Evidence map›Paper›PMID 30626337›Full record

ArticleBMC medical research methodology2019

Self-reported and routinely collected electronic healthcare resource-use data for trial-based economic evaluations: the current state of play in England and considerations for the future.

Matthew Franklin, Joanna Thorn

Abstract read
In one paragraph

Article in BMC medical research methodology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.

0numbers the graph read from it
0cells of the map it votes in
34citing 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

34 citing papers in PubMed.

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  5. Glycaemic control in labour with diabetes: GILD, a scoping study.Health technology assessment (Winchester, England) · 2025
    Article
  6. Prevalence trends and risk factors for allergic rhinoconjunctivitis, asthma and eczema in the UK.Allergy, asthma, and clinical immunology : official journal of the Canadian Society of Allergy and Clinical Immunology · 2025
    Article
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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

2 authors.

Matthew FranklinSchool of Health and Related Research (ScHARR), University of Sheffield West Court, 1 Mappin Street, Sheffield, S1 4DT, UK. matt.franklin@sheffield.ac.uk.ORCID 0000-0002-2774-9439
Joanna ThornSchool of Social and Community Medicine, University of Bristol Canynge Hall, 39 Whatley Road, Bristol, BS8 2PS, UK.

Funding

Medical Research Council MR/K025643/1Medical Research Council MR/L004933/2
6 · The paper itself

Abstract

backgroundRandomised controlled trials (RCTs) are generally regarded as the "gold standard" for providing quantifiable evidence around the effectiveness and cost-effectiveness of new healthcare technologies. In order to perform the economic evaluations associated with RCTs, there is a need for accessible and good quality resource-use data; for the purpose of discussion here, data that best reflect the care received. Traditionally, researchers have developed questionnaires for resource-use data collection. However, the evolution of routinely collected electronic data within care services provides new opportunities for collecting data without burdening patients or caregivers (e.g. clinicians). This paper describes the potential strengths and limitations of each data collection method and then discusses aspects for consideration before choosing which method to use. MAIN TEXT: We describe electronic data sources (large observational datasets, commissioning data, and raw data extraction) that may be suitable data sources for informing clinical trials and the current status of self-reported instruments for measuring resource-use. We assess the methodological risks and benefits, and compare the two methodologies. We focus on healthcare resource-use; however, many of the considerations have relevance to clinical questions. Patient self-report forms a pragmatic and cheap method that is largely under the control of the researcher. However, there are known issues with the validity of the data collected, loss to follow-up may be high, and questionnaires suffer from missing data. Routinely collected electronic data may be more accurate and more practical if large numbers of patients are involved. However, datasets often incur a cost and researchers are bound by the time for data approval and extraction by the data holders.

conclusionsOwing to the issues associated with electronic datasets, self-reported methods may currently be the preferred option. However, electronic hospital data are relatively more accessible, informative, standardised, and reliable. Therefore in trials where secondary care constitutes a major driver of patient care, detailed electronic data may be considered superior to self-reported methods; with the caveat of requiring data sharing agreements with third party providers and potentially time-consuming extraction periods. Self-reported methods will still be required when a 'societal' perspective (e.g. quantifying informal care) is desirable for the intended analysis.

Indexed as

Data AccuracyDatasets as TopicElectronic Health RecordsEnglandHumansRandomized Controlled Trials as TopicSelf ReportBig dataData collection methodologyLarge observational datasetsRoutinely collected dataSelf-reportTrial-based evaluation

Identifiers

PMID30626337
PMCPMC6325715

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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.