Because I See You: Pharmacist Social Determinants of Health as Predictor of Structural Awareness.

BACKGROUND: The contribution of Social Determinants of Health to health disparities and patient outcomes is widely acknowledged. Much less has been done to characterize provider SDOH, and in particular their effect on delivery of structurally competent care. Differing lived experiences create blind spots to the critical upstream factors contributing to health. OBJECTIVES: The primary objective of this study was to examine the association between Structural Awareness (SA) and Social Determinants of Health (SDOH) when controlling for year of first licensure, primary setting of pharmacy practice, race, and gender. The secondary objective was to examine the difference in mean SA scores with four stand-alone predictor variables: reliance on public transportation, insurance coverage gaps, food insecurity, and housing insecurity. METHODS: This study is a cross-sectional web-based survey of 606 Minnesota pharmacists. SDOH risk and SA scores were assessed using modified versions of the PRAPARE and CCSAQ tools, respectively. The association of these scores was assessed using a multiple linear regression model and the association with stand-alone variables was done using t-tests. RESULTS: SDOH risk was significantly associated with SA at the 95% confidence level with a p-value of 0.0016. Food and housing insecurity were also significantly associated with SA score while reliance on public transportation and insurance coverage gaps were not. CONCLUSION: Pharmacy and other healthcare professional training programs should create opportunities for exposure to the SDOH experienced by their patients through immersive learning and/or experiential education.

Falling through the net: An adaptive assessment of the 'Three Delays' encountered by patients seeking emergency maternal and neonatal care within a remote health system on Lake Victoria, Kenya.

In rural sub-Saharan Africa, preventable delays in accessing emergency care remain a dominant factor in maternal and neonatal deaths. The MOMENTUM study is a pragmatic cohort investigation designed to measure the "Three Delays", i.e. delays in recognizing need for care (Type 1), reaching care (Type 2), and receiving care (Type 3) within a remote island health system on Lake Victoria, Kenya. The study utilizes an adaptive methodology to provide actionable data for a locally-directed "Health Navigation" intervention. We present analysis of 56 maternal and neonatal emergency cases occurring between January 2019 and February 2020. The mean Total Delay Interval (Type 1-3) reported was 39.3 ± 32.3hours. Notably, 18 cases in this cohort resulted in a neonatal (n = 16) or maternal death (n = 2). Sub-analysis indicates significant delay interval reductions associated with involvement of a "Health Navigator" in emergency care coordination for Type 2 Delay Intervals (0.5 ± 0.3 vs. 1.2 ± 1.1 hrs., p = 0.002) and Type 3 Delay Intervals (17.9 ± 14.1 vs. 32.9 ± 33.7 hrs., p = 0.030). Prolonged delays, complex barriers, and high mortality highlight the fraught nature of maternal emergencies in this remote setting. We discuss practical considerations for application of the Three Delays model, and avenues for further investigation.

The MOMENTUM study: Putting the 'Three Delays' to work to evaluate access to emergency obstetric and neonatal care in a remote island community in Western Kenya.

Despite worldwide improvements in maternal and infant mortality, mothers and babies in remote, low-resource communities remain disproportionately vulnerable to adverse health outcomes. In these settings, delays in accessing emergency care are a major driver of poor outcomes. The 'Three Delays' model is now widely utilised to conceptualise these delays. However, in out-of-hospital contexts, operational and methodological constraints present major obstacles in practically quantifying the 'Three Delays'. Here, we describe a novel protocol for the MOMENTUM study (Monitoring of Maternal Emergency Navigation and Triage on Mfangano), a 12-month cohort design to assess delays during obstetric and neonatal emergencies within the remote villages of Mfangano Island Division, Lake Victoria, Kenya. This study also evaluates the preliminary impact of a community-based intervention called the 'Mfangano Health Navigation' programme. Utilising participatory case audits and contextually specific chronological reference strategies, this study combines quantitative tools with deeper-digging qualitative inquiry. This pragmatic design was developed to empower local research staff and study participants themselves as assets in unravelling the complex socio-economic, cultural, and logistical dynamics that contribute to delays, while providing real-time feedback for locally driven intervention. We present our methods as an adaptive framework for researchers grappling with similar challenges across fragmented, rural health landscapes.