Air Quality a Better Predictor Than Income of Who Will Use More Healthcare

A machine learning model from Jvion predicted which patients were most likely to be admitted to the hospital or visit the emergency department (ED) over a 90-day period, based on an algorithm fueled by easily obtained socioeconomic data: each patient’s age, gender, race and address. The study, appearing this week in the ninth annual health information technology issue of The American Journal of Managed Care, potentially offers health systems and policy makers a way to target groups of patients with “specific, individualized interventions to tackle detrimental social determinants of health,” at both the household and neighborhood levels. Learn more in Managed Healthcare Executive.

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