Effect of electronic records on mortality among patients in hospital and primary healthcare settings: a systematic review and meta-analyses.

IF 3.2 Q1 HEALTH CARE SCIENCES & SERVICES Frontiers in digital health Pub Date : 2024-06-26 eCollection Date: 2024-01-01 DOI:10.3389/fdgth.2024.1377826
Tariku Nigatu Bogale, Lemma Derseh, Loko Abraham, Herman Willems, Jonathan Metzger, Biruhtesfa Abere, Mesfin Tilaye, Tewodros Hailegeberel, Tadesse Alemu Bekele
{"title":"Effect of electronic records on mortality among patients in hospital and primary healthcare settings: a systematic review and meta-analyses.","authors":"Tariku Nigatu Bogale, Lemma Derseh, Loko Abraham, Herman Willems, Jonathan Metzger, Biruhtesfa Abere, Mesfin Tilaye, Tewodros Hailegeberel, Tadesse Alemu Bekele","doi":"10.3389/fdgth.2024.1377826","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Electronic medical records or electronic health records, collectively called electronic records, have significantly transformed the healthcare system and service provision in our world. Despite a number of primary studies on the subject, reports are inconsistent and contradictory about the effects of electronic records on mortality. Therefore, this review examined the effect of electronic records on mortality.</p><p><strong>Methods: </strong>The review followed the Preferred Reporting Items for Systematic Reviews and Meta-analyses 2020 guideline. Six databases: PubMed, EMBASE, Scopus, CINAHL, Cochrane Library, and Google Scholar, were searched from February 20 to October 25, 2023. Studies that assessed the effect of electronic records on mortality and were published between 1998 and 2022 were included. Joanna Briggs Institute quality appraisal tool was used to assess the methodological quality of the studies. Narrative synthesis was performed to identify patterns across studies. Meta-analysis was conducted using fixed effect and random-effects models to estimate the pooled effect of electronic records on mortality. Funnel plot and Egger's regression test were used to assess for publication bias.</p><p><strong>Results: </strong>Fifty-four papers were found eligible for the systematic review, of which 42 were included in the meta-analyses. Of the 32 studies that assessed the effect of electronic health record on mortality, eight (25.00%) reported a statistically significant reduction in mortality, 22 (68.75%) did not show a statistically significant difference, and two (6.25%) studies reported an increased risk of mortality. Similarly, among the 22 studies that determined the effect of electronic medical record on mortality, 12 (54.55%) reported a statistically significant reduction in mortality, and ten (45.45%) studies didn't show a statistically significant difference. The fixed effect and random effects on mortality were OR = 0.95 (95% CI: 0.93-0.97) and OR = 0.94 (95% CI: 0.89-0.99), respectively. The associated I-squared was 61.5%. Statistical tests indicated that there was no significant publication bias among the studies included in the meta-analysis.</p><p><strong>Conclusion: </strong>Despite some heterogeneity among the studies, the review indicated that the implementation of electronic records in inpatient, specialized and intensive care units, and primary healthcare facilities seems to result in a statistically significant reduction in mortality. Maturity level and specific features may have played important roles.</p><p><strong>Systematic review registration: </strong>PROSPERO (CRD42023437257).</p>","PeriodicalId":73078,"journal":{"name":"Frontiers in digital health","volume":"6 ","pages":"1377826"},"PeriodicalIF":3.2000,"publicationDate":"2024-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11233798/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Frontiers in digital health","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3389/fdgth.2024.1377826","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/1/1 0:00:00","PubModel":"eCollection","JCR":"Q1","JCRName":"HEALTH CARE SCIENCES & SERVICES","Score":null,"Total":0}
引用次数: 0

Abstract

Background: Electronic medical records or electronic health records, collectively called electronic records, have significantly transformed the healthcare system and service provision in our world. Despite a number of primary studies on the subject, reports are inconsistent and contradictory about the effects of electronic records on mortality. Therefore, this review examined the effect of electronic records on mortality.

