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急诊入院预测风险分层模型:实施后果评估(PRISMATIC 2):一项混合方法研究的方案

Emergency admission Predictive RIsk Stratification Models: Assessment of Implementation Consequences (PRISMATIC 2): a protocol for a mixed-methods study.

作者信息

Kingston Mark, Snooks Helen, Watkins Alan, Burton Christopher, Dale Jeremy, Davies Jan, Dearden Alex, Evans Bridie, Santos Gomes Bárbara, Jones Jenna, Kumar Rashmi, Porter Alison, Sewell Bernadette, Wallace Emma

机构信息

Swansea University Medical School, Swansea University, Swansea, UK

Swansea University Medical School, Swansea University, Swansea, UK.

出版信息

BJGP Open. 2025 Apr 24;9(1). doi: 10.3399/BJGPO.2024.0182. Print 2025 Apr.

DOI:10.3399/BJGPO.2024.0182
PMID:39284620
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12138022/
Abstract

BACKGROUND

Emergency admissions are costly, increasingly numerous, and associated with adverse patient outcomes. Policy responses have included the widespread introduction of emergency admission risk stratification (EARS) tools in primary care. These tools generate scores that predict patients' risk of emergency hospital admission and can be used to support targeted approaches to improve care and reduce admissions. However, the impact of EARS is poorly understood and there may be unintended consequences.

AIM

To assess effects, mechanisms, costs, and patient and healthcare professionals' views related to the introduction of EARS tools in England.

DESIGN & SETTING: Quasi-experimental mixed-methods design using anonymised routine data and qualitative methods.

METHOD

We will apply multiple interrupted time-series analysis to data, aggregated at former clinical commissioning group (CCG) level, to look at changes in emergency admission and other healthcare use following EARS introduction across England. We will investigate GP decision making at practice level using linked general practice and secondary care data to compare case-mix, demographics, indicators of condition severity, and frailty associated with emergency admissions before and after EARS introduction. We will undertake interviews (approximately 48) with GPs and healthcare staff to understand how patient care may have changed. We will conduct focus groups ( = 2) and interviews (approximately 16) with patients to explore how they perceive that communication of individual risk scores might affect their experiences and health-seeking behaviours.

CONCLUSION

Findings will provide policymakers, healthcare professionals, and patients, with a better understanding of the effects, costs, and stakeholder perspectives related to the introduction of EARS tools.

摘要

背景

急诊入院成本高昂,数量日益增多,且与不良患者预后相关。政策应对措施包括在初级医疗中广泛引入急诊入院风险分层(EARS)工具。这些工具生成预测患者急诊入院风险的分数,可用于支持有针对性的方法来改善护理并减少入院人数。然而,EARS的影响尚不清楚,可能会产生意想不到的后果。

目的

评估与在英格兰引入EARS工具相关的效果、机制、成本以及患者和医疗保健专业人员的看法。

设计与设置

采用匿名常规数据和定性方法的准实验混合方法设计。

方法

我们将对以前临床委托小组(CCG)层面汇总的数据应用多重中断时间序列分析,以观察在英格兰引入EARS后急诊入院和其他医疗保健使用情况的变化。我们将使用关联的全科医疗和二级医疗数据在实践层面调查全科医生的决策制定情况,以比较EARS引入前后与急诊入院相关的病例组合、人口统计学特征、病情严重程度指标和虚弱程度。我们将对全科医生和医护人员进行访谈(约48次)以了解患者护理可能如何发生变化。我们将开展焦点小组讨论(=2次)并对患者进行访谈(约16次)以探讨他们认为个人风险评分的沟通可能如何影响他们的就医体验和就医行为。

结论

研究结果将使政策制定者、医疗保健专业人员和患者更好地了解与引入EARS工具相关的效果、成本和利益相关者的观点。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7308/12138022/146699d8d750/bjgpopen-9-0182-f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7308/12138022/146699d8d750/bjgpopen-9-0182-f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7308/12138022/146699d8d750/bjgpopen-9-0182-f1.jpg

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本文引用的文献

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Implementing emergency admission risk prediction in general practice: a qualitative study.在全科医疗中实施紧急入院风险预测:一项定性研究。
Br J Gen Pract. 2022 Jan 27;72(715):e138-e147. doi: 10.3399/BJGP.2021.0146. Print 2022 Feb.
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Patterns of emergency admissions for ambulatory care sensitive conditions: a spatial cross-sectional analysis of observational data.门诊护理敏感型疾病的急诊入院模式:观察性数据的空间横断面分析
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