How Measurement Variability Affects Reporting of a Single Readmission Metric

Readmissions are an important quality measure for public reporting, payment, and collaborative research. Lack of measure standardization may lead to inconsistent reporting of outcomes across study sites. In this study, we examined the impact of measurement variability on reporting of a single readmission metric, 30-day all-condition readmission rates (ARRs). We conducted a secondary database analysis of 2006-2008 Medicaid Analytic eXtract data merged from four states of children younger than 21 years. We calculated 30-day ARRs for this cohort using three previously described models varying in their inclusions and exclusions of index hospitalizations and readmissions. The 30-day ARR was highest for the model allowing each readmission to serve as an index admission for subsequent readmissions (ARR: 7%); intermediate for the model allowing one index admission and more than one readmissions in each 30-day period (ARR: 6.2%); and lowest for the model allowing only one readmission in each 30-day period (ARR: 5.6%). Similar variation was seen when stratifying patients by individual diagnostic groups. In conclusion, measurement variability impacts reported outcomes of a single readmission metric. To improve the value of readmission as a quality metric, stakeholders engaged in multisite quality improvement or research should ensure that definitions are standardized across sites.