用于改进医疗保健数据管理和组织绩效的分析框架

Yeneneh Tamirat Negash , Faradilah Hanum
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引用次数: 0

摘要

数字医疗保健依赖于准确、互联的数据来提供安全、高效的患者护理。然而,分散的管理系统造成了数据孤岛,限制了互操作性,并延迟了临床和行政决策。这些情况阻碍了个性化、协调和高效护理的实现。智能产品服务系统(Smart PSS)集成了智能产品、数字平台和增值服务,从而提供了增强数据管理和改善患者护理的途径。先前的研究很少确定或联系影响医疗数据管理和组织绩效的特定智能PSS属性,特别是从因果关系的角度来看。本研究通过开发用于改进医疗保健数据管理和组织绩效的分析框架来填补这一空白。一篇文献综述产生了47个候选属性。33位医疗专家通过模糊德尔菲法验证了27个属性。然后,模糊决策试验与评价实验室绘制了被验证属性及其相关方面之间的因果结构。智能产品、利益相关者协作和服务实现成为影响数据管理和组织绩效的核心因果方面。智能维修、监测和预警、同步交易、信息集成、数据质量和组织就绪度被列为最具影响力的实践标准。通过对这些标准进行优先排序,医疗保健管理人员可以减少数据碎片并改善服务结果。该研究为推进数字医疗的机构提供了分层智能PSS框架和管理指导。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An analytical framework for improving healthcare data management and organizational performance
Digital healthcare relies on accurate, connected data to deliver safe and efficient patient care. Yet, fragmented management systems create data silos, limit interoperability, and delay clinical and administrative decisions. These conditions impede the promise of personalized, coordinated, and efficient care. Smart Product Service Systems (Smart PSS) integrate intelligent products, digital platforms, and value-added services, thereby providing a pathway to enhanced data management and improved patient care. Prior studies seldom identify or link the specific Smart PSS attributes that shape healthcare data management and organizational performance, particularly from a causal perspective. This study fills that gap by developing an analytical framework for improving healthcare data management and organizational performance. A literature review produced 47 candidate attributes. Thirty-three healthcare experts validated 27 attributes through the Fuzzy Delphi Method. Fuzzy Decision-Making Trial and Evaluation Laboratory then mapped the causal structure among the validated attributes and their associated aspects. Intelligent products, stakeholder collaboration, and service realization emerged as core causal aspects that influence data management and organizational performance. Smart repair, monitoring and early warning, synchronized transactions, information integration, data quality, and organizational readiness ranked as the most influential criteria for practice. By prioritizing these criteria, healthcare managers reduce data fragmentation and improve service outcomes. The study provides a hierarchical Smart PSS framework and managerial guidance for institutions advancing digital healthcare.
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来源期刊
Healthcare analytics (New York, N.Y.)
Healthcare analytics (New York, N.Y.) Applied Mathematics, Modelling and Simulation, Nursing and Health Professions (General)
CiteScore
4.40
自引率
0.00%
发文量
0
审稿时长
79 days
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