Assessing a Digital Medicine System in Veterans with Severe Mental Illness: A provider-randomized clinical trial (Preprint)



Suboptimal medication adherence is a significant problem for patients with serious mental illness (SMI). Measuring medication adherence through subjective and objective measures can be challenging, time consuming and inaccurate.


We evaluated a digital medicine system (DMS) compared to treatment as usual (TAU) on adherence to oral aripiprazole and patient and provider perspectives on the feasibility and acceptability of a DMS.


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. Semi-structured interviews with patients and providers were used to examine feasibility and acceptability of using the DMS.


We enrolled 46 patients across 2 Veterans Affairs (VA) sites: (21 in DMS and 25 in TAU). There was no difference in medication refill over 3 and 6 months, respectively (82% and 75% DMS vs. 86% and 82% TAU). The DMS arm had 85% days covered during the period they were engaged with the DMS (144 days on average). Interviews with patients (n=14) and providers (n=5) elicited themes salient to using the DMS. Patient themes included: pre-enrollment adherence strategies and interest in the DMS, positive impact on medication adherence, system usability challenges, support needs, and suggested design/functionality improvements. Provider themes included: concerns for patient medication adherence and interest in the DMS, concerns with the DMS, DMS dashboard usability, challenges of the DMS, and suggestions to increase provider use.


There was no observed difference in refill rates. Among those who engaged in the DMS arm, refill rates were relatively high (85%). The qualitative analyses highlighted areas for further refinement of the DMS.








Published Version (Please cite this version)


Publication Info

Gonzales, Sarah, Olaoluwa O Okusaga, J Corey Reuteman-Fowler, Megan M Oakes, Jamie N Brown, Scott Moore, Allison A Lewinski, Cristin Rodriguez, et al. (2021). Assessing a Digital Medicine System in Veterans with Severe Mental Illness: A provider-randomized clinical trial (Preprint). 10.2196/preprints.34893 Retrieved from

This is constructed from limited available data and may be imprecise. To cite this article, please review & use the official citation provided by the journal.



Allison A. Lewinski

Assistant Research Professor in the School of Nursing

As a nurse scientist and health services researcher, with a joint appointment between the Duke University School of Nursing (DUSON) and the Durham Veterans Affairs Health Care System (VHA), I have acquired expertise in the areas of diabetes distress, qualitative research methods, and virtual care (e.g., telehealth, digital health) as a method of care delivery. My research focuses on the current and potential ability of virtual care interventions to reduce distress, improve self-management, increase access to evidence-based care delivery, and improve patient and population health outcomes. My collaborative and interdisciplinary research focuses on how patient-, provider-, and system-level factors influence virtual care use and outcomes. As evidence of its growing significance and impact at DUSON and the VHA, my work has been well funded, published in high-impact journals, presented at select conferences, and used to guide health system decision-making. I am a sought-after teacher and mentor because I connect my research interests to teaching students and mentees rigorous and systematic research approaches. I am frequently asked by local and national colleagues to provide guidance on distress, qualitative research methods, and virtual care approaches used in grants, projects, and manuscripts.  

My research contributions have focused on alleviating psychosocial distress, developing and implementing multi-level virtual care interventions, and enhancing qualitative methods. As a staff nurse, I witnessed the psychosocial distress of patients who experience challenges in obtaining care which led to my interest in diabetes distress. I aspire and work to improve health outcomes for individuals with chronic illness by developing equitable and sustainable multi-level virtual care interventions and assessing their implementation and adaptation. Virtual care describes any remote interaction between a patient and/or members of their care team. To achieve these goals, I use qualitative methods and implementation science approaches to enhance alignment between patient, modality, disease state, and social and environmental context; my collective assessments address for whom and what purposes, in what situations and contexts, when in a disease course or clinical activity, and in what specific ways such interventions are effective. My focus on the uptake and adoption of virtual care to address psychosocial distress considers interactions with patients, between patients and clinicians, and within health care systems and the larger population.


Valerie A. Smith

Associate Professor in Population Health Sciences

Valerie A. Smith, DrPH, is an Associate Professor in the Duke University Department of Population Health Sciences and Senior Research Director of the Biostatistics Core at the Durham Veterans Affairs Medical Center's Center of Innovation. Her methodological research interests include: methods for semicontinuous and zero-inflated data, economic modeling methods, causal inference methods, observational study design, and longitudinal data analysis. Her current methodological research has focused on the development of marginalized models for semicontinuous data.

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, obesity and weight loss, bariatric surgery evaluation, and family caregiver supportive services.

Areas of expertise: Biostatistics, Health Services Research, Health Economics, and Health Policy

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