Risk Factors for 30-Day Readmission for Pancreatitis in the National Readmission Database (NRD)

Abstract

Introduction: Thirty-day readmissions have become a focus for cost reduction for select clinical conditions. In addition, early readmission has been an identified risk factor for mortality in acute pancreatitis. Our aim was to utilize the novel National Readmission Database (NRD) to determine the risk factors for 30-day readmission in patients with pancreatitis and evaluate the predictive ability of the created model. Methods: We utilized the Healthcare Cost and Utilization Project's (HCUP) 2013 and 2014 NRD. Index admissions had either a primary or secondary diagnosis of pancreatitis (ICD-9: 577, 577.0). Patients with an index admission death and those with an index admission in the month of December were excluded. The primary outcome of interest was risk factors for 30-day readmission. Data was analyzed using Student's t-test and stepwise, backward multivariate logistic regression analysis. Results: We identified 93,641 (2013) and 98,579 (2014) index admissions with pancreatitis. The average patient age was 52.3 years with an average of 4.5 chronic conditions per patient in the combined data set. The average length of stay (LOS) of the index hospitalization was 4.8 days and average cost was $ 40167.76. Utilizing the 2013 data set, within 30 days, 11,659 (12.5%) readmissions were identified. Twenty-four variables were included in the final multivariate model to include: Medicaid insurance (OR 1.45, 95% CI 1.36 - 1.55), malnutrition (OR 1.33, 95% CI 1.24 - 1.43), congestive heart failure (OR 1.33, 95% CI 1.23 - 1.45) and active malignancy (OR 1.89, 95% CI 1.67 - 2.12). Protective risk factors included: obesity (OR 0.89, 95% CI 0.84 - 0.94), alcohol use (OR 0.94, 95% CI 0.89 - 0.99) and the performance of a cholecystectomy (OR 0.46, 95% CI 0.43 - 0.5). The final multivariate model had an area under the curve (AUROC) of 0.631 (95% CI 0.626-0.636). Validation of the model utilizing 2014 data demonstrated a similar AUROC of 0.633 (95% CI 0.628-0.639, P=0.518). Conclusion: Utilizing a cross-sectional nationally available dataset we were able to identify plausible readmission risk factors among patients with pancreatitis that is replicated across data sets. However, the predictive ability of the final model limits the application of the model and dataset. Further study utilizing factors outside of discharge diagnosis codes is required in order to create validated predictive models.