Objective: To explore predictors of gaps between observed and best possible Hospital Compare scores in U.S. hospitals.
Data sources: American Hospital Association Annual Survey; Area Resource Files; Centers for Medicare and Medicaid Services Medicare Provider and Analysis Review; and Hospital Compare data.
Study design: Using Stochastic Frontier Analysis and secondary cross-sectional data, gaps between the best possible and actual scores of Hospital Compare quality measures were estimated. Poisson regressions were used to ascertain financial, organizational, and market predictors of those gaps.
Data extraction: Data were cleaned and matched based on hospital Medicare IDs. All U.S. hospitals that matched on analysis variables in 2007 were in the study (1,823-2,747, depending upon gap variable).
Principal findings: Most hospitals have a greater than 10 percent gap in quality indicators. Payer mix, registered nurse staffing, size, case mix index, accreditation, being a teaching hospital, market competition, urban location, and region were strong predictors of gaps, although the direction of the association with gaps was not uniform across outcomes.
Conclusions: A significant percentage of hospitals have gaps between their best possible and observed quality scores. It may be better to use gap scores than observed scores in payments systems. More SFA research is needed to know how to lower gaps through changes in hospital and market characteristics.
Keywords: Stochastic Frontier Analysis; predictors of gaps in hospital quality.
© Health Research and Educational Trust.