- Center on Health Equity & Access
- Clinical
- Health Care Cost
- Health Care Delivery
- Insurance
- Policy
- Technology
- Value-Based Care
Predicting Healthcare Utilization With Applied Machine Learning
On this episode of Managed Care Cast, we speak with John Showalter, MD, chief product officer at Jvion and an internal medicine physician, and Soy Chen, MS, director of data science at Jvion and part of their data science team. We discuss their research about using applied machine learning to predict healthcare utilization based on social determinants of health, appearing in the January 2019 Health IT issue of The American Journal of Managed Care®.
Researchers recently developed an algorithm for predicting which social determinants of health lead to hospitalizations and emergency department visits. The study, "Using Applied Machine Learning to Predict Healthcare Utilization Based on Socioeconomic Determinants of Care", appears in the annual Health IT issue of The American Journal of Managed Care®.
They found that the social determinant of health most associated with risk was air quality. In addition, neighborhood in-migration, transportation, and purchasing channel preferences were more telling than ethnicity or gender in determining patients’ use of resources.
On this episode of Managed Care Cast, we speak to study authors Soy Chen, MS, and John Showalter, MD, about how they sourced data for the algorithm, the technology's impact on the future of healthcare, and privacy concerns raised by artificial intelligence.
Listen above or through one of these podcast services:
