A. M. Jensen1, M. L. Crandall1, B. K. Yorkgitis1, J. H. Ra1 1University Of Florida,Department Of Surgery,Jacksonville, FL, USA
Introduction: There is a growing movement in today’s health care environment to not only tie reimbursements for patient care to outcomes, but to publicly report these results. Hospitals are looking for effective, simple methods to not only track patient outcomes, but to track outcomes that are risk-adjusted for patient population characteristics. This is especially relevant for safety net institutions servicing high-risk populations. One such program with the above goals is the American College of Surgeons National Surgical Quality Improvement Program® (ACS NSQIP®). NSQIP data powers a preoperative risk calculator tool that allows clinicians to input an individual patient’s risk factors into a statistical model that calculates the likelihood of various outcomes. This is an institution-based, retrospective quality audit whereby we determined the presence and consistency of charted data required to compute perioperative risk in the ACS NSQIP risk calculator.
Methods: A retrospective chart review of 30 randomly selected, elective major colorectal procedures was performed at an urban, academic safety net hospital between January 1st, 2015 and December 31st, 2015. For each case it was determined in a yes/no format whether or not the required NSQIP variables were readily presented via pre-operative documentation. The collected data was then analyzed to determine the presence and consistency of charted data required to compute perioperative risk in the ACS NSQIP risk calculator.
Results: Of the 30 reviewed patient charts, none (n=0) had all pre-operative risk documentation required to complete an ACS NSQIP risk analysis. Only 23.3% (n=7) of charts had ≥ 50% of required data, while 96.6% of charts (n=29) had ≤ 55% of required data to complete a NSQIP pre-operative risk assessment. It was noted that pre-operative risk variable documentation was found widely throughout patients’ charts in a largely non-uniform fashion, performed in varying degrees by multiple providers, and often lacked definitive documentation of pre-operative interventions to modulate risk based on patient risk factors.
Conclusion: Pre-operative risk assessment and charting practices at the safety net hospital reviewed was fragmented and often lacking the data needed to properly risk-assess patients in the pre-operative period. Even if risk was being assessed, there was lack of documentation required for outcomes assessments under current reimbursement models such as the MACRA Quality Payment Program. At safety net hospitals especially, where there are high-risk patients with often multiple comorbidities and socioeconomic barriers, we must implement means to consistently risk-stratify patients so that outcomes occurring correlate with pre-operative risks. Future research should be geared towards applicability and possible deficiencies of NSQIP in predicting postoperative complications in these safety net institutions.