Measuring Value in Healthcare

Abstract

A statistical description and model of individual healthcare expenditures in the US has been developed for measuring value in healthcare. We find evidence that healthcare expenditures are quantifiable as an infusion-diffusion process, which can be thought of intuitively as a steady change in the intensity of treatment superimposed on a random process reflecting variations in the efficiency and effectiveness of treatment. The arithmetic mean represents the net average annual cost of healthcare; and when multiplied by the arithmetic standard deviation, which represents the effective risk, the result is a measure of healthcare cost control. Policymakers, providers, payors, or patients that decrease these parameters are generating value in healthcare. The model has an average absolute prediction error of approximately 10-12% across the range of expenditures which spans 6 orders of magnitude over a nearly 10-year period. For the top 1% of the population with the largest expenditures, representing 20%-30% of total spending on healthcare, a power-law relationship emerges. This relationship also applies to the most expensive medical conditions in the US. A fundamental connection between healthcare expenditures and mathematical finance is found by showing that the process healthcare expenditures follow is similar to a widely used model for managing financial assets, leading to the conclusion that a combination of these two fields may yield useful results.