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苏格兰不同人口统计学特征人群急诊入院风险评分的差异行为——一项回顾性研究

Differential behaviour of a risk score for emergency hospital admission by demographics in Scotland-A retrospective study.

作者信息

Thoma Ioanna, Rogers Simon, Ireland Jillian, Porteous Rachel, Borland Katie, Vallejos Catalina A, Aslett Louis J M, Liley James

机构信息

Alan Turing Institute, London, United Kingdom.

MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, United Kingdom.

出版信息

PLOS Digit Health. 2024 Dec 17;3(12):e0000675. doi: 10.1371/journal.pdig.0000675. eCollection 2024 Dec.

DOI:10.1371/journal.pdig.0000675
PMID:39689107
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11651550/
Abstract

The Scottish Patients at Risk of Re-Admission and Admission (SPARRA) score predicts individual risk of emergency hospital admission for approximately 80% of the Scottish population. It was developed using routinely collected electronic health records, and is used by primary care practitioners to inform anticipatory care, particularly for individuals with high healthcare needs. We comprehensively assess the SPARRA score across population subgroups defined by age, sex, ethnicity, socioeconomic deprivation, and geographic location. For these subgroups, we consider differences in overall performance, score distribution, and false positive and negative rates, using causal methods to identify effects mediated through age, sex, and deprivation. We show that the score is well-calibrated across subgroups, but that rates of false positives and negatives vary widely, mediated by various causes including variability in demographic characteristics, admission reasons, and potentially differential data availability. Our work assists practitioners in the application and interpretation of the SPARRA score in population subgroups.

摘要

苏格兰再入院和入院风险(SPARRA)评分可预测约80%苏格兰人口的急诊入院个体风险。它是利用常规收集的电子健康记录开发的,初级保健从业者用其为预期护理提供信息,特别是针对医疗需求高的个体。我们全面评估了按年龄、性别、种族、社会经济剥夺程度和地理位置定义的人群亚组的SPARRA评分。对于这些亚组,我们考虑总体表现、评分分布以及假阳性和假阴性率的差异,使用因果方法来识别通过年龄、性别和剥夺程度介导的影响。我们表明,该评分在各亚组中校准良好,但假阳性和假阴性率差异很大,由多种原因介导,包括人口特征、入院原因的变异性以及潜在的不同数据可用性。我们的工作有助于从业者在人群亚组中应用和解释SPARRA评分。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0e92/11651550/4d18370c350d/pdig.0000675.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0e92/11651550/7932c33f018a/pdig.0000675.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0e92/11651550/9b6cb1fce486/pdig.0000675.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0e92/11651550/4d18370c350d/pdig.0000675.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0e92/11651550/7932c33f018a/pdig.0000675.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0e92/11651550/9b6cb1fce486/pdig.0000675.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0e92/11651550/4d18370c350d/pdig.0000675.g003.jpg

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本文引用的文献

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Measuring health inequalities: a systematic review of widely used indicators and topics.测量健康不平等:广泛使用的指标和主题的系统评价。
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Failure demand: a concept evaluation in UK primary care.失效需求:英国初级医疗保健中的概念评估
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Predicting the risk of emergency admission with machine learning: Development and validation using linked electronic health records.使用机器学习预测急诊入院风险:基于电子健康记录的开发和验证。
PLoS Med. 2018 Nov 20;15(11):e1002695. doi: 10.1371/journal.pmed.1002695. eCollection 2018 Nov.
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Possible Sources of Bias in Primary Care Electronic Health Record Data Use and Reuse.基层医疗电子健康记录数据使用与再利用中可能存在的偏差来源。
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Biases in electronic health record data due to processes within the healthcare system: retrospective observational study.由于医疗体系内的流程而导致电子健康记录数据出现偏差:回顾性观察性研究。
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