Coordination Control for Hospital Referral With Multitype Patients

Service coordination among hospitals is a crucial strategy to improving care outcomes and operational efficiency of healthcare delivery systems. This article proposes a referral cooperation system where patients can be referred from one upper-level hospital (ULH) to one lower-level hospital (LLH) for services provided in both types of hospitals with similar service qualities. For multitype patients with different disease conditions, a method for determining the types and quantities of patients that should be referred is explored based on ensuring the interests of the ULH and LLH simultaneously. This article proposes a threshold control method to address these issues along with the Pareto-based negotiation process to implement referral. The control decisions of both ULH and LLH can be achieved by the developed Pareto optimization based on particle swarm optimization-optimal computing budget allocation (POPSO-OCBA) simulation optimization method. To implement the threshold control easily, we further propose a simplified referral control method and conclude that when the flow variability is small, the method can approach similar effects as the previously proposed control while significantly reducing the administrative costs. The methodologies are studied using numerical investigation and a real case exploration in Shanghai. The results show that the methodologies are effective in helping to make the decisions in practice.
Note to Practitioners
—Under the tide of the sharing economy, healthcare providers are more ready to coordinate on delivering integrated care to patients, especially on care transition operations. With the government’s promotion of hospital alliances, hospitals should pay increasing attention to dynamic care transition control at the operational level to ensure better quality of service. This article investigates an easily implementable threshold control policy for patient referral coordination, which is expected to aid hospitals in dealing with imbalanced resource utilization to share service requests based on their respective resource availability. More importantly, we expect that the derived Pareto frontier of control thresholds can help the hospitals with the presentation of quantitative evidence for facilitating the negotiation on the control agreement of patient referral coordination. At the same time, the control-based methodology proposed can help hospitals to make decisions on their implementation strategy. A case study on negotiating the control agreement between a representative urban-area comprehensive hospital and its partner is provided in this article. We emphasize the importance of applying system engineering and mathematical modeling to study the referral cooperation system and real-time patient control decisions through our analyses.