Methods: The review followed the Preferred Reporting Items for Systematic Reviews and Meta-analyses 2020 guideline. Six databases: PubMed, EMBASE, Scopus, CINAHL, Cochrane Library, and Google Scholar, were searched from February 20 to October 25, 2023. Studies that assessed the effect of electronic records on mortality and were published between 1998 and 2022 were included. Joanna Briggs Institute quality appraisal tool was used to assess the methodological quality of the studies. Narrative synthesis was performed to identify patterns across studies. Meta-analysis was conducted using fixed effect and random-effects models to estimate the pooled effect of electronic records on mortality. Funnel plot and Egger's regression test were used to assess for publication bias.

Results: Fifty-four papers were found eligible for the systematic review, of which 42 were included in the meta-analyses. Of the 32 studies that assessed the effect of electronic health record on mortality, eight (25.00%) reported a statistically significant reduction in mortality, 22 (68.75%) did not show a statistically significant difference, and two (6.25%) studies reported an increased risk of mortality. Similarly, among the 22 studies that determined the effect of electronic medical record on mortality, 12 (54.55%) reported a statistically significant reduction in mortality, and ten (45.45%) studies didn't show a statistically significant difference. The fixed effect and random effects on mortality were OR = 0.95 (95% CI: 0.93-0.97) and OR = 0.94 (95% CI: 0.89-0.99), respectively. The associated I-squared was 61.5%. Statistical tests indicated that there was no significant publication bias among the studies included in the meta-analysis.

Conclusion: Despite some heterogeneity among the studies, the review indicated that the implementation of electronic records in inpatient, specialized and intensive care units, and primary healthcare facilities seems to result in a statistically significant reduction in mortality. Maturity level and specific features may have played important roles.

Systematic review registration: PROSPERO (CRD42023437257).

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
电子病历对医院和基层医疗机构患者死亡率的影响:系统回顾和荟萃分析。
背景:电子病历或电子健康记录统称为电子记录,它极大地改变了我们这个世界的医疗保健系统和服务提供方式。尽管对这一主题进行了大量的初步研究,但关于电子病历对死亡率的影响的报告并不一致且相互矛盾。因此,本综述研究了电子病历对死亡率的影响:综述遵循了《2020 年系统综述和元分析首选报告项目》指南。六个数据库:从 2023 年 2 月 20 日至 10 月 25 日,检索了 PubMed、EMBASE、Scopus、CINAHL、Cochrane Library 和 Google Scholar 六个数据库。纳入了 1998 年至 2022 年间发表的评估电子记录对死亡率影响的研究。乔安娜-布里格斯研究所(Joanna Briggs Institute)质量评估工具用于评估研究的方法质量。进行了叙述性综合,以确定各项研究的模式。使用固定效应和随机效应模型进行 Meta 分析,以估计电子病历对死亡率的总体影响。使用漏斗图和 Egger 回归检验来评估发表偏倚:54篇论文符合系统综述的要求,其中42篇被纳入荟萃分析。在 32 项评估电子病历对死亡率影响的研究中,8 项(25.00%)报告死亡率在统计学上显著降低,22 项(68.75%)没有显示出统计学上的显著差异,2 项(6.25%)报告死亡率风险增加。同样,在确定电子病历对死亡率影响的 22 项研究中,12 项研究(54.55%)报告死亡率在统计学上有明显降低,10 项研究(45.45%)未显示统计学上的明显差异。死亡率的固定效应和随机效应分别为 OR = 0.95(95% CI:0.93-0.97)和 OR = 0.94(95% CI:0.89-0.99)。相关的 I 平方为 61.5%。统计检验表明,纳入荟萃分析的研究之间不存在明显的发表偏倚:尽管研究之间存在一些异质性,但综述表明,在住院、专科和重症监护病房以及基层医疗机构实施电子病历似乎能在统计学上显著降低死亡率。成熟度和具体特征可能发挥了重要作用:prospero(CRD42023437257)。
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
CiteScore
4.20
自引率
0.00%
发文量
0
审稿时长
13 weeks
期刊最新文献
The walking surface influences vertical ground reaction force and centre of pressure data obtained with pressure-sensing insoles. Promoting appropriate medication use by leveraging medical big data. Prospects for AI clinical summarization to reduce the burden of patient chart review. Data management practice of health extension workers and associated factors in Central Gondar Zone, northwest Ethiopia. Developing remote patient monitoring infrastructure using commercially available cloud platforms.
×
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