Faculty Bibliography

Unintentional overdose deaths, most involving opioids, have eclipsed all other causes of US deaths for individuals less than 50 years of age. An estimated 2.4 to 5 million individuals have opioid use disorder (OUD) yet a minority receive treatment in a given year. Medications for OUD (MOUD) are the gold standard treatment for OUD however early dropout remains a major challenge for improving clinical outcomes. A Cascade of Care (CoC) framework, first popularized as a public health accountability strategy to stem the spread of HIV, has been adapted specifically for OUD. The CoC framework has been promoted by the NIH and several states and jurisdictions for organizing quality improvement efforts through clinical, policy, and administrative levers to improve OUD treatment initiation and retention. This roadmap details CoC design domains based on available data and potential linkages as individual state agencies and health systems typically rely on limited datasets subject to diverse legal and regulatory requirements constraining options for evaluations. Both graphical decision trees and catalogued studies are provided to help guide efforts by state agencies and health systems to improve data collection and monitoring efforts under the OUD CoC framework.

Background/UNASSIGNED:Mobile health (mHealth) tools offer an effective and personalized approach to enhance chronic disease management and may partially offset provider-level barriers to increasing buprenorphine prescribing in primary care. This study assessed the feasibility of integrating a text messaging-based medical management tool (TeMeS) in primary care among patients initiating buprenorphine. Methods/UNASSIGNED:TeMeS messages are categorized per the medical management model, programed in a HIPAA-compliant texting software (Apptoto©), and delivered in a tiered fashion over 8-weeks to patients. This mixed-methods evaluation of TeMeS utilized key stakeholder feedback (patients, physicians, administrators, nursing), text messaging software process measures, thematic analysis of patient participant text message content, and electronic administrative data (eg, appointment adherence, treatment retention) at 2-months. Results/UNASSIGNED:The study team approached 65 patients and n = 14 (21%) were ineligible or declined to participate in the study. Most eligible participants owned a smartphone (90%), responded to at least one text query (88%) over an average of 24 days, and few requested to stop receiving texts (6%). Participant text replies included responses to cognitive behavioral therapy-based queries (13.8%), confirming or rescheduling appointments (6.1%), and insurance, pharmacy, or clinical issues pertaining to buprenorphine dispensation or dosing (2%). Suggestions for design modifications included personalizing message content and adjusting message frequency per patient risk of illicit opioid reuse, use of video-based informational content, and real-time provider and staff support for emergent issues. Conclusion/UNASSIGNED:Our findings highlight the acceptability, feasibility, and high rates of engagement of utilizing text messaging to enhance self-management among patients initiating buprenorphine treatment.

Objectives/UNASSIGNED:We aim to assess the influence of COVID-19 on the social needs of emergency department (ED) patients, and assess patients' access to social services. Methods/UNASSIGNED:We conducted a cross-sectional survey of 175 purposively sampled adult ED patients. Results/UNASSIGNED:Approximately half of participants stated that COVID-19 negatively impacted their social needs with statistically significant differences observed for race, ethnicity, and insurance status. Many participants did not know of available social services, and a majority welcomed assistance from the ED. Conclusion/UNASSIGNED:This study suggests that unmet social needs have risen because of COVID-19, and EDs may be positioned to identify and assist affected patients.

BACKGROUND:Guidelines recommend moderate to high-intensity statins and antithrombotic agents in patients with atherosclerotic cardiovascular disease (ASCVD). However, guideline-directed medical therapy (GDMT) remains suboptimal. METHODS:In this quality initiative, best practice alerts (BPA) in the electronic health record (EHR) were utilized to alert providers to prescribe to GDMT upon hospital discharge in ASCVD patients. Rates of GDMT were compared for 5 months pre- and post-BPA implementation. Multivariable regression was used to identify predictors of GDMT. RESULTS:In 5985 pre- and 5568 post-BPA patients, the average age was 69.1 ± 12.8 years and 58.5% were male. There was a 4.0% increase in statin use from 67.3% to 71.3% and a 3.1% increase in antithrombotic use from 75.3% to 78.4% in the post-BPA cohort. CONCLUSIONS:This simple EHR-based initiative was associated with a modest increase in ASCVD patients being discharged on GDMT. Leveraging clinical decision support tools provides an opportunity to influence provider behavior and improve care for ASCVD patients, and warrants further investigation.

Background: Mobile health cardiac rehabilitation (mHealth-CR) may improve outcomes among older adults with ischemic heart disease, but variable engagement is not yet understood. We therefore analyzed preliminary data from the RESILIENT trial, an ongoing randomized trial of mHealth-CR vs. usual care in patients age >= 65.
Method(s): Data from the first 50 intervention participants were analyzed. Weekly engagement was scored from 0-11 based on exercise completion, therapist communication, video viewing, and BP self-measurement. Participants were classified as high or low engagement based on median engagement scores. Groups were compared by age, sex, social support (living alone), depression (PHQ-8), and Charlson Comorbidity Index (CCI).
Result(s): There was widely varying engagement with mHealth-CR that ranged from nearly zero to nearly perfect engagement (Figure). There were no significant differences between high and low engagement groups based on mean age (72.6 vs. 72.8, P=0.8), sex (76% male vs. 80%, P=0.7), living alone (28% vs. 44%, P=0.2), depression (mean 3.9 vs. 4.6, P=0.5), or comorbidity burden (mean 4.4 vs. 4.8, P=0.3), although the sample size was small.
Conclusion(s): Our early findings show wide variation in mHealth-CR engagement among older adults

We present a hierarchical integrated model of self-regulation in which executive function is the cognitive component of the model, together with emotional, behavioral, physiological, and genetic components. These five components in the model are reciprocally and recursively related. The model is supported by empirical evidence, primarily from a single longitudinal study with good measurement at each level of the model. We also find that the model is consistent with current thinking on related topics such as cybernetic theory, the theory of allostasis and allostatic load, and the theory of skill development in harsh and unpredictable environments, referred to as "hidden talents." Next, we present literature that the integrative processes are susceptible to environmental adversity, poverty-related risk in particular, while positive social interactions with caregivers (e.g., maternal sensitivity) would promote self-regulatory processes or mitigate the adverse effect of early risk on the processes. A hierarchical integrative model of self-regulation advances our understanding of self-regulatory processes. Future research may consider broader social contexts of the integrative self-regulation system, such as neighborhood/community contexts and structural racism. This can be an integral step to provide children with equitable opportunities to thrive, even among children living in socioeconomically and psychosocially disadvantaged environments.