Assessing the Estimands and Estimates of Hospitalization Rates in Health Economics and Clinical Medicine

Even though data on hospital admissions are widely used in health research, hospitalization-related quantities measured using these data are not always clearly conceptualized. Consequently, estimators of these quantities can have unclear rationales and undesirable properties. We evaluate three rate estimators for measuring hospitalization-related quantities that are of interest in health economics and clinical medicine subspecialities. Using the Grossman human capital model, we motivate the importance of measuring healthy time. We show that an upper bound on healthy time can be calculated using lengths of hospital stay without assumptions about health status outside the hospital. We find that an admission rate conventionally used in clinical research is a patient follow-up time weighted average that lacks a clear basis for the weights. We evaluate the Centers for Medicare and Medicaid Services (CMS) use of risk-standardized readmission rates to penalize hospitals under the Hospital Readmissions Reduction Program (HRRP) and find that it may inadvertently conflict with disease-specific care aimed at reducing mortality risk. We show that risk-standardized rates can be sensitive to patient case mix, potentially leading to hospital rankings that do not reflect hospital quality. We also summarize debates regarding the effectiveness of risk-standardized readmission rates in reducing readmissions.