wHealth static hospital price transparency
Our approach to understanding hospital price variability focuses on the holistic view of the environment in which hospitals operate. We focus on patient-level, health-system, and socio-economic factors to provide a robust context to investigate this pricing dilemma. Our fundamental question asks how these factors relate to the hospital pricing variability.
We used the Robert Wood Johnson Foundationâ€™s County Health Ranking and Roadmap framework to profile each county in the United States. This framework is based on rates of smoking, obesity, unemployment, being uninsured, as well as gender, race, and income. We chose six common DRGs and calculated the weighted average price based on the number of hospitals and discharges within a county. That weighted average price, combined with the various measures from the RWJF County Health Ranking, was analyzed using linear regression to determine which county-level factors were associated with higher prices. We then provided mathematical models to allow users to predict their cost of a hospitalization for a particular condition based on their geographic location, health and demographic profile.
Our analysis showed three main findings. First, counties with higher rates of unemployment and uninsured individuals had higher prices charged to patients. On average, prices rose $576.76 and $389.87 for every 1% increase in rates of unemployment and uninsured, respectively. Second, certain subgroups of the population, such as women, appear to be associated with higher prices. Lastly, smoking and obesity are known factors that increase overall healthcare costs, but play little to no role in determining charges billed by hospitals.