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利用电子健康记录在英国初级保健中量化和分层 2 型糖尿病的严重程度:原理和队列研究设计。

Using electronic health records to quantify and stratify the severity of type 2 diabetes in primary care in England: rationale and cohort study design.

机构信息

Division of Population Health, Health Services Research and Primary Care, School of Health Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre (MAHSC), University of Manchester, Manchester, UK.

NIHR School for Primary Care Research, Centre for Primary Care, Manchester Academic Health Science Centre (MAHSC), University of Manchester, Manchester, UK.

出版信息

BMJ Open. 2018 Jun 30;8(6):e020926. doi: 10.1136/bmjopen-2017-020926.

Abstract

INTRODUCTION

The increasing prevalence of type 2 diabetes mellitus (T2DM) presents a significant burden on affected individuals and healthcare systems internationally. There is, however, no agreed validated measure to infer diabetes severity from electronic health records (EHRs). We aim to quantify T2DM severity and validate it using clinical adverse outcomes.

METHODS AND ANALYSIS

Primary care data from the Clinical Practice Research Datalink, linked hospitalisation and mortality records between April 2007 and March 2017 for patients with T2DM in England will be used to develop a clinical algorithm to grade T2DM severity. The EHR-based algorithm will incorporate main risk factors (severity domains) for adverse outcomes to stratify T2DM cohorts by baseline and longitudinal severity scores. Provisionally, T2DM severity domains, identified through a systematic review and expert opinion, are: diabetes duration, glycated haemoglobin, microvascular complications, comorbidities and coprescribed treatments. Severity scores will be developed by two approaches: (1) calculating a count score of severity domains; (2) through hierarchical stratification of complications. Regression models estimates will be used to calculate domains weights. Survival analyses for the association between weighted severity scores and future outcomes-cardiovascular events, hospitalisation (diabetes-related, cardiovascular) and mortality (diabetes-related, cardiovascular, all-cause mortality)-will be performed as statistical validation. The proposed EHR-based approach will quantify the T2DM severity for primary care performance management and inform the methodology for measuring severity of other primary care-managed chronic conditions. We anticipate that the developed algorithm will be a practical tool for practitioners, aid clinical management decision-making, inform stratified medicine, support future clinical trials and contribute to more effective service planning and policy-making.

ETHICS AND DISSEMINATION

The study protocol was approved by the Independent Scientific Advisory Committee. Some data were presented at the National Institute for Health Research School for Primary Care Research Showcase, September 2017, Oxford, UK and the Diabetes UK Professional Conference March 2018, London, UK. The study findings will be disseminated in relevant academic conferences and peer-reviewed journals.

摘要

简介

2 型糖尿病(T2DM)的患病率不断上升,给全球的患者和医疗体系带来了巨大的负担。然而,目前还没有一种公认的经过验证的方法可以从电子健康记录(EHR)中推断出糖尿病的严重程度。我们旨在通过临床不良结局来量化 T2DM 的严重程度并对其进行验证。

方法和分析

我们将使用英格兰临床实践研究数据链中的初级保健数据,结合 2007 年 4 月至 2017 年 3 月的住院和死亡记录,开发一种临床算法来评估 T2DM 的严重程度。该基于 EHR 的算法将结合主要的不良结局风险因素(严重程度域),根据基线和纵向严重程度评分对 T2DM 队列进行分层。暂时通过系统评价和专家意见确定 T2DM 严重程度域,包括:糖尿病病程、糖化血红蛋白、微血管并发症、合并症和合并治疗。严重程度评分将通过两种方法开发:(1)计算严重程度域的计数评分;(2)通过并发症的分层。回归模型估计将用于计算域权重。将对加权严重程度评分与未来结局(心血管事件、住院(糖尿病相关、心血管)和死亡(糖尿病相关、心血管、全因死亡))之间的关联进行生存分析,作为统计学验证。拟议的基于 EHR 的方法将量化初级保健管理中 T2DM 的严重程度,并为衡量其他初级保健管理的慢性疾病的严重程度提供方法学依据。我们预计,开发的算法将成为临床医生的实用工具,有助于临床管理决策,为分层医学提供信息,支持未来的临床试验,并有助于更有效的服务规划和决策制定。

伦理和传播

该研究方案已获得独立科学咨询委员会的批准。部分数据于 2017 年 9 月在英国牛津举行的国家卫生研究院初级保健研究学校展示会和 2018 年 3 月在英国伦敦举行的糖尿病协会专业会议上进行了展示。研究结果将在相关学术会议和同行评议期刊上发表。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d614/6042592/5e236063bc3b/bmjopen-2017-020926f01.jpg

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