医生绩效评分用于预测急诊室入院人数和过度入院负担
Andy Eyre1, Gideon Y Stein2,3, Jacob Chen4
1Respiratory Medicine, Meir Medical Center, Kfar Saba, Israel andyeyre@gmail.com.
BMJ health & care informatics
|September 17, 2024
概括
预测住院人数对于管理过度拥挤至关重要. 这项研究表明,结合医生绩效指标可显著提高预测模型的准确性,用于急诊室的到来和入院.
科学领域:
- 医疗保健管理的管理
- 医疗信息学 医疗信息学
- 医院运营 医院运营
背景情况:
- 医院过度拥挤是与不良事件有关的重要问题.
- 紧急部门 (ED) 的决策有助于过度拥挤.
- 个体医生的表现会影响入院率,但在预测模型中往往无法衡量.
研究的目的:
- 开发预测模型,用于每天的急救部门 (ED) 抵达和入院号码.
- 将个人员工绩效的客观指标纳入这些模型中.
- 加强劳动力规划和干预措施,以减少过度拥挤.
主要方法:
- 利用了从2016年到2021年期间232,245名ED出勤者的数据库.
- 开发了统计模型,包括医生绩效指标,历史病例和其他变量.
- 专注于预测ED到达和入院人数.
主要成果:
- 模型实现了6.85%的平均绝对百分比误差 (MAPE) 对于到达号码和10.6%的录取号码.
- 同一天,针对高吸收负担的警报系统显示了75%的灵敏度,虚假阳性率为20%.
- 包括医生绩效指标在内,显著提高了模型的准确性.
结论:
- 预测ED到达和入院的预测模型具有足够的干预准确性.
- 干预措施可以有效地减少过多的入院并改善患者流动.
- 个人工作人员的表现是准确的招生号码建模的关键,有影响力的变量.
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