Literature Collection

As healthcare costs and physician burnout in the U.S. escalate, and the acuity and prevalence of behavioral health issues hit historical highs, it is critically important that we continue to evolve care approaches that can deliver good health and well-being at the population level. Colorado Integrated Behavioral Health Plus (CIBH+) uses a whole-person health perspective, aligning psychologists, primary care physicians, and other specialists, within a generalist approach to primary care. Here, we document our local experience in services delivery, including the rationale for the CIBH+ approach, key implementation elements, and the ability to mitigate population, patient, and provider challenge by building upon existing clinically-and cost-effective models of integrated care. With this description, we hope to spark optimism, enthusiasm, and ongoing innovation in other multidisciplinary care teams seeking ways to improve patient and provider experience.

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.