使用在线评论推动以人为本的护理:hcahps验证方法。

IF 1.8 Q3 HEALTH CARE SCIENCES & SERVICES
Journal of Patient Experience Pub Date : 2025-07-28 eCollection Date: 2025-01-01 DOI:10.1177/23743735251360471
Joseph G Taylor, Meghan P Leaver, Alex Griffiths
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引用次数: 0

摘要

以人为本的护理侧重于接受护理的个人的需要,并涉及患者和卫生专业人员之间的合作,以制定和监测护理。这项研究表明,在线患者评论提供了丰富、实时和详细的患者体验来源,可用于此目的。这项研究还表明,非结构化的在线数据可以使用机器学习和自然语言处理进行量化,以自动标记和评估患者的评论。我们描述了一种监督学习方法,在人工注释的患者评论的大型数据集上训练模型。我们报告的模型分数在预测总体得分方面的准确率为99%,在预测患者体验的七个领域(如有效治疗、快速获取和情感支持)的相关性方面的准确率为93%至99%。此外,我们在统计上显示了这些汇总的在线患者评论和HCAHPS星级评级之间的显著一致性——HCAHPS星级评级是美国医院护理质量的“金标准”衡量标准。这种方法能够在卫生系统之间建立基准,并评估干预措施对患者体验的影响,同时量化和加强以患者为中心的护理。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Using Online Reviews to Drive Person-Centered Care: An HCAHPS-Validated Approach.

Person-centered care focuses on the needs of the individual receiving care, and involves cooperation between patients and health professionals to develop and monitor care. This research demonstrates that online patient reviews provide a rich, real-time, and detailed source of patient experience that can be used for this purpose. This study also shows that unstructured online data can be quantified using machine learning and natural language processing to automatically flag and rate patient reviews. We describe a supervised learning approach, training a model on a large dataset of manually annotated patient reviews. We report model scores of 99% accuracy in predicting overall score, and 93% to 99% in predicting relevance to seven domains of patient experience, such as Effective Treatment, Fast Access, and Emotional Support. Furthermore, we show statistically significant alignment between these aggregated online patient reviews and HCAHPS star ratings-a "gold-standard" measure of care quality for hospitals in the United States. This approach enables benchmarking between health systems and evaluating the impact of interventions on patient experience, while quantifying and enhancing the patient-centeredness of care.

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来源期刊
Journal of Patient Experience
Journal of Patient Experience HEALTH CARE SCIENCES & SERVICES-
CiteScore
2.00
自引率
6.70%
发文量
178
审稿时长
15 weeks
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