Literature Collection

OBJECTIVES: Patients experiencing homelessness (PEH) with serious mental illness (SMI) have poor satisfaction with primary care. We assessed if primary care teams tailored for homeless patients (Homeless-Patient Aligned Care Teams (H-PACTs)) provide this population with superior experiences than mainstream primary care and explored whether integrated behavioral health and social services were associated with favorable experiences. METHODS: We surveyed VA PEH with SMI (n = 1095) to capture the valence of their primary care experiences in 4 domains (Access/Coordination, Patient-Clinician Relationships, Cooperation, and Homeless-Specific Needs). We surveyed clinicians (n = 52) from 29 H-PACTs to elucidate if their clinics had embedded mental health, addiction, social work, and/or housing services. We counted these services in each H-PACT (0-4) and classified H-PACTs as having high (3-4) versus low (0-2) service integration. We controlled for demographics, housing history, and needs in comparing H-PACT versus mainstream experiences; and experiences in high versus low integration H-PACTs. RESULTS: Among respondents, 969 (91%) had complete data and 626 (62%) were in H-PACTs. After covariate adjustment, compared to mainstream respondents, H-PACT respondents were more likely (P < .01) to report favorable experiences (AORs = 1.7-2.1) and less likely to report unfavorable experiences (AORs = 0.5-0.6) in all 4 domains. Of 29 H-PACTs, 27.6% had high integration. High integration H-PACT respondents were twice as likely as low integration H-PACT respondents to report favorable access/coordination experiences (AOR = 1.7). CONCLUSIONS: Homeless-tailored clinics with highly-integrated services were associated with better care experiences among PEH with SMI. These observational data suggest that tailored primary care with integrated services may improve care perceptions among complex patients.

INTRODUCTION: Older adults face significant health risks owing to gaps in the management of polypharmacy and medication adherence, as well as the integration of physical and mental health needs. Current models do not fully address these challenges. This study introduced the Safety, Efficacy, and Adherence (SEA) model designed to enhance interdisciplinary collaboration, improve medication management, and integrate care for older adults. This model addresses the core drivers of poor health outcomes: (1) medication adherence challenges, (2) social determinants of health, (3) polypharmacy, (4) team-based care with family support for deprescribing, and (5) psychosocial factors related to aging. METHODS: The SEA model was developed through a structured literature review focusing on medication safety, polypharmacy, behavioral health integration, home safety inspections and adherence. It draws on frameworks such as the Chronic Care Model, Interprofessional Collaborative Care for Older Adults, and Consolidated Framework for Implementation Research. This model fosters interdisciplinary collaboration by integrating pharmacists, primary care providers, mental health professionals, substance use treatment, and family suppowrt, and it is adaptable to diverse clinical settings. RESULTS: The SEA model assessed short- and long-term outcomes. Potential short-term effects included improved medication adherence, enhanced team coordination, and reduced occurrence of adverse drug events. Long-term goals and possible effects included better chronic disease management, fewer hospitalizations, and improved quality of life for older adults. The model's scalability allows for application across various healthcare settings, although further testing is required for validation. CONCLUSION: The SEA model provides a comprehensive framework for addressing the complex needs of older adults by focusing on medication SEA. Two vignettes, one clinical and one organizational, demonstrate the practical application of the model in patient care and implementation science. By improving interdisciplinary collaboration and addressing social and behavioral factors, in home safety for medications, this model aims to reduce polypharmacy and hospitalization. Based on existing evidence-based frameworks, this model would benefit from future studies to validate its effectiveness in diverse settings.

The United States Preventive Services Task Force (USPSTF) recommends routine screening for alcohol use disorders in adults 18 years or older using one to three validated tools. One favored tool is the Alcohol Use Disorders Identification Test-Concise (AUDIT-C), a brief three-item questionnaire noted for its ease of implementation, sensitivity, and specificity. A positive screen on the AUDIT-C should prompt brief behavioral health counseling to help reduce harmful drinking patterns. Before this quality improvement project, the Texas Tech University Health Sciences Center (TTUHSC) El Paso Internal Medicine Residency Clinic did not routinely use the AUDIT-C and its residents had not received training in alcohol-related behavioral health counseling. In response, the AUDIT-C was integrated into the clinic's electronic medical record (EMR), and residents received instruction on alcohol use disorder counseling from a certified physician in Addiction Medicine. This intervention enhanced compliance with USPSTF recommendations and provided an opportunity to evaluate alcohol use in a primarily Hispanic border population. A total of 39 patients reporting alcohol use were screened with the AUDIT-C; 34 screened positive and five screened negative. Among the patients who received behavioral health counseling, 12 completed a post-counseling survey to assess their drinking habits. The survey revealed that 10 (83%) of these patients had never previously received counseling. Furthermore, nine (75%) found the counseling helpful, eight (67%) were surprised by the unhealthiness of their drinking habits, and nine (75%) felt comfortable during the session. Additionally, eight (67%) expressed a willingness to consider changing their drinking behaviors. Among those unwilling to change, five patients did not perceive a problem with their drinking, while one patient did not wish to reduce alcohol consumption. These findings demonstrate a strong willingness among El Paso residents to discuss problematic alcohol use within the clinical setting. The positive patient responses support the broader implementation of the AUDIT-C in practice and underscore the importance of training clinicians in effective intervention techniques.

