Darwin Ang1, Mark McKenney2, Scott Norwood3, Stanley Kurek4, Brian Kimbrell5, Huazhi Liu6, Michele Ziglar6, James Hurst7. 1. Department of Surgery, University of South Florida, Tampa, Florida; Ocala Health System, Ocala, Florida. Electronic address: darwinang@usf.edu. 2. Department of Surgery, University of South Florida, Tampa, Florida; Kendall Regional Medical Center, Miami, Florida. 3. Department of Surgery, University of South Florida, Tampa, Florida; Bayonet Point Regional Medical Center, Hudson, Florida. 4. Department of Surgery, University of South Florida, Tampa, Florida; Lawnwood Medical Center, Fort Pierce, Florida. 5. Department of Surgery, University of South Florida, Tampa, Florida; Blake Medical Center, Bradenton, Florida. 6. Hospital Corporation of America, Nashville, Tennessee. 7. Department of Surgery, University of South Florida, Tampa, Florida.
Abstract
BACKGROUND: Improving clinical outcomes of trauma patients is a challenging problem at a statewide level, particularly if data from the state's registry are not publicly available. Promotion of optimal care throughout the state is not possible unless clinical benchmarks are available for comparison. Using publicly available administrative data from the State Department of Health and the Agency for Healthcare Research and Quality (AHRQ) patient safety indicators (PSIs), we sought to create a statewide method for benchmarking trauma mortality and at the same time also identifying a pattern of unique complications that have an independent influence on mortality. METHODS: Data for this study were obtained from State of Florida Agency for Health Care Administration. Adult trauma patients were identified as having International Classification of Disease ninth edition codes defined by the state. Multivariate logistic regression was used to create a predictive inpatient expected mortality model. The expected value of PSIs was created using the multivariate model and their beta coefficients provided by the AHRQ. Case-mix adjusted mortality results were reported as observed to expected (O/E) ratios to examine mortality, PSIs, failure to prevent complications, and failure to rescue from death. RESULTS: There were 50,596 trauma patients evaluated during the study period. The overall fit of the expected mortality model was very strong at a c-statistic of 0.93. Twelve of 25 trauma centers had O/E ratios <1 or better than expected. Nine statewide PSIs had failure to prevent O/E ratios higher than expected. Five statewide PSIs had failure to rescue O/E ratios higher than expected. The PSI that had the strongest influence on trauma mortality for the state was PSI no. 9 or perioperative hemorrhage or hematoma. Mortality could be further substratified by PSI complications at the hospital level. CONCLUSIONS: AHRQ PSIs can have an integral role in an adjusted benchmarking method that screens at risk trauma centers in the state for higher than expected mortality. Stratifying mortality based on failure to prevent PSIs may identify areas of needed improvement at a statewide level.
BACKGROUND: Improving clinical outcomes of traumapatients is a challenging problem at a statewide level, particularly if data from the state's registry are not publicly available. Promotion of optimal care throughout the state is not possible unless clinical benchmarks are available for comparison. Using publicly available administrative data from the State Department of Health and the Agency for Healthcare Research and Quality (AHRQ) patient safety indicators (PSIs), we sought to create a statewide method for benchmarking trauma mortality and at the same time also identifying a pattern of unique complications that have an independent influence on mortality. METHODS: Data for this study were obtained from State of Florida Agency for Health Care Administration. Adult traumapatients were identified as having International Classification of Disease ninth edition codes defined by the state. Multivariate logistic regression was used to create a predictive inpatient expected mortality model. The expected value of PSIs was created using the multivariate model and their beta coefficients provided by the AHRQ. Case-mix adjusted mortality results were reported as observed to expected (O/E) ratios to examine mortality, PSIs, failure to prevent complications, and failure to rescue from death. RESULTS: There were 50,596 traumapatients evaluated during the study period. The overall fit of the expected mortality model was very strong at a c-statistic of 0.93. Twelve of 25 trauma centers had O/E ratios <1 or better than expected. Nine statewide PSIs had failure to prevent O/E ratios higher than expected. Five statewide PSIs had failure to rescue O/E ratios higher than expected. The PSI that had the strongest influence on trauma mortality for the state was PSI no. 9 or perioperative hemorrhage or hematoma. Mortality could be further substratified by PSI complications at the hospital level. CONCLUSIONS: AHRQ PSIs can have an integral role in an adjusted benchmarking method that screens at risk trauma centers in the state for higher than expected mortality. Stratifying mortality based on failure to prevent PSIs may identify areas of needed improvement at a statewide level.
Authors: Ohad Ronen; K Thomas Robbins; Remco de Bree; Orlando Guntinas-Lichius; Dana M Hartl; Akihiro Homma; Avi Khafif; Luiz P Kowalski; Fernando López; Antti A Mäkitie; Wai Tong Ng; Alessandra Rinaldo; Juan P Rodrigo; Alvaro Sanabria; Alfio Ferlito Journal: Eur Arch Otorhinolaryngol Date: 2021-05-12 Impact factor: 2.503
Authors: Syed K Mehdi; Joseph E Tanenbaum; Vincent J Alentado; Jacob A Miller; Daniel Lubelski; Edward C Benzel; Thomas E Mroz Journal: Spine J Date: 2016-09-21 Impact factor: 4.166
Authors: Joseph E Tanenbaum; Jacob A Miller; Vincent J Alentado; Daniel Lubelski; Benjamin P Rosenbaum; Edward C Benzel; Thomas E Mroz Journal: Spine J Date: 2016-08-04 Impact factor: 4.166