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利用在线评论推动以患者为中心的护理:一种经医疗保健消费者评估和医疗服务提供者与系统消费者评估(HCAHPS)验证的方法。

Using Online Reviews to Drive Person-Centered Care: An HCAHPS-Validated Approach.

作者信息

Taylor Joseph G, Leaver Meghan P, Griffiths Alex

机构信息

PEP Health, London, UK.

出版信息

J Patient Exp. 2025 Jul 28;12:23743735251360471. doi: 10.1177/23743735251360471. eCollection 2025.

Abstract

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.

摘要

以患者为中心的护理关注接受护理的个体的需求,并涉及患者与医疗专业人员之间的合作,以制定和监督护理。这项研究表明,在线患者评价提供了丰富、实时且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评价。我们描述了一种监督学习方法,在一个人工标注的患者评价大型数据集上训练模型。我们报告该模型在预测总体评分时的准确率为99%,在预测与患者体验的七个领域(如有效治疗、快速就诊和情感支持)的相关性时的准确率为93%至99%。此外,我们表明这些汇总的在线患者评价与HCAHPS星级评级(美国医院护理质量的“黄金标准”衡量指标)之间存在统计学上的显著一致性。这种方法能够在医疗系统之间进行基准比较,并评估干预措施对患者体验的影响,同时量化并提高护理的以患者为中心程度。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4853/12304609/53f539aa5cd0/10.1177_23743735251360471-fig1.jpg

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