited themes salient to using the DMS. Patient findings described the positive impact of the DMS on medication adherence, challenges with the DMS patch connectivity and skin irritation, and challenges with the DMS app that affected overall use. Providers described an overall interest in using a DMS as an objective measure to support medication adherence in their patients. However, providers described challenges with the DMS dashboard and integrating DMS data into their workflow, which decreased the usability of the DMS for providers.Conclusions
There was no observed difference in refill rates. Among those who engaged in the DMS arm, the proportion of days covered by refills were relatively high (mean 0.85, SD 0.20). The qualitative analyses highlighted areas for further refinement of the DMS.Trial registration
ClinicalTrials.gov NCT03881449; https://clinicaltrials.gov/ct2/show/NCT03881449.Type
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Gonzales, Sarah, Olaoluwa O Okusaga, J Corey Reuteman-Fowler, Megan M Oakes, Jamie N Brown, Scott Moore, Allison A Lewinski, Cristin Rodriguez, et al. (2022). Digital Medicine System in Veterans With Severe Mental Illness: Feasibility and Acceptability Study. JMIR formative research, 6(12). p. e34893. 10.2196/34893 Retrieved from https://hdl.handle.net/10161/28693.
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Scholars@Duke
Scott Daniel Moore
We are currently developing a model system for the investigation of physiological effects of acute ethanol. This model utilizes a rat brain slice preparation incorporating the amygdala, a brain region associated with anxiety and ethanol-induced anxiolysis. We anticipate expanding this model to investigate effects of other anxiolytic agents and to elucidate the basic mechanisms underlying anxiogenesis.
We are also currently examining the neurobiological basis of seizure-induced memory disruption using similar in vitro electrophysiological techniques. Full development of this model should provide important information relevant to basic mechanisms of memory. We anticipate expanding this model to include behavioral correlates.
Allison A. Lewinski
I am a health services researcher and implementation scientist with a joint appointment at the Duke University School of Nursing (DUSON) and the Durham Veterans Affairs Health Care System (VHA). My expertise spans diabetes distress, qualitative research methods, and virtual care delivery (including telehealth and digital health).
My research examines how virtual care interventions can reduce distress, improve self-management, expand access to evidence-based care, and enhance patient and population health outcomes. I focus on patient-, provider-, and system-level factors that influence the use and effectiveness of virtual care. This work has been funded by competitive grants, published in high-impact journals, presented at national conferences, and used to inform health system decision-making. I am frequently sought by colleagues locally and nationally for expertise in diabetes distress, qualitative methods, and virtual care strategies for grants, projects, and manuscripts.
I strive to improve outcomes for individuals with chronic illness by developing equitable, sustainable virtual care solutions and evaluating their implementation. To optimize these interventions, I apply qualitative and implementation science approaches to ensure alignment among patient needs, care modalities, disease states, and social contexts. My work addresses critical questions: for whom and for what purposes are these interventions effective, in which contexts, and at what points in the care continuum. Ultimately, my research advances the implementation and adoption of virtual care to reduce psychosocial distress and improve health outcomes through patient-clinician interactions and system-level innovations.
Valerie A. Smith
Valerie A. Smith, DrPH, is a Professor in the Duke University Department of Population Health Sciences. Her methodological research interests include methods for semicontinuous and zero-inflated data, cost and utilization modeling, causal inference methods, observational study design, and longitudinal data analysis.
Dr. Smith works largely in collaboration with a multidisciplinary team of researchers, with a focus on health policy interventions, health care utilization and expenditure patterns, program and policy evaluation, bariatric surgery and obesity treatment evaluation, aging, and caregiving.
Areas of expertise: Biostatistics, Health Services Research, Health Economics, and Health Policy
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