What Drives Variation in Healthcare Provider Prices?

Researchers have identified significant variation in the prices commercial insurers pay for similar healthcare services. A number of explanations of this variation have been proposed, some focusing on the provider, some focusing on the payer, and some focusing on geographic variation in costs. Learning which of these factors is most important will focus policymakers and researchers looking to evaluate the most important measures to constrain costs.

We use the Colorado All-Payer Claims Database to determine whether geography, providers, or payers are the main sources of variation in provider prices. In contrast to previous research, such as that using HCCI or Truven Marketscan data, we are able to reliably distinguish events associated with different providers and payers.[1] This enables us to assess the relative importance of payers and providers in driving costs. Also, by studying Colorado, we are able to evaluate this variation in a state without a single large dominant system and with multiple major metropolitan areas.

In line with previous research, we use two main approaches to evaluate prices. First, we isolate clinically homogeneous services and focus on the prices for those services. Second, we construct aggregate price indices after adjusting for treatment acuity. Preliminary results using both approaches are consistent; for the sake of brevity, we focus on the first set of results here.

We isolate a sample of inpatient admissions for non-complicated vaginal births paid for by commercial payers during the years 2012-2015. Consistent with previous research, there is a great deal of price variation across Colorado patients. The coefficient of variation for this sample is 31.1. Simple factors such as time and patient’s length of stay explain little – only 15% – of the variation in the data.

As has been previously found, our data show substantial price variation across metro areas. Including controls for these metro areas increases the explained variation of the data from 15% to 33%. Within a metro area, we find that variation in prices across hospitals and across insurers are of similar importance in explaining price variation. In particular, including insurer by metro area fixed effects or hospital fixed effects each increases the amount of explained variation to approximately 42%.

Interestingly, we find that there is not one uniformly low-cost or high-cost payer, and that payer fixed effects that do not vary across metro areas explain little of the variation in the data. These patterns imply that in some hospitals, a payer is higher priced relative to other payers but in other hospitals, that same payer is lower priced relative to other payers. Including controls for this hospital by payer variation explains an additional 7% of the variation in prices for labor and delivery.

We are in the process of assessing how observable characteristics of payers and providers correlate with differences in their average prices.

[1] However, our results will not name either payers or providers per our Data Use Agreement.