The Surgical Risk Preoperative Assessment System: Determining which predictor variables can be automatically obtained from the electronic health record. Issue 6 (December 2019)

• Record Type: Journal Article
• Authors: Meguid, Robert A; Bronsert, Michael R; Hammermeister, Karl E; Kao, David P; Lambert-Kerzner, Anne; Sinex, Jacob A; Myers, Jody M; Henderson, William G
• Is Part Of: Journal of patient safety and risk management. Volume 24:Issue 6(2019)
• Page Start: 230
• Page End: 237
• Publication Date: 2019-12
• Subjects: Electronic health records -- health services research -- surgical outcomes -- clinical decision support; Medical jurisprudence -- Great Britain -- Periodicals; Medical personnel -- Malpractice -- Great Britain -- Periodicals; Risk management -- Great Britain -- Periodicals
• DOI: 10.1177/2516043519876489
• Languages: English
• ISSNs: 2516-0435

Abstract

Introduction: The Surgical Risk Preoperative Assessment System is a parsimonious, universal surgical risk calculator integrated into our local electronic health record. We determined how many of its eight preoperative risk predictor variables could be automatically obtained from the electronic health record. This has implications for the usability and adoption of Surgical Risk Preoperative Assessment System, serving as an example of use of electronic health record data for populating clinical decision support tools. Methods: We quantified the availability and accuracy in the electronic health record of the eight Surgical Risk Preoperative Assessment System predictor variables (patient age, American Society of Anesthesiology physical status classification, functional health status, sepsis, work Relative Value Unit, in-/outpatient operation, surgeon specialty, emergency status) at the patient's preoperative encounter of 5205 patients entered into the American College of Surgeons National Surgical Quality Improvement Program. Accuracy was determined by comparing the electronic health record data to the same patient's National Surgical Quality Improvement Program data, used as the "gold standard." Acceptable accuracy was defined as a Kappa statistic or Pearson correlation coefficient ≥0.8 when comparing electronic health record and National Surgical Quality Improvement Program data. Acceptable availability was defined as presence of the variable in the electronic health record at the preoperative encounter ≥95% of the time. Results: Of the eight predictor variables, six had acceptable accuracy. Only preoperative sepsis and functional health status had Kappa statistics <0.8. However, only patient age and surgeon specialty were ≥95% available in the electronic health record at the preoperative visit. Conclusions: Processes need to be developed to populate more of the Surgical Risk Preoperative Assessment System preoperative predictor variables in the patient's electronic health record prior to the preoperative visit to lessen the burden on the busy surgeon and encourage more widespread use of Surgical Risk Preoperative Assessment System.