Prediction of 1 and 2 week nonelective hospitalization and sepsis hospitalization risk in adults

IF 15.1 1区 医学 Q1 HEALTH CARE SCIENCES & SERVICES NPJ Digital Medicine Pub Date : 2025-04-07 DOI:10.1038/s41746-025-01574-6
Vincent X. Liu, Gabriel J. Escobar, Liam O’Suilleabhain, Khanh K. Thai, David Schlessinger, Laura C. Myers, John D. Greene, Fernando Barreda, Lawrence D. Gerstley, Patricia Kipnis
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Abstract

We developed and validated models to predict 1- and 2-week risk of non-elective hospitalization (NEH) and sepsis hospitalization following outpatient clinic, emergency department treat and release (EDTR), or hospitalization encounters. We employed data from 4,488,579 adults with 1,481,430 hospital, 6,035,296 EDTR, and 86,013,893 clinic encounters. Predictors included administrative, clinical (laboratory tests, vital signs), utilization, and prescription pattern data. We employed 2012–2018 data for development and 2019 data for validation. In validation datasets, discrimination (area under the receiver operator characteristic curve) ranged from 0.687 for NEH within 1 week of hospital discharge to 0.904 for sepsis hospitalization within 2 weeks of clinic visits. At a sensitivity of 40%, numbers needed to evaluate (NNE) ranged from 4.3 for NEH within 2 weeks of hospitalization to 45 for sepsis hospitalization within 1 week of a clinic visit. Our models have potentially clinically actionable NNEs and could support clinical programs for the prevention of short-term hospitalizations and sepsis.

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成人1和2周非选择性住院和败血症住院风险的预测
我们开发并验证了模型,以预测门诊、急诊科治疗和出院(EDTR)或住院治疗后1周和2周非选择性住院(NEH)和败血症住院的风险。我们采用了来自1,481,430家医院、6,035,296家EDTR和86,013,893家诊所的4,488,579名成年人的数据。预测因素包括行政管理、临床(实验室检查、生命体征)、用药和处方模式数据。我们使用2012-2018年的数据进行开发,2019年的数据进行验证。在验证数据集中,鉴别(接受者操作者特征曲线下的面积)范围从出院1周内NEH的0.687到就诊2周内败血症住院的0.904。在40%的敏感性下,需要评估的数字(NNE)范围从NEH住院2周内的4.3到败血症住院1周内的45。我们的模型具有潜在的临床可操作的NNEs,可以支持预防短期住院和败血症的临床计划。
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来源期刊
CiteScore
25.10
自引率
3.30%
发文量
170
审稿时长
15 weeks
期刊介绍: npj Digital Medicine is an online open-access journal that focuses on publishing peer-reviewed research in the field of digital medicine. The journal covers various aspects of digital medicine, including the application and implementation of digital and mobile technologies in clinical settings, virtual healthcare, and the use of artificial intelligence and informatics. The primary goal of the journal is to support innovation and the advancement of healthcare through the integration of new digital and mobile technologies. When determining if a manuscript is suitable for publication, the journal considers four important criteria: novelty, clinical relevance, scientific rigor, and digital innovation.
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