常规医疗投诉的隐藏危险:揭露患者的伤害
Shaoting Luo1, Xueting Chen2, Xinyu Wen2
1Department of Pediatric Orthopedics, Shengjing Hospital of China Medical University, Shenyang, Liaoning, PR, 110004, China.
BMC health services research
|July 18, 2025
概括
一个新的预测模型可以有效地区分真正的患者伤害事件 (PHI) 和一般医疗投诉. 治疗选择和提供者行为等关键因素对于提高患者安全和预防伤害至关重要.
科学领域:
- 改善医疗保健质量 改善医疗保健质量
- 患者安全研究 患者安全研究
- 临床信息学 临床信息学
背景情况:
- 患者伤害事件 (PHI) 严重影响医疗保健质量和患者的治疗结果.
- 尽管医疗保健技术取得了进步,但预测和管理PHI仍然是一个持续的挑战.
- 区分真正的PHI与非有害的医疗投诉对于有针对性的干预至关重要.
研究的目的:
- 开发和验证一个预测模型,以区分真正的患者伤害事件 (PHI) 和其他医疗投诉.
- 确定与医疗保健环境中的患者伤害事件相关的关键预测因素.
- 为医疗保健机构提供一个工具,以便主动识别和减轻导致PHI的风险.
主要方法:
- 从2014年1月到2023年12月,对987起医疗投诉进行了回顾性分析.
- 使用最小绝对收缩和选择运算子 (LASSO) 回归的预测模型的开发.
- 通过分割样本方法和使用AUC,校准图表和决策曲线分析的性能评估进行验证.
主要成果:
- 该研究在987份医疗投诉中发现了361例PHI病例.
- PHI的主要预测因素包括治疗方法,医疗保健提供者的专业行为和投诉性质.
- 预测模型表现出高性能,AUC为0.917 (训练) 和0.904 (测试).
结论:
- 开发的预测模型显示了从服务投诉中识别患者伤害事件 (PHI) 的重大前景.
- 治疗决策和医疗保健提供者的行为被确定为影响患者安全的关键因素.
- 该模型的实施可以帮助医疗保健机构主动解决PHI的潜在原因.
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