BACKGROUND: Value-based purchasing programs use administrative data to compare hospitals by rates of hospital-acquired pressure ulcers (HAPUs) for public reporting and financial penalties. However, validation of these data is lacking. OBJECTIVE: To assess the validity of the administrative data used to generate HAPU rates by comparing the rates generated from these data with those generated from surveillance data. DESIGN: Retrospective analysis of 2 million all-payer administrative records from 448 California hospitals and quarterly hospitalwide surveillance data from 213 hospitals from the Collaborative Alliance for Nursing Outcomes (as publicly reported on the CalHospitalCompare Web site). SETTING: 196 acute care hospitals with at least 6 months of available administrative and surveillance data. PATIENTS: Nonobstetric adults discharged in 2009. MEASUREMENTS: Hospital-specific HAPU rates were computed as the percentage of discharged adults (from administrative data) or examined adults (from surveillance data) with at least 1 stage II or greater HAPU (HAPU2+). Categorization of hospital performance based on administrative data was compared with the grade assigned when surveillance data were used. RESULTS: When administrative data were used, the mean hospital-specific HAPU2+ rate was 0.15% (95% CI, 0.13% to 0.17%); when surveillance data were used, the rate was 2.0% (CI, 1.8% to 2.2%). Among the 49 hospitals with HAPU2+ rates in the highest (worst) quartile from administrative data, use of the surveillance data set resulted in performance grades of "superior" for 3 of these hospitals, "above average" for 14, "average" for 15, and "below average" for 17. LIMITATION: Data are from 1 state and 1 year. CONCLUSION: Hospital performance scores generated from HAPU2+ rates varied considerably according to whether administrative or surveillance data were used, suggesting that administrative data may not be appropriate for comparing hospitals. PRIMARY FUNDING SOURCE: Agency for Healthcare Research and Quality.
BACKGROUND: Value-based purchasing programs use administrative data to compare hospitals by rates of hospital-acquired pressure ulcers (HAPUs) for public reporting and financial penalties. However, validation of these data is lacking. OBJECTIVE: To assess the validity of the administrative data used to generate HAPU rates by comparing the rates generated from these data with those generated from surveillance data. DESIGN: Retrospective analysis of 2 million all-payer administrative records from 448 California hospitals and quarterly hospitalwide surveillance data from 213 hospitals from the Collaborative Alliance for Nursing Outcomes (as publicly reported on the CalHospitalCompare Web site). SETTING: 196 acute care hospitals with at least 6 months of available administrative and surveillance data. PATIENTS: Nonobstetric adults discharged in 2009. MEASUREMENTS: Hospital-specific HAPU rates were computed as the percentage of discharged adults (from administrative data) or examined adults (from surveillance data) with at least 1 stage II or greater HAPU (HAPU2+). Categorization of hospital performance based on administrative data was compared with the grade assigned when surveillance data were used. RESULTS: When administrative data were used, the mean hospital-specific HAPU2+ rate was 0.15% (95% CI, 0.13% to 0.17%); when surveillance data were used, the rate was 2.0% (CI, 1.8% to 2.2%). Among the 49 hospitals with HAPU2+ rates in the highest (worst) quartile from administrative data, use of the surveillance data set resulted in performance grades of "superior" for 3 of these hospitals, "above average" for 14, "average" for 15, and "below average" for 17. LIMITATION: Data are from 1 state and 1 year. CONCLUSION: Hospital performance scores generated from HAPU2+ rates varied considerably according to whether administrative or surveillance data were used, suggesting that administrative data may not be appropriate for comparing hospitals. PRIMARY FUNDING SOURCE: Agency for Healthcare Research and Quality.
Authors: William V Padula; Robert D Gibbons; Robert J Valuck; Mary B F Makic; Manish K Mishra; Peter J Pronovost; David O Meltzer Journal: Med Care Date: 2016-05 Impact factor: 2.983
Authors: Jennifer Meddings; Heidi Reichert; Mary A M Rogers; Timothy P Hofer; Laurence F McMahon; Kyle L Grazier Journal: J Am Geriatr Soc Date: 2015-07-03 Impact factor: 5.562
Authors: William V Padula; Robert D Gibbons; Peter J Pronovost; Donald Hedeker; Manish K Mishra; Mary Beth F Makic; John Fp Bridges; Heidi L Wald; Robert J Valuck; Adam J Ginensky; Anthony Ursitti; Laura Ruth Venable; Ziv Epstein; David O Meltzer Journal: J Am Med Inform Assoc Date: 2017-04-01 Impact factor: 4.497
Authors: Barry L Rosenberg; Joshua A Kellar; Anna Labno; David H M Matheson; Michael Ringel; Paige VonAchen; Richard I Lesser; Yue Li; Justin B Dimick; Atul A Gawande; Stefan H Larsson; Hamilton Moses Journal: PLoS One Date: 2016-12-14 Impact factor: 3.240
Authors: William V Padula; Peter J Pronovost; Mary Beth F Makic; Heidi L Wald; Dane Moran; Manish K Mishra; David O Meltzer Journal: BMJ Qual Saf Date: 2018-08-10 Impact factor: 7.035