# Optimizing Cooperative Community Hospital Selection for Post-Discharge Care with NSGA-II Algorithm

## TL;DR

This paper presents a new optimization framework using the NSGA-II algorithm to improve post-discharge care by selecting cooperative community hospitals.

## Contribution

The novel contribution is a multi-objective optimization model and NSGA-II-based heuristic for hospital collaboration in post-discharge care.

## Key findings

- The Pareto set reveals a knee region where moderate expansion of cooperating providers significantly improves accessibility.
- Further expansion yields limited gains but increases hospital costs.
- Cost-related parameters and follow-up frequencies are key drivers of the accessibility–cost trade-off.

## Abstract

Background: With the growing emphasis on full-process disease management, efficient post-discharge care has become increasingly critical. Although prior studies have examined follow-up services, resource allocation, and facility location in primary healthcare, model-based optimization of collaborative frameworks between comprehensive hospitals and primary care systems remains limited. Methods: We study a cooperative community hospital selection problem involving contractual cooperation, patient engagement, and follow-up resource allocation. A multi-objective mixed-integer programming model is developed to maximize patient accessibility and minimize total hospital costs, and an NSGA-II-based heuristic is proposed for solution generation. A real-world case study using data from a comprehensive hospital in Chengdu, China, is conducted. Results: The proposed approach produces a Pareto set that quantifies the accessibility–cost trade-off and reveals a knee region with diminishing returns: moderate expansion of cooperating providers substantially improves accessibility, whereas further expansion yields limited additional gains while increasing hospital cost. Sensitivity analyses indicate that cost-related parameters and follow-up frequencies are key drivers of the trade-off. Conclusions: The proposed optimization framework serves as an implementable decision aid for designing hospital–primary care collaboration for post-discharge follow-up: it supports partner selection and capacity planning and indicates levers to improve performance.