Cross-Site Predictions of Readmission After Psychiatric Hospitalization With Mood or Psychotic Disorders: Retrospective Study.

IF 5.8 2区 医学 Q1 PSYCHIATRY
Jmir Mental Health Pub Date : 2025-09-12 DOI:10.2196/71630
Boyu Ren, WonJin Yoon, Spencer Thomas, Guergana Savova, Timothy Miller, Mei-Hua Hall
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引用次数: 0

Abstract

Background: Patients with mood or psychotic disorders experience high rates of unplanned hospital readmissions. Predicting the likelihood of readmission can guide discharge decisions and optimize patient care.

Objective: The purpose of this study is to evaluate the predictive power of structured variables from electronic health records for all-cause readmission across multiple sites within the Mass General Brigham health system and to assess the transportability of prediction models between sites.

Methods: This retrospective, multisite study analyzed structured variables from electronic health records separately for each site to develop in-site prediction models. The transportability of these models was evaluated by applying them across different sites. Predictive performance was measured using the F1-score, and additional adjustments were made to account for differences in predictor distributions.

Results: The study found that the relevant predictors of readmission varied significantly across sites. For instance, length of stay was a strong predictor at only 3 of the 4 sites. In-site prediction models achieved an average F1-score of 0.661, whereas cross-site predictions resulted in a lower average F1-score of 0.616. Efforts to improve transportability by adjusting for differences in predictor distributions did not improve performance.

Conclusions: The findings indicate that individual site-specific models are necessary to achieve reliable prediction accuracy. Furthermore, the results suggest that the current set of predictors may be insufficient for cross-site model transportability, highlighting the need for more advanced predictor variables and predictive algorithms to gain robust insights into the factors influencing early psychiatric readmissions.

Abstract Image

Abstract Image

伴有情绪或精神障碍的精神病住院后再入院的跨中心预测:回顾性研究
背景:情绪或精神障碍患者的意外再入院率很高。预测再入院的可能性可以指导出院决策并优化患者护理。目的:本研究的目的是评估来自电子健康记录的结构化变量对麻省总医院布莱根卫生系统多个站点的全因再入院的预测能力,并评估预测模型在站点之间的可移植性。方法:这项回顾性的多站点研究分别分析了每个站点电子健康记录中的结构化变量,以建立站点内预测模型。通过在不同地点应用这些模型,评估了这些模型的可移植性。预测性能使用f1评分进行测量,并进行额外的调整以解释预测器分布的差异。结果:研究发现,不同地区再入院的相关预测因素差异显著。例如,在4个站点中,只有3个站点的停留时间是一个强有力的预测因素。站点内预测模型的平均f1得分为0.661,而跨站点预测模型的平均f1得分较低,为0.616。通过调整预测器分布的差异来提高可移植性的努力并没有提高性能。结论:研究结果表明,为了获得可靠的预测精度,个体特定位点模型是必要的。此外,研究结果表明,目前的预测变量集可能不足以实现跨站点模型的可移植性,因此需要更先进的预测变量和预测算法,以获得对影响早期精神病学再入院因素的可靠见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Jmir Mental Health
Jmir Mental Health Medicine-Psychiatry and Mental Health
CiteScore
10.80
自引率
3.80%
发文量
104
审稿时长
16 weeks
期刊介绍: JMIR Mental Health (JMH, ISSN 2368-7959) is a PubMed-indexed, peer-reviewed sister journal of JMIR, the leading eHealth journal (Impact Factor 2016: 5.175). JMIR Mental Health focusses on digital health and Internet interventions, technologies and electronic innovations (software and hardware) for mental health, addictions, online counselling and behaviour change. This includes formative evaluation and system descriptions, theoretical papers, review papers, viewpoint/vision papers, and rigorous evaluations.
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