{"title":"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","authors":"Teshager Worku, Seffi Gebeyehu, Amare Lakew","doi":"10.1002/isd2.70030","DOIUrl":null,"url":null,"abstract":"<div>\n \n <p>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 (<i>n</i> = 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.</p>\n </div>","PeriodicalId":46610,"journal":{"name":"Electronic Journal of Information Systems in Developing Countries","volume":"91 5","pages":""},"PeriodicalIF":1.4000,"publicationDate":"2025-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Agent-Based Referral Decision Support Framework for Medical Services Identification: A Design Science Approach\",\"authors\":\"Teshager Worku, Seffi Gebeyehu, Amare Lakew\",\"doi\":\"10.1002/isd2.70030\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div>\\n \\n <p>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 (<i>n</i> = 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.</p>\\n </div>\",\"PeriodicalId\":46610,\"journal\":{\"name\":\"Electronic Journal of Information Systems in Developing Countries\",\"volume\":\"91 5\",\"pages\":\"\"},\"PeriodicalIF\":1.4000,\"publicationDate\":\"2025-08-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Electronic Journal of Information Systems in Developing Countries\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1002/isd2.70030\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"SOCIAL SCIENCES, INTERDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Electronic Journal of Information Systems in Developing Countries","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/isd2.70030","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"SOCIAL SCIENCES, INTERDISCIPLINARY","Score":null,"Total":0}
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.