UK Electronic Healthcare Records for Research: A Scientometric Analysis of Respiratory, Cardiovascular, and COVID-19 Publications.

IF 2.3 Q2 MEDICINE, GENERAL & INTERNAL Pragmatic and Observational Research Pub Date : 2024-08-15 eCollection Date: 2024-01-01 DOI:10.2147/POR.S469973
Georgie M Massen, Olivia Blamires, Megan Grainger, Max Matta, Rachel Monica Gyemfuah Twumasi, Tanvi Joshi, Alex Laity, Elena Nakariakova, Thilaksana Thavaranjan, Aziz Sheikh, Jennifer K Quint
{"title":"UK Electronic Healthcare Records for Research: A Scientometric Analysis of Respiratory, Cardiovascular, and COVID-19 Publications.","authors":"Georgie M Massen, Olivia Blamires, Megan Grainger, Max Matta, Rachel Monica Gyemfuah Twumasi, Tanvi Joshi, Alex Laity, Elena Nakariakova, Thilaksana Thavaranjan, Aziz Sheikh, Jennifer K Quint","doi":"10.2147/POR.S469973","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Routinely collected electronic healthcare records (EHRs) document many details of a person's health, including demographics, preventive services, symptoms, tests, disease diagnoses and prescriptions. Although not collected for research purposes, these data provide a wealth of information which can be incorporated into epidemiological investigations, and records can be analysed to understand a range of important health questions. We aimed to understand the use of routinely collected health data in epidemiological studies relating to three of the most common chronic respiratory conditions, namely: asthma, chronic obstructive pulmonary disease (COPD) and interstitial lung disease (ILD). We also characterised studies using EHR data to investigate respiratory diseases more generally, relative to cardiovascular disease and COVID-19, to understand trends in the use of these data.</p><p><strong>Methods: </strong>We conducted a search of the Scopus database, to identify original research articles (irrespective of date) which used data from one of the following most frequently used UK EHR databases: Clinical Practice Research Datalink (including General Practice Research Database (CPRD's predecessor)), The Health Improvement Network and QResearch, defined through the presence of keywords. These databases were selected as they had been previously included in the works of Vezyridis and Timmons.</p><p><strong>Findings: </strong>A total of 716 manuscripts were included in the analysis of the three chronic respiratory conditions. The majority investigated either asthma or COPD, whilst only 28 manuscripts investigated ILD. The number of publications has increased for respiratory conditions over the past 10 years (888% increase from 2000 to 2022) but not as much as for cardiovascular diseases (1105%). These data have been used to investigate comorbidities, off-target effects of medication, as well as assessing disease incidence and prevalence. Most papers published across all three domains were in journals with an impact factor less than 10.</p>","PeriodicalId":20399,"journal":{"name":"Pragmatic and Observational Research","volume":null,"pages":null},"PeriodicalIF":2.3000,"publicationDate":"2024-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11332414/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Pragmatic and Observational Research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2147/POR.S469973","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/1/1 0:00:00","PubModel":"eCollection","JCR":"Q2","JCRName":"MEDICINE, GENERAL & INTERNAL","Score":null,"Total":0}
引用次数: 0

Abstract

Background: Routinely collected electronic healthcare records (EHRs) document many details of a person's health, including demographics, preventive services, symptoms, tests, disease diagnoses and prescriptions. Although not collected for research purposes, these data provide a wealth of information which can be incorporated into epidemiological investigations, and records can be analysed to understand a range of important health questions. We aimed to understand the use of routinely collected health data in epidemiological studies relating to three of the most common chronic respiratory conditions, namely: asthma, chronic obstructive pulmonary disease (COPD) and interstitial lung disease (ILD). We also characterised studies using EHR data to investigate respiratory diseases more generally, relative to cardiovascular disease and COVID-19, to understand trends in the use of these data.

Methods: We conducted a search of the Scopus database, to identify original research articles (irrespective of date) which used data from one of the following most frequently used UK EHR databases: Clinical Practice Research Datalink (including General Practice Research Database (CPRD's predecessor)), The Health Improvement Network and QResearch, defined through the presence of keywords. These databases were selected as they had been previously included in the works of Vezyridis and Timmons.

Findings: A total of 716 manuscripts were included in the analysis of the three chronic respiratory conditions. The majority investigated either asthma or COPD, whilst only 28 manuscripts investigated ILD. The number of publications has increased for respiratory conditions over the past 10 years (888% increase from 2000 to 2022) but not as much as for cardiovascular diseases (1105%). These data have been used to investigate comorbidities, off-target effects of medication, as well as assessing disease incidence and prevalence. Most papers published across all three domains were in journals with an impact factor less than 10.

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
英国用于研究的电子医疗记录:呼吸系统、心血管系统和 COVID-19 出版物的科学计量分析。
背景:日常收集的电子医疗记录(EHR)记录了个人健康的许多细节,包括人口统计学、预防服务、症状、检查、疾病诊断和处方。虽然这些数据不是为研究目的而收集的,但它们提供了大量信息,可用于流行病学调查,对记录进行分析可了解一系列重要的健康问题。我们旨在了解常规收集的健康数据在与三种最常见的慢性呼吸系统疾病(即哮喘、慢性阻塞性肺病 (COPD) 和间质性肺病 (ILD) )相关的流行病学研究中的使用情况。相对于心血管疾病和 COVID-19,我们还对使用电子病历数据更广泛地调查呼吸系统疾病的研究进行了描述,以了解这些数据的使用趋势:我们对 Scopus 数据库进行了搜索,以确定使用了以下最常用的英国电子病历数据库之一的数据的原创研究文章(不论日期):临床实践研究数据链(包括全科实践研究数据库(CPRD 的前身))、健康改善网络和 QResearch(通过关键词定义)。之所以选择这些数据库,是因为它们曾被纳入 Vezyridis 和 Timmons 的著作中:共有 716 篇手稿被纳入三种慢性呼吸系统疾病的分析中。其中大部分研究了哮喘或慢性阻塞性肺病,只有 28 篇手稿研究了 ILD。在过去十年中,呼吸系统疾病的论文数量有所增加(从2000年到2022年增加了888%),但不及心血管疾病(1105%)。这些数据被用于研究合并症、药物的脱靶效应以及评估疾病的发病率和流行率。在所有三个领域发表的大多数论文都发表在影响因子小于 10 的期刊上。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Pragmatic and Observational Research
Pragmatic and Observational Research MEDICINE, GENERAL & INTERNAL-
自引率
0.00%
发文量
11
期刊介绍: Pragmatic and Observational Research is an international, peer-reviewed, open-access journal that publishes data from studies designed to closely reflect medical interventions in real-world clinical practice, providing insights beyond classical randomized controlled trials (RCTs). While RCTs maximize internal validity for cause-and-effect relationships, they often represent only specific patient groups. This journal aims to complement such studies by providing data that better mirrors real-world patients and the usage of medicines, thus informing guidelines and enhancing the applicability of research findings across diverse patient populations encountered in everyday clinical practice.
期刊最新文献
Improving the Transparency and Replicability of Consensus Methods: Respiratory Medicine as a Case Example. Non-Alcoholic Steatohepatitis Patient Characterization and Real-World Management Approaches in Italy. Comparing Machine Learning and Advanced Methods with Traditional Methods to Generate Weights in Inverse Probability of Treatment Weighting: The INFORM Study. Involvement of Root Canal Treatment in Pro-Inflammatory Processes - A Real-World Study. UK Electronic Healthcare Records for Research: A Scientometric Analysis of Respiratory, Cardiovascular, and COVID-19 Publications.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1