Literature Collection

OBJECTIVES: To demonstrate an innovative method combining machine learning with comparative effectiveness research techniques and to investigate a hitherto unstudied question about the effectiveness of common prescribing patterns. DATA SOURCES: United States Veterans Health Administration Corporate Data Warehouse. STUDY DESIGN: For Operation Enduring Freedom/Operation Iraqi Freedom veterans with major depressive disorder, we generate pharmacotherapy pathways (of antidepressants) using process mining and machine learning. We select the medication episodes that were started at subtherapeutic doses by the first assigned primary care physician and observe the paths that those medication episodes follow. Using 2-stage least squares, we test the effectiveness of starting at a low dose and staying low for longer versus ramping up fast while balancing observable and unobservable characteristics of patients and providers through instrumental variables. We leverage predetermined provider practice patterns as instruments. DATA COLLECTION: We collected outpatient pharmacy data for selective serotonin reuptake inhibitors and selective norepinephrine reuptake inhibitors, patient and provider characteristics (as control variables), and the instruments for our cohort. All data were extracted for the period between 2006 and 2020. PRINCIPAL FINDINGS: There is a statistically significant positive effect (0.68, 95% CI 0.11-1.25) of "ramping up fast" on engagement in care. When we examine the effect of "ramping up slow", we see an insignificant negative impact on engagement in care (-0.82, 95% CI -1.89 to 0.25). As expected, the probability of drop-out also seems to have a negative effect on engagement in care (-0.39, 95% CI -0.94 to 0.17). We further validate these results by testing with medication possession ratios calculated periodically as an alternative engagement in care metric. CONCLUSIONS: Our findings contradict the "Start low, go slow" adage, indicating that ramping up the dose of an antidepressant faster has a significantly positive effect on engagement in care for our population.

Family medicine departments see elevating equity, diversity, and inclusion (EDI)* as socially necessary and as powerful in achieving core missions. The importance and timeliness of this longstanding issue in medicine are magnified by the COVID-19 pandemic with its disproportionate effect on communities of color and by civil unrest focused on racial justice. EDI plays out in three pillars: (1) care delivery and health, (2) workforce recruitment and retention, and (3) learner recruitment and training. People are at very different places with EDI work with regard to knowledge, experience, comfort and confidence. This is a wide-ranging developmental challenge, not a narrow, technical, or quick fix. The Immediate Goal: To make a strong start in taking all faculty and staff on a participatory journey that brings changes in everything they do, using inclusive means to this inclusive end. Initial Achievements: An inclusive process that resulted in (1) a shared intellectual framework-definitions with "north star" goals across the three pillars of EDI action, (2) shared acceptance of need for change, (3) top growth areas with actions to take, and (4) harnessing the energy for action-many volunteers, a visible leader, and charge. Ongoing Action: Application of an equity lens to department relationships, specific incidents, tools and education, policy review, and measures development. Invitation to Further Conversation Among Departments: EDI work can quickly create a shared intellectual framework and broadly engage people in taking a department down its developmental path. Operating principles for undertaking such work are offered for conversation among departments.

Numerous barriers exist for patients attempting to access treatment for opioid-use disorder and/or naloxone, with geographical, racial, and age-related differences exacerbating these hardships.