ACS NSQIP Surgical Risk Calculator: Pilot Analysis on Feasibility in an Academic Safety Net Hospital

• Published in: The Journal of surgical research 2019-04, Vol.236, p.124-128
• Main Authors: Jensen, A.M., Crandall, M.L., Tepas, J.J., Ra, J.H.
• Format: Article
• Language: English
• Subjects: ACS NSQIP; American College of Surgeons; Colon - surgery; Digestive System Surgical Procedures - adverse effects; Documentation of risk; Elective Surgical Procedures - adverse effects; Feasibility Studies; Humans; NSQIP; Outcome and Process Assessment, Health Care - methods; Outcomes; Performance evaluation; Perioperative Period - statistics & numerical data; Pilot Projects; Postoperative Complications - epidemiology; Postoperative Complications - etiology; Postoperative Complications - prevention & control; Quality; Quality Improvement; Rectum - surgery; Reproducibility of Results; Retrospective Studies; Risk Assessment - methods; Risk Factors; Safety-net hospitals; Safety-net Providers - organization & administration; Safety-net Providers - statistics & numerical data; Surgical risk assessment; United States - epidemiology
• ISSN: 0022-4804; 1095-8673
• DOI: 10.1016/j.jss.2018.11.012

Hospitals are looking for effective methods to track outcomes that are risk-adjusted for patient population characteristics. This is especially relevant for safety net hospitals (SNHs) servicing high-risk populations and in an era of quality-based reimbursement incentives. One such program with these goals is the American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP). This is an institution-based quality audit whereby we determined the presence and consistency of charted data required to compute perioperative risk in the ACS NSQIP risk calculator. A retrospective chart review of 28 elective colorectal procedures was performed at an urban, academic SNH over a 1-y period. For each case, it was determined whether the required NSQIP variables were readily presented via preoperative documentation. Univariate and bivariate statistics were employed to compare data field completion rates. Of the 28 reviewed patient charts, none (n = 0) had all preoperative risk documentation required to complete an ACS NSQIP risk analysis. 89.3% of charts (n = 25) had ≤ 55% of required data to complete a risk assessment. However on bivariate analysis, demographic variables were more likely to have been recorded (P