Novel Approaches to Global Benchmarking of Risk-Adjusted Surgical Outcomes

dc.contributor.advisorPanieri, Eugenio
dc.contributor.authorSpence, Richard Trafford
dc.date.accessioned2019-02-18T11:29:22Z
dc.date.available2019-02-18T11:29:22Z
dc.date.issued2018
dc.date.updated2019-02-15T08:24:44Z
dc.description.abstractBackground Despite the existence of multiple validated risk-assessment and quality benchmarking tools in surgery, their utility outside of High Income Countries is limited. We sought to derive, validate and apply a scoring system that is both 1) feasible, and 2) reliably predicts mortality in a Middle Income Country (MIC) context. Methods A 5-step methodology was used: 1. Development of a de novo surgical outcomes database modeled around the American College of Surgeons’ National Surgical Quality Improvement Program (ACS-NSQIP) in South Africa (SA Dataset) 2. Use of the resultant data to identify all predictors of in-hospital death with more than 90% capture indicating feasibility of collection 3. Use these predictors to derive and validate an integer-based score that reliably predicts in-hospital death in the 2012 ACS-NSQIP 4. Apply the score in the original SA dataset and demonstrate it’s performance 5. Identify threshold cutoffs of the score to prompt action and drive quality improvement. Results Following Step one-three above, the 13 point Codman’s score was derived and validated on 211,737 and 109,079 patients, respectively, and includes: 1) age≥65 (1), partially or completely dependent functional status (1), preoperative transfusions≥4 units (1), emergency operation (2), sepsis or septic shock (2) American Society of Anesthesia (ASA) score ≥3 (3) and operative procedure (1-3). Application of the score to 373 patients in the SA dataset showed good discrimination and calibration to predict an inhospital death. A Codman Score of 8 is an optimal cutoff point for defining expected and unexpected deaths. Conclusion We have designed a novel risk prediction score specific for a MIC context. The Codman Score can prove useful for both 1) preoperative decision-making and 2) benchmarking the quality of surgical care in MIC’s.
dc.identifier.apacitationSpence, R. T. (2018). <i>Novel Approaches to Global Benchmarking of Risk-Adjusted Surgical Outcomes</i>. (). University of Cape Town ,Faculty of Health Sciences ,Department of Surgery. Retrieved from http://hdl.handle.net/11427/29635en_ZA
dc.identifier.chicagocitationSpence, Richard Trafford. <i>"Novel Approaches to Global Benchmarking of Risk-Adjusted Surgical Outcomes."</i> ., University of Cape Town ,Faculty of Health Sciences ,Department of Surgery, 2018. http://hdl.handle.net/11427/29635en_ZA
dc.identifier.citationSpence, R. 2018. Novel Approaches to Global Benchmarking of Risk-Adjusted Surgical Outcomes. University of Cape Town.en_ZA
dc.identifier.ris TY - Thesis / Dissertation AU - Spence, Richard Trafford AB - Background Despite the existence of multiple validated risk-assessment and quality benchmarking tools in surgery, their utility outside of High Income Countries is limited. We sought to derive, validate and apply a scoring system that is both 1) feasible, and 2) reliably predicts mortality in a Middle Income Country (MIC) context. Methods A 5-step methodology was used: 1. Development of a de novo surgical outcomes database modeled around the American College of Surgeons’ National Surgical Quality Improvement Program (ACS-NSQIP) in South Africa (SA Dataset) 2. Use of the resultant data to identify all predictors of in-hospital death with more than 90% capture indicating feasibility of collection 3. Use these predictors to derive and validate an integer-based score that reliably predicts in-hospital death in the 2012 ACS-NSQIP 4. Apply the score in the original SA dataset and demonstrate it’s performance 5. Identify threshold cutoffs of the score to prompt action and drive quality improvement. Results Following Step one-three above, the 13 point Codman’s score was derived and validated on 211,737 and 109,079 patients, respectively, and includes: 1) age≥65 (1), partially or completely dependent functional status (1), preoperative transfusions≥4 units (1), emergency operation (2), sepsis or septic shock (2) American Society of Anesthesia (ASA) score ≥3 (3) and operative procedure (1-3). Application of the score to 373 patients in the SA dataset showed good discrimination and calibration to predict an inhospital death. A Codman Score of 8 is an optimal cutoff point for defining expected and unexpected deaths. Conclusion We have designed a novel risk prediction score specific for a MIC context. The Codman Score can prove useful for both 1) preoperative decision-making and 2) benchmarking the quality of surgical care in MIC’s. DA - 2018 DB - OpenUCT DP - University of Cape Town LK - https://open.uct.ac.za PB - University of Cape Town PY - 2018 T1 - Novel Approaches to Global Benchmarking of Risk-Adjusted Surgical Outcomes TI - Novel Approaches to Global Benchmarking of Risk-Adjusted Surgical Outcomes UR - http://hdl.handle.net/11427/29635 ER - en_ZA
dc.identifier.urihttp://hdl.handle.net/11427/29635
dc.identifier.vancouvercitationSpence RT. Novel Approaches to Global Benchmarking of Risk-Adjusted Surgical Outcomes. []. University of Cape Town ,Faculty of Health Sciences ,Department of Surgery, 2018 [cited yyyy month dd]. Available from: http://hdl.handle.net/11427/29635en_ZA
dc.language.isoeng
dc.publisher.departmentDepartment of Surgery
dc.publisher.facultyFaculty of Health Sciences
dc.publisher.institutionUniversity of Cape Town
dc.subject.otherSurgery
dc.titleNovel Approaches to Global Benchmarking of Risk-Adjusted Surgical Outcomes
dc.typeMaster Thesis
dc.type.qualificationlevelMasters
dc.type.qualificationnameMMed
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