公共医院过程管理和成熟度的评估:一个可解释的机器学习方法
Aziz Hantem1, Jamal Abdelfattah2, Zineb El Gabbas3
1MADILOG Laboratory, Ibn Zohr Univertsity, Agadir, Morocco.
概括
摩洛哥公共医院的流程管理成熟度较低,大学医院的表现优于其他医院. 改进的关键领域包括风险管理和合规控制,以及最高管理层参与改善医院绩效.
科学领域:
- 医疗保健管理的管理
- 过程改进 过程改进
- 医疗保健中的人工智能
背景情况:
- 医院在医疗保健系统中起着至关重要的作用,平衡医疗,学术和管理职能.
- 提高绩效和创新需求促使公共医院采用动态的管理实践.
- 本研究评估了摩洛哥公共医院 (MPH) 的流程管理成熟度,并确定了相关的组织因素.
研究的目的:
- 评估摩洛哥公共医院当前的流程管理成熟度水平.
- 确定与更高的过程成熟度相关的关键组织维度.
- 利用机器学习来理解和改进医院管理实践.
主要方法:
- 利用了业务流程定向成熟度模型 (BPOMM) 的七个关键轴.
- 通过问卷收集数据,分析了154个完整的答案.
- 应用后勤回归,随机森林和XGBoost,用SHAP解释以确定关键成熟度因素.
主要成果:
- 县和省级医院的成熟度水平低于2,而大学医院的成熟度超过2.
- 可解释AI (SHAP) 确定风险管理和合规控制 (RMCC) 和最高管理层参与 (ITMSA) 对于成熟度至关重要.
- 优化:行动计划和绩效测量 (OAPM) 以及社会经济和运营绩效 (SEOP) 也显示出重要意义.
结论:
- 现代化MPH面临的挑战是由于复杂性和日益增长的性能要求.
- 在大学医院和一级和二级医院之间存在很大的成熟差距.
- 可解释的机器学习有效地补充了MPH中的过程成熟度评估.
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