The growing availability of electronic health data and increasing sophistication of the analytic capacities of computer systems presents new opportunities for using such capacities to impact health outcomes. Administrative health data has been used for risk stratification of patient populations in the insurance industry, but can it be used in the health care industry to accurately predict which patients will be admitted to the hospital?
To answer this question, the Heritage Provider Network (HPN) developed the Heritage Health Prize , to spur development of new approaches in the analysis of health data and create new predictive algorithms.
This prize is designed to challenge teams to develop algorithms that will, based on a limited set of de-identified patient data, reliably predict which patients will be admitted to the hospital. The intent of this competition is to later apply this to patient populations prospectively and in real time to alert providers to patients at risk for hospital admissions. In this way, providers can develop new care plans, ultimately reducing the number of patient hospitalizations.
Participants in the Health Prize challenge will be given a data set comprised of the de-identified medical records of 100,000 individuals who are members of HPN. The teams will then need to predict the hospitalization of a set percentage of those members who went to the hospital during the year following the start date, and do so with a defined accuracy rate. The winners will receive the $3 million prize, which is larger than the Nobel Prize for Medicine.
(Thanks to Fred Grunwald for the tip! Gregory PS, Editor)