TY - JOUR
T1 - Reliability of 30-Day Readmission Measures Used in the Hospital Readmission Reduction Program
AU - Thompson, Michael P.
AU - Kaplan, Cameron M.
AU - Cao, Yu
AU - Bazzoli, Gloria J.
AU - Waters, Teresa M.
N1 - Publisher Copyright:
© Health Research and Educational Trust
PY - 2016/12/1
Y1 - 2016/12/1
N2 - Objective: To assess the reliability of risk-standardized readmission rates (RSRRs) for medical conditions and surgical procedures used in the Hospital Readmission Reduction Program (HRRP). Data Sources: State Inpatient Databases for six states from 2011 to 2013 were used to identify patient cohorts for the six conditions used in the HRRP, which was augmented with hospital characteristic and HRRP penalty data. Study Design: Hierarchical logistic regression models estimated hospital-level RSRRs for each condition, the reliability of each RSRR, and the extent to which socioeconomic and hospital factors further explain RSRR variation. We used publicly available data to estimate payments for excess readmissions in hospitals with reliable and unreliable RSRRs. Principal Findings: Only RSRRs for surgical procedures exceeded the reliability benchmark for most hospitals, whereas RSRRs for medical conditions were typically below the benchmark. Additional adjustment for socioeconomic and hospital factors modestly explained variation in RSRRs. Approximately 25 percent of payments for excess readmissions were tied to unreliable RSRRs. Conclusions: Many of the RSRRs employed by the HRRP are unreliable, and one quarter of payments for excess readmissions are associated with unreliable RSRRs. Unreliable measures blur the connection between hospital performance and incentives, and threaten the success of the HRRP.
AB - Objective: To assess the reliability of risk-standardized readmission rates (RSRRs) for medical conditions and surgical procedures used in the Hospital Readmission Reduction Program (HRRP). Data Sources: State Inpatient Databases for six states from 2011 to 2013 were used to identify patient cohorts for the six conditions used in the HRRP, which was augmented with hospital characteristic and HRRP penalty data. Study Design: Hierarchical logistic regression models estimated hospital-level RSRRs for each condition, the reliability of each RSRR, and the extent to which socioeconomic and hospital factors further explain RSRR variation. We used publicly available data to estimate payments for excess readmissions in hospitals with reliable and unreliable RSRRs. Principal Findings: Only RSRRs for surgical procedures exceeded the reliability benchmark for most hospitals, whereas RSRRs for medical conditions were typically below the benchmark. Additional adjustment for socioeconomic and hospital factors modestly explained variation in RSRRs. Approximately 25 percent of payments for excess readmissions were tied to unreliable RSRRs. Conclusions: Many of the RSRRs employed by the HRRP are unreliable, and one quarter of payments for excess readmissions are associated with unreliable RSRRs. Unreliable measures blur the connection between hospital performance and incentives, and threaten the success of the HRRP.
KW - Readmissions
KW - reliability
KW - risk-adjustment
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U2 - 10.1111/1475-6773.12587
DO - 10.1111/1475-6773.12587
M3 - Article
C2 - 27766634
AN - SCOPUS:84995404110
SN - 0017-9124
VL - 51
SP - 2095
EP - 2114
JO - Health Services Research
JF - Health Services Research
IS - 6
ER -