Feasibility of 30-day hospital readmission prediction modeling based on health information exchange data.

Journal: International journal of medical informatics
Published Date:

Abstract

INTRODUCTION: Unplanned 30-day hospital readmission account for roughly $17 billion in annual Medicare spending. Many factors contribute to unplanned hospital readmissions and multiple models have been developed over the years to predict them. Most researchers have used insurance claims or administrative data to train and operationalize their Readmission Risk Prediction Models (RRPMs). Some RRPM developers have also used electronic health records data; however, using health informatics exchange data has been uncommon among such predictive models and can be beneficial in its ability to provide real-time alerts to providers at the point of care.

Authors

  • Matthew J Swain
    U.S. Department of Health and Human Services, United States. Electronic address: swain.matthew@gmail.com.
  • Hadi Kharrazi
    Johns Hopkins Bloomberg School of Public Health, Center for Population Health Information Technology, Baltimore, United States.