Care Strategies for Reducing Hospital Readmissions Using Stochastic Programming

A hospital readmission occurs when a patient has an unplanned admission to a hospital within a specific time period of discharge from an earlier or initial hospital stay. Preventable readmissions have turned into a critical challenge for the healthcare system globally, and hospitals seek care strate...

Full description

Saved in:
Bibliographic Details
Published in:Healthcare (Basel) 2021-07, Vol.9 (8), p.940
Main Authors: Lahijanian, Behshad, Alvarado, Michelle
Format: Article
Language:English
Subjects:
care strategy
Chronic obstructive pulmonary disease
Costs
Decision making
Design
Estimates
Fines & penalties
hospital readmission
Hospitalization
Hospitals
Machine learning
Medicaid
Medicare
Optimization
OR in health services
Patients
probabilistic constraints
Probability
scenario-based stochastic programming
Survival analysis
Systematic review
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:A hospital readmission occurs when a patient has an unplanned admission to a hospital within a specific time period of discharge from an earlier or initial hospital stay. Preventable readmissions have turned into a critical challenge for the healthcare system globally, and hospitals seek care strategies that reduce the readmission burden. Some countries have developed hospital readmission reduction policies, and in some cases, these policies impose financial penalties for hospitals with high readmission rates. Decision models are needed to help hospitals identify care strategies that avoid financial penalties, yet maintain balance among quality of care, the cost of care, and the hospital’s readmission reduction goals. We develop a multi-condition care strategy model to help hospitals prioritize treatment plans and allocate resources. The stochastic programming model has probabilistic constraints to control the expected readmission probability for a set of patients. The model determines which care strategies will be the most cost-effective and the extent to which resources should be allocated to those initiatives to reach the desired readmission reduction targets and maintain high quality of care. A sensitivity analysis was conducted to explore the value of the model for low- and high-performing hospitals and multiple health conditions. Model outputs are valuable to hospitals as they examine the expected cost of hitting its target and the expected improvement to its readmission rates.
ISSN:2227-9032
2227-9032
DOI:10.3390/healthcare9080940