Generalizability of heat-related health risk associations observed in a large healthcare claims database of patients with commercial health insurance.

Abstract

Extreme ambient heat is unambiguously associated with higher risk of illness and death. The Optum Labs Data Warehouse (OLDW), a database of medical claims from US-based patients with commercial or Medicare Advantage health insurance, has been used to quantify heat-related health impacts. Whether results for the insured sub-population are generalizable to the broader population has to our knowledge not been documented. We sought to address this question, for the US population in California from 2012 to 2019. We examined changes in daily rates of emergency department (ED) encounters and in-patient hospitalization encounters for all-causes, heat-related outcomes, renal disease, mental/behavioral disorders, cardiovascular disease, and respiratory disease. OLDW was the source for health data for insured individuals in California, and health data for the broader population were gathered from the California Department of Health Care Access and Information (HCAI). We defined extreme heat exposure as any day in a group of 2 or more days with maximum temperatures exceeding the county-specific 97.5 th percentile and used a space-time-stratified case-crossover design to assess and compare the impacts of heat on health. Average incidence rates of medical encounters differed by dataset. However, rate ratios for ED encounters were similar across datasets for all causes (ratio of incidence rate ratios (rIRR) = 0.989; 95% confidence interval (CI) = 0.973, 1.011), heat-related causes (rIRR = 1.080; 95% CI = 0.999, 1.168), renal disease (rIRR = 0.963; 95% CI = 0.718, 1.292), and mental health disorders (rIRR = 1.098; 95% CI = 1.004, 1.201). Rate ratios for inpatient encounters were also similar. This work presents evidence that OLDW can continue to be a resource for estimating the health impacts of extreme heat.