为全科医生提供基于人工智能的临床决策支持系统的需求分析:以用户为中心的设计过程
Dania Schütze1, Svea Holtz2, Michaela C Neff3
1Goethe University Frankfurt, Institute of General Practice, Theodor-Stern-Kai 7, 60590, Frankfurt, Germany. schuetze@allgemeinmedizin.uni-frankfurt.de.
BMC medical informatics and decision making
|July 31, 2023
概括
一般医生 (GPs) 需要更好的工具来诊断不清楚的疾病. 这项研究确定了人工智能智能医生门户的关键用户要求,以提高德国全科医生的诊断准确性和效率.
科学领域:
- 医疗信息学 医疗信息学
- 医疗保健中的人工智能
- 初级医疗保健医学 一级医疗保健医学
背景情况:
- 一般医生 (GPs) 面临非特异性症状的挑战,导致诊断延迟.
- 临床决策支持系统 (CDSS) 为提高诊断准确性提供了一个潜在的解决方案.
- 该SATURN项目旨在开发一个针对德国全科医生量身定制的基于AI的诊断支持系统.
研究的目的:
- 为基于AI的诊断支持系统进行以用户为中心的需求分析.
- 为满足德国全科医生在诊断不明确疾病方面的特殊需求.
- 为开发一个用户友好和有效的智能医生门户提供信息.
主要方法:
- 代需求分析涉及五名全科医生.
- 采访以了解当前的诊断工作流程和数字工具的使用.
- 研讨会定义和优先考虑理想智能医生门户的功能,从而形成任务模型和用户要求.
主要成果:
- 确定了许多一般医生对数据输入,结果审查,沟通和转介流程的特定要求.
- 强调需要系统专注于非典型疾病模式,显示差异诊断概率,并确保透明度.
- 对同事沟通和直接传输电子健康记录数据的推功能.
结论:
- 来自开发初级保健诊断系统的基本用户要求.
- 这些要求将指导SATURN项目的模型开发和系统工程阶段.
- 该分析为创建符合全科医生的实际需求的诊断支持系统提供了基础.
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