BACKGROUND: Systematic implementation of guidelines for opioid therapy management in chronic non-cancer pain can reduce opioid-related harms. However, implementation of guideline-recommended practices in routine care is subpar. The goal of this quality improvement (QI) project is to assess whether a clinic-tailored QI intervention improves the implementation of a health system-wide, guideline-driven policy on opioid prescribing in primary care. This manuscript describes the protocol for this QI project. METHODS: A health system with 28 primary care clinics caring for approximately 294,000 primary care patients developed and implemented a guideline-driven policy on long-term opioid therapy in adults with opioid-treated chronic non-cancer pain (estimated N = 3980). The policy provided multiple recommendations, including the universal use of treatment agreements, urine drug testing, depression and opioid misuse risk screening, and standardized documentation of the chronic pain diagnosis and treatment plan. The project team drew upon existing guidelines, feedback from end-users, experts and health system leadership to develop a robust QI intervention, targeting clinic-level implementation of policy-directed practices. The resulting multi-pronged QI intervention included clinic-wide and individual clinician-level educational interventions. The QI intervention will augment the health system's "routine rollout" method, consisting of a single educational presentation to clinicians in group settings and a separate presentation for staff. A stepped-wedge design will enable 9 primary care clinics to receive the intervention and assessment of within-clinic and between-clinic changes in adherence to the policy items measured by clinic-level electronic health record-based measures and process measures of the experience with the intervention. DISCUSSION: Developing methods for a health system-tailored QI intervention required a multi-step process to incorporate end-user feedback and account for the needs of targeted clinic team members. Delivery of such tailored QI interventions has the potential to enhance uptake of opioid therapy management policies in primary care. Results from this study are anticipated to elucidate the relative value of such QI activities.

BACKGROUND: Clinical trials of remote patient monitoring (RPM) technology are well-suited to remote studies, for which patients complete key procedures online. However, remote digital health studies often suffer from low enrollment and retention, threatening the successful achievement of study outcomes and wasting resources and time. Recruiting patients from a large integrated health system offers a greater potential pool of participants for enrollment, which can increase the likelihood of successful study completion. OBJECTIVE: This study describes enrollment and retention outcomes for a remote digital health study of an RPM device conducted in collaboration with researchers from the Veterans Health Administration (VA). The VA is the largest integrated health system in the United States, with 9 million enrollees who are, as a group, older and with more medical and mental health comorbidities than the civilian population. METHODS: We aimed to enroll 200 VA patients for a clinical study of a cellular-enabled, handheld, multisensor device that captures multiple health parameters and transmits data to a cloud-based dashboard for viewing by clinicians. Eligible patients were hospitalized with COVID-19 within 3-6 months before enrollment and had one of 6 pre-existing medical comorbidities. Potentially eligible patients were identified using the VA Corporate Data Warehouse. Every 3 weeks, up to 1000 potentially eligible patients were mailed a recruitment letter. All study tasks, including obtaining informed consent, device training and troubleshooting, and handling study-related questions, were completed online and by telephone. Device and survey data were combined with VA clinical and utilization data to develop a predictive algorithm for clinical decompensation. The geographic distribution of enrolled patients was mapped by county. Demographic and health characteristics of nonenrolled versus enrolled, and of completers versus noncompleters were compared using t tests and chi-square tests as appropriate. Reasons for noncompletion were summed. Multivariate logistic regression was used to evaluate variables associated with enrolling versus nonenrolling, and completing versus noncompleting. RESULTS: Of the 7714 who were mailed a study invitation, 560 were screened. Of the screened patients, 203 were enrolled (2.9% enrollment yield) and 166 completed the study (82% retention rate). Enrolled patients were broadly distributed across the United States. Among those enrolled, completers and noncompleters were similar except for a slightly higher proportion of patients with hypertension among completers. The most common reason for noncompletion of the study was that participants were unable to be contacted for study tasks. CONCLUSIONS: Remote digital health studies are increasingly common, but inadequate enrollment often results in failed studies. Recruiting patients through the VA enables access to a very large population of potentially eligible patients and can help ensure that clinical trials reach targets for enrollment and completion. TRIAL REGISTRATION: ClinicalTrials.gov NCT05713266; https://clinicaltrials.gov/study/NCT05713266.