开发和实施出生预测工具以优化COVID-19疫情期间产科护理资源:混合方法研究
Huibert-Jan Joosse1, Karin Jongsma2, Marcel Moes3
1Central Diagnostic Laboratory, University Medical Center Utrecht, University Utrecht, Heidelberglaan 100, Utrecht, 3584CX, The Netherlands, 31 88 755 0759.
通过使用区域数据预测出生人数,在COVID-19大流行期间改善了产科护理计划. 该工具加强了医疗保健提供者之间的沟通和协作,证明了管理不可预测的护理需求的价值.
科学领域:
- 医疗保健管理
- 公共卫生
- 医疗信息学
背景情况:
- 有效的医疗资源分配至关重要,特别是在流行病期间和产科等不可预测需求的服务.
- 预测工具可以帮助管理医疗保健机构的稀缺资源.
研究的目的:
- 在COVID-19大流行期间,为乌得勒支地区的产科人员规划开发,验证和实施区域出生预测工具.
- 评估预测工具对医疗保健提供者的沟通和协作的影响.
主要方法:
- 综合区域实验室预测的出生日期与国家围产阶段登记和统计数据用于模型开发.
- 创建并实施基于HTML的预测工具,可视化预测出生.
- 在实施六个月后通过利益相关者会议评估该工具的影响.
主要成果:
- 预测准确度 (R) 为每3周的出生预测达到0.67.
- 实施的2周预测工具改善了医疗保健提供者之间的沟通,护理需求意识和协作.
- 利益相关者发现了其他应用,包括患者沟通和员工培训.
结论:
- 实施出生预测工具提供了对护理需求的有价值的见解,提高了产科护理的沟通和协作.
- 进一步的研究应侧重于改善数据共享,以加强区域产科急症护理需求预测.
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