Novel Approaches to Global Benchmarking of Risk-Adjusted Surgical Outcomes

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.

Grantor dc:publisher.institution

Department of Surgery

Year dc:date.issued

2018

Author dc:creator

• Spence, Richard Trafford

Advisor dc:contributor.advisor

• Panieri, Eugenio

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/11427/29635

OAI identifier oai:identifier

oai:open.uct.ac.za:11427/29635