A wolf dressed in sheep's clothing: perhaps quality measures are just unmeasured severity

While there has been much discussion in recent years concerning the construction of hospital quality indexes, researchers have often failed to adequately test these quality measures against testable hypotheses. Our objective is to create a quality index using a fixed-effects methodology (FE-score) and use the resulting index to explain price variation across hospitals and theoretically grounded hypotheses.

Medicare data (MEDPAR) are used for the risk adjustment of patient characteristics and the calculation of a quality score using a fixed-effects methodology for all US hospitals that provide coronary artery bypass graft (CABG). The resulting FE-score then serves as an independent variable, among others, to explain market prices for patients treated at a subset of the hospitals who have health insurance supplied from a self-insured employer.

We find that the FE-score is positively correlated with prices, which is the opposite to the theory that hospitals with higher-than-expected adverse events would receive a lower price than higher quality hospitals. Other covariates such as insurance status and number of procedures do have the expected sign.

We conclude that the positive correlation between the FE-score and prices demonstrates that it is behaving more like a severity scale. This indicates either an inability to isolate true quality using administrative data (i.e. incomplete risk adjustment) or a possible market failure.