优化败血症的第一反应:基于电子健康记录的马尔可夫决策过程模型

IF 2.5 4区 管理学 Q3 MANAGEMENT
Erik T. Rosenstrom, Sareh Meshkinfam, J. Ivy, Shadi Hassani Goodarzi, M. Capan, J. Huddleston, S. Romero-Brufau
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引用次数: 4

摘要

脓毒症被认为是一种医疗紧急情况,其中初始治疗的延迟与发病率和死亡率的增加有关,但没有确定脓毒症发病和治疗时机的黄金标准。我们利用电子健康记录(EHR)数据和临床专业知识开发了一个连续时间马尔可夫决策过程(MDP)最佳停止模型,该模型确定了最佳的首次干预行动(抗感染、输液或等待)。为了研究初始治疗对有脓毒症发生风险的患者的影响,我们定义了延迟治疗人群,他们在入院或住院期间接受了延迟治疗,并作为脓毒症自然历史的近似。我们将最优的首次治疗策略应用于非延迟治疗人群的样本患者访问。该分析表明,与他们在医院接受的治疗相比,平均死亡风险可降低约2.2%,平均治疗时间可减少106分钟,治疗状态的平均严重程度可降低15.5%。我们研究了最优策略的特性,以定义一个易于解释的初始治疗启发式,该启发式考虑了患者的器官功能障碍,位置和感染性休克状态。这一可推广的框架可以为有败血症风险的患者提供个性化治疗。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Optimizing the First Response to Sepsis: An Electronic Health Record-Based Markov Decision Process Model
Sepsis is considered a medical emergency where delays in initial treatment are associated with increased morbidity and mortality, yet there is no gold standard for identifying sepsis onset and thus treatment timing. We leverage electronic health record (EHR) data with clinical expertise to develop a continuous-time Markov decision process (MDP) optimal stopping model that identifies the optimal first intervention action (anti-infective, fluid, or wait). To study the impact of initial treatment of patients at risk for developing sepsis, we define the delayed treatment population who received delayed treatment upon admission or during hospitalization and serves as an approximation of the natural history of sepsis. We apply the optimal first treatment policy to sample patient visits from the nondelayed treatment population. This analysis indicates the average risk of death could be reduced by approximately 2.2%, the average time until treatment could be reduced by 106 minutes, and the average severity of the treatment state could be reduced by 15.5% compared with the treatment they received in the hospital. We study the properties of the optimal policy to define an easily interpretable initial treatment heuristic that considers a patient’s organ dysfunction, location, and septic shock status. This generalizable framework can inform personalized treatment of patients at risk for sepsis.
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来源期刊
Decision Analysis
Decision Analysis MANAGEMENT-
CiteScore
3.10
自引率
21.10%
发文量
19
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