Evidence map›Paper›PMID 37991820›Full record

ArticleJMIR medical informatics2023

The Roles of Electronic Health Records for Clinical Trials in Low- and Middle-Income Countries: Scoping Review.

Jiancheng Ye, Shangzhi Xiong, Tengyi Wang, Jingyi Li, Nan Cheng, Maoyi Tian, Yang Yang

Erratum issuedAbstract readScoping Review
In one paragraph

Article in JMIR medical informatics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 13 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

13 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  12. Multimodal Data Hybrid Fusion and Natural Language Processing for Clinical Prediction Models.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2024
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors.

Jiancheng Ye *Weill Cornell Medicine, New York, NY, United States.ORCID https://orcid.org/0000-0003-4143-8423
Shangzhi Xiong *The George Institute for Global Health, Faulty of Medicine and Health, University of New South Wales, Sydney, Australia.ORCID https://orcid.org/0000-0002-5580-8686
Tengyi WangSchool of Public Health, Harbin Medical University, Harbin, China.ORCID https://orcid.org/0009-0008-7609-533X
Jingyi LiSchool of Basic Medicine, Harbin Medical University, Harbin, China.ORCID https://orcid.org/0000-0001-8897-5475
Nan ChengThe First Affiliated Hospital of Harbin Medical University, Harbin, China.ORCID https://orcid.org/0009-0004-8719-2574
Maoyi TianThe George Institute for Global Health, Faulty of Medicine and Health, University of New South Wales, Sydney, Australia.ORCID https://orcid.org/0000-0002-5660-8571
Yang YangSchool of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, China.ORCID https://orcid.org/0000-0002-0576-9455

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundClinical trials are a crucial element in advancing medical knowledge and developing new treatments by establishing the evidence base for safety and therapeutic efficacy. However, the success of these trials depends on various factors, including trial design, project planning, research staff training, and adequate sample size. It is also crucial to recruit participants efficiently and retain them throughout the trial to ensure timely completion.

objectiveThere is an increasing interest in using electronic health records (EHRs)-a widely adopted tool in clinical practice-for clinical trials. This scoping review aims to understand the use of EHR in supporting the conduct of clinical trials in low- and middle-income countries (LMICs) and to identify its strengths and limitations.

methodsA comprehensive search was performed using 5 databases: MEDLINE, Embase, Scopus, Cochrane Library, and the Cumulative Index to Nursing and Allied Health Literature. We followed the latest version of the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guideline to conduct this review. We included clinical trials that used EHR at any step, conducted a narrative synthesis of the included studies, and mapped the roles of EHRs into the life cycle of a clinical trial.

resultsA total of 30 studies met the inclusion criteria: 13 were randomized controlled trials, 3 were cluster randomized controlled trials, 12 were quasi-experimental studies, and 2 were feasibility pilot studies. Most of the studies addressed infectious diseases (15/30, 50%), with 80% (12/15) of them about HIV or AIDS and another 40% (12/30) focused on noncommunicable diseases. Our synthesis divided the roles of EHRs into 7 major categories: participant identification and recruitment (12/30, 40%), baseline information collection (6/30, 20%), intervention (8/30, 27%), fidelity assessment (2/30, 7%), primary outcome assessment (24/30, 80%), nonprimary outcome assessment (13/30, 43%), and extended follow-up (2/30, 7%). None of the studies used EHR for participant consent and randomization.

conclusionsDespite the enormous potential of EHRs to increase the effectiveness and efficiency of conducting clinical trials in LMICs, challenges remain. Continued exploration of the appropriate uses of EHRs by navigating their strengths and limitations to ensure fitness for use is necessary to better understand the most optimal uses of EHRs for conducting clinical trials in LMICs.

Indexed as

clinical trialselectronic health recordslow- and middle-income countries

Identifiers

PMID37991820
PMCPMC10701650

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.