Abstract
BACKGROUND: Current preoperative risk assessment tools are often cumbersome, have limited accuracy, and are poorly adopted. The Care Assessment Need (CAN) score, an existing tool developed for primary care providers in the U.S. Veterans Administration health-care system (VA), is automatically calculated for individual patients using electronic health record data. Therefore, it could present an efficient preoperative risk assessment tool. The aim of this project was to determine if the CAN score can be repurposed as a preoperative risk assessment tool for patients undergoing total knee arthroplasty (TKA). METHODS: A multicenter retrospective observational study was conducted using national VA data from 2013 to 2016. The cohort included veterans who underwent TKA identified through ICD-9 (International Classification of Diseases, Ninth Revision), ICD-10, and CPT (Current Procedural Terminology) codes. The focus of the study was the preoperative patient CAN score, a single numerical value ranging from 0 to 99 (with a higher score representing greater risk) that is automatically calculated each week using multiple data points in the VA electronic health record. Study outcomes of interest were 90-day readmission, prolonged hospital stay (>5 days), 1-year mortality, and non-routine patient discharge. RESULTS: The study included 17,210 veterans. Their median preoperative CAN score was 75, although there was substantial variability in patient CAN scores among different facilities. A preoperative CAN score of >75 was significantly associated with mortality (odds ratio [OR] = 3.54), prolonged length of stay (OR = 1.97), 90-day readmission (OR = 1.65), and non-routine discharge (OR = 1.57). The CAN score had good accuracy with a receiver operating characteristic (ROC) curve value of >0.7 for all outcomes except 90-day readmission. CONCLUSIONS: The CAN score can be leveraged as an extremely efficient way to risk-stratify patients before TKA, with results that surpass other commonly available and labor-intensive alternatives. As a result, this simple and efficient solution is well positioned for broad adoption as a standardized decision support tool. LEVEL OF EVIDENCE: Prognostic Level IV. See Instructions for Authors for a complete description of levels of evidence.