Risk-adjusted mortality rates as a quality proxy outperform volume in surgical oncology

• Verfasst von: Baum, Philip [VerfasserIn]
• Verfasst von: Lenzi, Jacopo [VerfasserIn]
• Verfasst von: Diers, Johannes [VerfasserIn]
• Verfasst von: Rust, Christoph [VerfasserIn]
• Verfasst von: Eichhorn, Martin E. [VerfasserIn]
• Verfasst von: Taber, Samantha [VerfasserIn]
• Verfasst von: Germer, Christoph-Thomas [VerfasserIn]
• Verfasst von: Winter, Hauke [VerfasserIn]
• Verfasst von: Wiegering, Armin [VerfasserIn]
• Titel: Risk-adjusted mortality rates as a quality proxy outperform volume in surgical oncology
• Titelzusatz: a new perspective on hospital centralization using national population-based data
• Verf.angabe: Philip Baum, MD; Jacopo Lenzi, PhD; Johannes Diers, MD, MScPH; Christoph Rust, MSc; Martin E. Eichhorn, MD; Samantha Taber, MD; Christoph-Thomas Germer, MD; Hauke Winter, MD; and Armin Wiegering, MD
• E-Jahr: 2022
• Jahr: January 11, 2022
• Umfang: 11 S.
• Fussnoten: Gesehen am 16.02.2022
• Titel Quelle: Enthalten in: Journal of clinical oncology
• Ort Quelle: Alexandria, Va. : American Society of Clinical Oncology, 1983
• Jahr Quelle: 2022
• Band/Heft Quelle: 40(2022), 10, Seite 1041-1050
• ISSN Quelle: 1527-7755
• DOI: doi:10.1200/JCO.21.01488
• Datenträger: Online-Ressource
• Sprache: eng
• K10plus-PPN: 1789726123

Abstract

PURPOSE - - Despite a long-known association between annual hospital volume and outcome, little progress has been made in shifting high-risk surgery to safer hospitals. This study investigates whether the risk-standardized mortality rate (RSMR) could serve as a stronger proxy for surgical quality than volume. - - METHODS - - We included all patients who underwent complex oncologic surgeries in Germany between 2010 and 2018 for any of five major cancer types, splitting the data into training (2010-2015) and validation sets (2016-2018). For each surgical group, we calculated annual volume and RSMR quintiles in the training set and applied these thresholds to the validation set. We studied the overlap between the two systems, modeled a market exit of low-performing hospitals, and compared effectiveness and efficiency of volume- and RSMR-based rankings. We compared travel distance or time that would be required to reallocate patients to the nearest hospital with low-mortality ranking for the specific procedure. - - RESULTS - - Between 2016 and 2018, 158,079 patients were treated in 974 hospitals. At least 50% of high-volume hospitals were not ranked in the low-mortality group according to RSMR grouping. In an RSMR centralization model, an average of 32 patients undergoing complex oncologic surgery would need to relocate to a low-mortality hospital to save one life, whereas 47 would need to relocate to a high-volume hospital. Mean difference in travel times between the nearest hospital to the hospital that performed surgery ranged from 10 minutes for colorectal cancer to 24 minutes for pancreatic cancer. Centralization on the basis of RSMR compared with volume would ensure lower median travel times for all cancer types, and these times would be lower than those observed. - - CONCLUSION - - RSMR is a promising proxy for measuring surgical quality. It outperforms volume in effectiveness, efficiency, and hospital availability for patients.