Prescriptive analytics for reducing 30-day hospital readmissions after general surgery.

ABSTRACT:

Introduction

New financial incentives, such as reduced Medicare reimbursements, have led hospitals to closely monitor their readmission rates and initiate efforts aimed at reducing them. In this context, many surgical departments participate in the American College of Surgeons National Surgical Quality Improvement Program (NSQIP), which collects detailed demographic, laboratory, clinical, procedure and perioperative occurrence data. The availability of such data enables the development of data science methods which predict readmissions and, as done in this paper, offer specific recommendations aimed at preventing readmissions.

Materials and methods

This study leverages NSQIP data for 722,101 surgeries to develop predictive and prescriptive models, predicting readmissions and

SUBMITTER: Bertsimas D 

PROVIDER: S-EPMC7480861 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature