Public Health

Tracking short-term public health outcomes using high-resolution TEMPO data

Allan C. Just PhD, Icahn School of Medicine at Mount Sinai

Daniel Carrión PhD MPH, Icahn School of Medicine at Mount Sinai

The Mount Sinai Health System is a large, multi-faceted healthcare system, located predominantly in the greater New York metropolitan area. Mount Sinai has more than 150,000 inpatient, 3.4 million outpatient, and 0.5 million emergency visits each year over eight hospitals and numerous health centers. The health system is integrating and harmonizing health records across all encounters to ensure effective data to improve health outcomes. Near real-time daytime hourly estimates of gaseous air pollutants from TEMPO will be included as acute exposures in epidemiological case-crossover analyses of children’s asthma exacerbations. This approach compares exposure before case events (e.g. unprompted emergency or urgent care medical visits and medication adjustments) and control periods for the same participants. Distributed lag non-linear modelling will be used to identify critical exposure windows relative to the time of visit, assigning exposure based on the child’s geocoded home address. The richness of our health datasets will allow us to stratify by key variables such as asthmatic subtypes, as they may be differentially susceptible to air pollution levels. Improved exposure assessment within epidemiological studies can provide the evidence base to predict short-term public health outcomes and, consequently, improve healthcare decision-making. For example, changing air pollution levels may lead to notifications or prompts for specific patients to avoid physical exertion or to stay indoors when possible. It can also underscore the importance of effective disease management, whereby individuals who live in areas with chronically higher exposures can be targeted for outreach for checkups and prescription refills.

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