基于代理的医疗服务识别转诊决策支持框架:设计科学方法

IF 1.4 Q2 SOCIAL SCIENCES, INTERDISCIPLINARY
Teshager Worku, Seffi Gebeyehu, Amare Lakew
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引用次数: 0

摘要

尽管对低收入和中等收入国家(LMICs)的医疗保健给予了很大的重视,但转诊决策系统和连接各级医疗保健的接口研究不足。低收入和中等收入国家经常面临系统性效率低下的挑战,包括决策技能方面的差距、有限的自主权、与环境互动的能力差、解决问题的智力较低以及卫生机构之间的协作不足。通过开发灵活、动态、可靠和智能的决策支持系统,可以解决这种低效和多样化的内在复杂性。然而,在埃塞俄比亚的情况下,没有决策支持机制来帮助医生做出转诊决定。本研究旨在发展一个基于代理的决策支持框架,以支持临床医生在转诊后确定所需的服务。遵循设计科学方法,具有分层架构的自适应框架使不同临床输入参数的过程能够增强数据共享和基于证据的决策,同时保护数据隐私。通过为临床医生提供结构化支持和解决数据异质性,该框架减轻了复杂转诊过程中有限理性的局限性。为了评估目的,本研究进行了可用性评估框架(n = 12)。每个因素的可用性水平和建议的决策支持框架达到了优秀的水平(超过80%)。评估结果显示,用户似乎对该系统的印象是易于理解,高效使用,并提供了一个可管理的交互。本研究通过可用性测试验证了有限理性在医疗转诊框架中的实际应用,从而提高了向健康临床医生、医生和阿姆哈拉地区卫生局转诊的效率和质量,从而为理论和实践做出了贡献。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Agent-Based Referral Decision Support Framework for Medical Services Identification: A Design Science Approach

Even though much emphasis has been given to healthcare in low- and middle-income countries (LMICs), referral decision systems and the interfaces linking the various levels of healthcare have been under-researched. LMICs are often challenged with systemic inefficiencies, including a gap in decision-making skills, limited autonomy, poor ability to interact with the environment, lower intelligence in problem-solving, and poor collaboration between health institutions. Such intrinsic complexity of inefficiencies and diversity of care can be tackled by developing flexible, dynamic, reliable, and intelligent decision support systems. However, there is no decision support mechanism to aid physicians in making referral decisions in the Ethiopian context. This study aims to develop an agent-based decision support framework to support clinicians in identifying required services after referral is indicated. Following the design science approach, the adaptive framework with a layered architecture enables the process of diverse clinical input parameters to enhance data sharing and evidence-based decision-making while preserving data privacy. By providing clinicians with structured support and addressing data heterogeneity, the framework mitigates the limitations of bounded rationality in complex referral processes. For evaluation purposes, the study conducted a usability evaluation framework (n = 12). The usability level for each factor and the proposed decision support framework achieved an excellent level (above 80%). The evaluation result revealed that users seem to have the impression that the system is easy to understand, efficient to use, and offers a manageable interaction. This study contributes to both theory and practice by demonstrating the practical application of bounded rationality within a healthcare referral framework, validated through usability testing, leading to improved efficiency and quality of medical referrals to health clinicians, medical doctors, and the Amhara Region Health Bureau.

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来源期刊
CiteScore
3.60
自引率
15.40%
发文量
51
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