Workload Management in Telemedical Physician Triage and Other Knowledge-Based Service Systems
Workload Management in Telemedical Physician Triage and Other Knowledge-Based Service Systems
复制标题
DOI：
10.1287/mnsc.2017.2905
复制
发表时间：
2018-11-01
影响因子：
5.4
通讯作者：
Diermeier, Daniel
中科院分区：
文献类型：
--
作者：
Saghafian, Soroush;Hopp, Wallace J.;Diermeier, Daniel
远程医疗医生分诊（TPT）是分层知识服务系统（HKBSS）的一个示例，其中第二级决策代理（远程医疗医生）对初级代理（分诊护士）转介给他或她的病例做出决定。在这样的系统中管理速度与质量的权衡提出了一个独特的挑战，因为代理知识和两个级别之间的工作流之间的相互作用。我们开发了一种新的代理知识模型，基于贝塔分布，并将其部署在一个部分可观察的马尔可夫决策过程模型来描述最佳的政策，用于决定哪些情况下（患者）指的是第二个层次的进一步评估。我们发现，这种政策有一个单调的控制限制结构，减少了工作量的增加，在上层决策的比例。由于最优策略是复杂的，我们使用它的结构性见解来设计两个实用的策略。这些策略使HKBSS能够有效地适应工作量的变化，通过调整的标准，将决策提交给上层的部分实时队列长度信息的基础上。最后，我们进行分析和数值分析，以获得洞察到TPT系统的管理。我们发现：（1）随着急诊室等候区的拥挤程度增加，远程医疗医生应该评估更多的患者;（2）提高医生和/或护士准确性的培训可能是有效的，即使它只对单一患者类型有效，但提高一致性的培训必须对所有患者类型有效;及（3）除病人本身的健康状况外，病人分类时亦应考虑环境及手术情况。
Telemedical physician triage (TPT) is an example of a hierarchical knowledge-based service system (HKBSS) in which a second level of decision agent (telemedical physician) renders a decision on cases referred to him or her by the primary level agents (triage nurses). Managing the speed-versus-quality trade-off in such systems presents a unique challenge because of the interplay between agent knowledge and flow of work between the two levels. We develop a novel model of agent knowledge, based on the beta distribution, and deploy it in a partially observable Markov decision process model to describe the optimal policy for deciding which cases (patients) to refer to the second level for further evaluation. We show that this policy has a monotone control-limit structure that reduces the fraction of decisions made at the upper level as workload increases. Because the optimal policy is complex, we use structural insights from it to design two practical heuristics. These heuristics enable an HKBSS to adapt efficiently to workload shifts by adjusting the criteria for referring decisions to the upper level based on partial real-time queue length information. Finally, we conduct analytic and numerical analyses to derive insights into the management of a TPT system. We find that (1) the telemedical physician should evaluate more patients as congestion in the emergency room waiting area increases; (2) training that improves accuracy of the physician and/or nurses can be effective even if it only does so for a single patient type, but training that improves consistency must do so for all patient types to be effective; and (3) patient classification in triage should consider environmental and operational conditions in addition to the patient's medical condition.