TY - JOUR
T1 - Incorporating harms into the weighting of the revised Agency for Healthcare Research and Quality Patient Safety for Selected Indicators Composite (Patient Safety Indicator 90)
AU - Zrelak, Patricia A.
AU - Utter, Garth H.
AU - McDonald, Kathryn M.
AU - Houchens, Robert L.
AU - Davies, Sheryl M.
AU - Skinner, Halcyon G.
AU - Owens, Pamela L.
AU - Romano, Patrick S
N1 - Funding Information:
This article was supported by Contract #HHSAA290201200003I from the Agency for Healthcare Research and Quality (AHRQ). Dr. Owens is an employee of AHRQ. Drs. Utter and Romano served on an AHRQ Quality Indicators Expert Workgroup, for which they received honoraria, and served as consultants to AHRQ for its Healthcare Cost and Utilization Project (HCUP). The views expressed in this article are those of the authors and do not necessarily reflect those of AHRQ or the US Department of Health and Human Services. No other disclosures. We acknowledge the HCUP Partner organizations that participated in the HCUP State Inpatient Databases: Arizona Department of Health Services, Arkansas Department of Health, California Office of Statewide Health Planning and Development, Colorado Hospital Association, Florida Agency for Health Care Administration, Georgia Hospital Association, Hawaii Laulima Data Alliance, Hawaii University of Hawai'i at Hilo, Illinois Department of Public Health, Indiana Hospital Association, Iowa Hospital Association, Kansas Hospital Association, Kentucky Cabinet for Health and Family Services, Maine Health Data Organization, Maryland Health Services Cost Review Commission, Massachusetts Center for Health Information and Analysis, Michigan Health & Hospital Association, Minnesota Hospital Association (provides data for Minnesota and North Dakota), Mississippi State Department of Health, Montana MHA—An Association of Montana Health Care Providers, Nebraska Hospital Association, Nevada Department of Health and Human Services, New Hampshire Department of Health & Human Services, New Jersey Department of Health, New Mexico Department of Health, New York State Department of Health, North Carolina Department of Health and Human Services, North Dakota (data provided by the Minnesota Hospital Association), Oklahoma State Department of Health, Oregon Association of Hospitals and Health Systems, Oregon Health Policy and Research, Pennsylvania Health Care Cost Containment Council, Rhode Island Department of Health, South Carolina Budget & Control Board, South Dakota Association of Healthcare Organizations, Tennessee Hospital Association, Texas Department of State Health Services, Vermont Association of Hospitals and Health Systems, Virginia Health Information, Washington State Department of Health, and Wisconsin Department of Health Services.
Publisher Copyright:
© 2021 Health Research and Educational Trust
PY - 2021
Y1 - 2021
N2 - Objective: To reweight the Agency for Healthcare Research and Quality Patient Safety for Selected Indicators Composite (Patient Safety Indicator [PSI] 90) from weights based solely on the frequency of component PSIs to those that incorporate excess harm reflecting patients' preferences for outcome-related health states. Data Sources: National administrative and claims data involving hospitalizations in nonfederal, nonrehabilitation, acute care hospitals. Study Design: We estimated the average excess aggregate harm associated with the occurrence of each component PSI using a cohort sample for each indicator based on denominator-eligible records. We used propensity scores to account for potential confounding in the risk models for each PSI and weighted observations to estimate the “average treatment effect in the treated” for those with the PSI event. We fit separate regression models for each harm outcome. Final PSI weights reflected both the disutilities and the frequencies of the harms. Data Collection/Extraction Methods: We estimated PSI frequencies from the 2012 Healthcare Cost and Utilization Project State Inpatient Databases with present on admission data and excess harms using 2012–2013 Centers for Medicare & Medicaid Services Medicare Fee-for-Service data. Principal Findings: Including harms in the weighting scheme changed individual component weights from the original frequency-based weighting. In the reweighted composite, PSIs 11 (“Postoperative Respiratory Failure”), 13 (“Postoperative Sepsis”), and 12 (“Perioperative Pulmonary Embolism or Deep Vein Thrombosis”) contributed the greatest harm, with weights of 29.7%, 21.1%, and 20.4%, respectively. Regarding reliability, the overall average hospital signal-to-noise ratio for the reweighted PSI 90 was 0.7015. Regarding discrimination, among hospitals with greater than median volume, 34% had significantly better PSI 90 performance, and 41% had significantly worse performance than benchmark rates (based on percentiles). Conclusions: Reformulation of PSI 90 with harm-based weights is feasible and results in satisfactory reliability and discrimination, with a more clinically meaningful distribution of component weights.
AB - Objective: To reweight the Agency for Healthcare Research and Quality Patient Safety for Selected Indicators Composite (Patient Safety Indicator [PSI] 90) from weights based solely on the frequency of component PSIs to those that incorporate excess harm reflecting patients' preferences for outcome-related health states. Data Sources: National administrative and claims data involving hospitalizations in nonfederal, nonrehabilitation, acute care hospitals. Study Design: We estimated the average excess aggregate harm associated with the occurrence of each component PSI using a cohort sample for each indicator based on denominator-eligible records. We used propensity scores to account for potential confounding in the risk models for each PSI and weighted observations to estimate the “average treatment effect in the treated” for those with the PSI event. We fit separate regression models for each harm outcome. Final PSI weights reflected both the disutilities and the frequencies of the harms. Data Collection/Extraction Methods: We estimated PSI frequencies from the 2012 Healthcare Cost and Utilization Project State Inpatient Databases with present on admission data and excess harms using 2012–2013 Centers for Medicare & Medicaid Services Medicare Fee-for-Service data. Principal Findings: Including harms in the weighting scheme changed individual component weights from the original frequency-based weighting. In the reweighted composite, PSIs 11 (“Postoperative Respiratory Failure”), 13 (“Postoperative Sepsis”), and 12 (“Perioperative Pulmonary Embolism or Deep Vein Thrombosis”) contributed the greatest harm, with weights of 29.7%, 21.1%, and 20.4%, respectively. Regarding reliability, the overall average hospital signal-to-noise ratio for the reweighted PSI 90 was 0.7015. Regarding discrimination, among hospitals with greater than median volume, 34% had significantly better PSI 90 performance, and 41% had significantly worse performance than benchmark rates (based on percentiles). Conclusions: Reformulation of PSI 90 with harm-based weights is feasible and results in satisfactory reliability and discrimination, with a more clinically meaningful distribution of component weights.
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U2 - 10.1111/1475-6773.13918
DO - 10.1111/1475-6773.13918
M3 - Article
C2 - 34859429
AN - SCOPUS:85122641989
JO - Health Services Research
JF - Health Services Research
SN - 0017-9124
ER -