Evidence map›Paper›PMID 29945656›Full record

Trial reportTrials2018

Automated recruitment and randomisation for an efficient randomised controlled trial in primary care.

Victoria R Cornelius, Lisa McDermott, Alice S Forster, Mark Ashworth, Alison J Wright, Martin C Gulliford

Abstract readComparative StudyMulticenter StudyRandomized Controlled Trial
In one paragraph

Trial report in Trials, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–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

5 citing papers in PubMed.

  1. Trial
  2. Article
  3. Review
  4. Review
  5. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Victoria R CorneliusDepartment of Primary Care and Public Health Sciences, King's College, London, UK. v.cornelius@imperial.ac.uk.ORCID http://orcid.org/0000-0002-0080-1065
Lisa McDermottDepartment of Primary Care and Public Health Sciences, King's College, London, UK.
Alice S ForsterDepartment of Primary Care and Public Health Sciences, King's College, London, UK.
Mark AshworthDepartment of Primary Care and Public Health Sciences, King's College, London, UK.
Alison J WrightDepartment of Primary Care and Public Health Sciences, King's College, London, UK.
Martin C GullifordDepartment of Primary Care and Public Health Sciences, King's College, London, UK.

Funding

Cancer Research UK 17429Department of Health 11/129/61
6 · The paper itself

Abstract

BACKGROUND/

aimsUse of electronic health records and information technology to deliver more efficient clinical trials is attracting the attention of research funders and researchers. We report on methodological issues and data quality for a comparison of 'automated' and manual (or 'in-practice') methods for recruitment and randomisation in a large randomised controlled trial, with individual patient allocation in primary care.

methodsWe conducted a three-arm randomised controlled trial in primary care to evaluate interventions to improve the uptake of invited NHS health checks for cardiovascular risk assessment. Eligible participants were identified using a borough-wide health check management information system. An in-practice recruitment and randomisation method used at 12 general practices required the research team to complete monthly visits to each general practice. For the fully automated method, employed for six general practices, randomisation of eligible participants was performed automatically and remotely using a bespoke algorithm embedded in the health check management information system.

resultsThere were 8588 and 4093 participants recruited for the manual and automated methods, respectively. The in-practice method was ready for implementation 3 months sooner than the automated method and the in-practice method allowed for full control and documentation of the randomisation procedure. However the in-practice approach was labour intensive and the requirement for participant records to be stored locally resulted in the loss of data for 10 practice months. No records for participants allocated using the automated method were lost. A fixed-effects meta-analysis showed that effect estimates for the primary outcome were consistent for the two allocation methods.

conclusionsThis trial demonstrated the feasibility of automated recruitment and randomisation methods into a randomised controlled trial performed in primary care. Future research should explore the application of these techniques in other clinical contexts and health care settings.

trial registrationCurrent Controlled Trials, ID: ISRCTN42856343 . Registered on 21 March 2013.

Indexed as

Electronic Health RecordsPatient SelectionPrimary Health CareAlgorithmsAutomationData AccuracyData MiningDiabetes MellitusHealth Services ResearchHeart DiseasesHumansLondonRenal Insufficiency, ChronicRisk FactorsState MedicineStrokeAutomated randomisationEfficient trial designElectronic health recordsPrimary careRandomised controlled trial

Identifiers

PMID29945656
PMCPMC6020316

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Registered trials

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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.