Threshold Control Policy Optimization for Real-Time Reverse Referral Decision of Chinese Comprehensive Hospitals
Threshold Control Policy Optimization for Real-Time Reverse Referral Decision of Chinese Comprehensive Hospitals
复制标题
中国综合医院实时反向转诊决策的阈值控制策略优化
DOI：
10.1109/tase.2018.2842772
复制
发表时间：
2019-01-01
影响因子：
5.6
通讯作者：
Kong, Nan
中科院分区：
文献类型：
--
作者：
Li, Na;Teng, De;Kong, Nan
近年来，我国医院分级管理体制下医疗资源利用不均衡问题受到广泛关注。反向转诊作为一种促进患者从上级医院流向下级医院的措施，在缓解上级医院工作负担、平衡上级医院与下级医院资源利用方面具有优势。然而，如何在业务一级控制反向转诊的决定程序仍不清楚。在本文中，我们考虑了一个ULH主导的设置，LLH必须接受病人转介的ULH时，它有可用的病床。我们把注意力集中在一个易于实施的阈值政策，为ULH作出反向转介的决定。为了调查，我们首先制定了一个分析听话的模型，一个简化的反向推荐过程。然后，我们研究了一个更一般的病人流量控制模型，我们分析了病人的人口动态与马尔可夫链过程，并应用状态依赖马尔可夫到达过程的概念，以产生系统的无穷小生成器。我们使用RG分解来计算系统性能指标。接下来，我们制定了一个阈值优化问题的目标是最大限度地提高ULH利润。仿真实验表明，该门限控制策略对服务时间分布不敏感。最后，我们报告现实世界的启发数值研究，从中我们产生的见解，有效调整的控制阈值，以响应系统参数和讨论潜在的阻碍LLH不正确地通知其实时资源可用性的ULH。本文的工作是国内首次将系统工程应用于实时反向推荐决策问题。它提供了新的视角资源平衡的病人流控制研究的护理过渡管理文献。从业者注意-几乎所有卫生保健提供基础设施不足的国家都认识到，护理协调是提高卫生保健系统有效性、安全性和效率的关键战略。通过沟通/共享知识，多个护理组织共同努力，为患者制定积极主动的护理计划，以满足他们的需求和偏好，特别是处理护理的过渡。随着人口护理管理的推广，世界各地的从业人员越来越认识到患者流程简化，每个人群内的资源整合以及与社区护理资源的联系的重要性。然而，在医疗实践的日常工作中应用护理协调可能是压倒性的，即使很明显，这些变化将改善患者护理并提供效率。在本文中，我们探讨了一个易于实施的病人流量控制政策，使反向转诊决策的病人接受出院后护理。我们希望通过改善运营管理来提高供应商的利润。通过我们的分析，我们想强调的重要性，应用系统工程和数学建模研究护理协调和组织间的病人流量控制。我们还希望倡导知识共享和问责制的建立，因为不同层次的医院之间良好的伙伴关系可能非常依赖它们。
In recent years, imbalanced utilization of medical resources is widely concerned within the tiered Chinese hospital system. Reverse referral, as a measure of promoting patient flows from upper level hospitals (ULHs) to lower level hospitals (LLHs), has demonstrated its advantages on alleviating ULH workload and balancing resource utilization between ULHs and LLHs. Nevertheless, it remains unclear on how to control the reverse referral decision process at the operational level. In this paper, we consider an ULH-dominant setting at which the LLH must accept patient referrals from the ULH whenever it has available beds. We focus our attention on an easy-to-implement threshold policy for the ULH to make the reverse referral decision. To investigate, we first formulate an analytically tractable queueing model for a simplified reverse referral process. We then investigate a more general patient flow control model, for which we analyze the patient population dynamics with a Markov chain process, and apply the concept of state-dependent Markovian arrival process to generate an infinitesimal generator of the system. We use RG factorization to compute the system performance measures. We next formulate a threshold optimization problem with the objective of maximizing the ULH profit. Simulation experiments are performed, which conclude that the threshold control policy is insensitive to the service time distribution. Finally, we report real-world inspired numerical studies, from which we generate insights into effective adjustment of the control threshold in response to the system parameters and discuss potential hindrance from the LLH incorrectly informing its real-time resource availability to the ULH. Our work is the first that applies systems engineering to the real-time reverse referral decision problem in China. It provides the novel perspective of resource balancing to patient flow control studies in the care transition management literature. Note to Practitioners—It is recognized, in almost all countries with insufficient health care delivery infrastructure, that the care coordination is a key strategy to improve the effectiveness, safety, and efficiency of the health care system. Through communicating/sharing knowledge, multiple care organizations work together to create a proactive care plan for the patients to meet their needs and preferences, especially dealing with transitions of care. With the promotion of population care management, practitioners throughout the world have increasingly acknowledged the importance of patient flow streamlining, resource alignment within each population, and linking to community care resources from acute care facilities. However, applying care coordination in everyday routines of a medical practice can be overwhelming, even when it is obvious that the changes will improve patient care and provide efficiency. In this paper, we investigate an easy-to-implement patient flow control policy in making reverse referral decisions for patients receiving postdischarge care. We expect to improve provider’s profit with improved operational management. Through our analyses, we want to stress the importance of applying systems engineering and mathematical modeling to study care coordination and interorganization patient flow control. We also want to advocate knowledge sharing and accountability establishment, as a well-functioned partnership between hospitals at different tiers may very much rely on them.