Evidence map›Paper›PMID 41144579›Full record

ArticleJMIR public health and surveillance2025

Correcting for the Inflated Adult Population Denominator in an English Nationwide Health Care Cohort: Database Analysis Study.

Sudhir Venkatesan, Mark Joy, Gavin Jamie, Debasish Kar, Robert Williams, Xuejuan Fan, Wilhelmine Meeraus, Ruby S M Tsang, Kathryn S Taylor, Sylvia Taylor and 4 more

Abstract read
In one paragraph

Article in JMIR public health and surveillance, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

14 authors.

Sudhir VenkatesanBPM Evidence Statistics, BioPharmaceuticals Medical, AstraZeneca, Cambridge, United Kingdom.ORCID 0000-0002-2093-5781
Mark JoyNuffield Department of Primary Care Health Sciences, University of Oxford, Radcliffe Observatory Quarter, Woodstock Road, Oxford, OX2 6GG, United Kingdom, 44 1865 617855.ORCID 0000-0002-4974-3724
Gavin JamieNuffield Department of Primary Care Health Sciences, University of Oxford, Radcliffe Observatory Quarter, Woodstock Road, Oxford, OX2 6GG, United Kingdom, 44 1865 617855.ORCID 0000-0001-9147-7784
Debasish KarNuffield Department of Primary Care Health Sciences, University of Oxford, Radcliffe Observatory Quarter, Woodstock Road, Oxford, OX2 6GG, United Kingdom, 44 1865 617855.ORCID 0000-0002-1524-1312
Robert WilliamsNuffield Department of Primary Care Health Sciences, University of Oxford, Radcliffe Observatory Quarter, Woodstock Road, Oxford, OX2 6GG, United Kingdom, 44 1865 617855.ORCID 0000-0002-1370-8898
Xuejuan FanNuffield Department of Primary Care Health Sciences, University of Oxford, Radcliffe Observatory Quarter, Woodstock Road, Oxford, OX2 6GG, United Kingdom, 44 1865 617855.ORCID 0000-0002-0165-8344
Wilhelmine MeerausVaccines and Immune Therapies, BioPharmaceuticals R&D, AstraZeneca, Cambridge, United Kingdom.ORCID 0000-0001-7476-8061
Ruby S M TsangPopulation Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom.
Kathryn S TaylorNuffield Department of Primary Care Health Sciences, University of Oxford, Radcliffe Observatory Quarter, Woodstock Road, Oxford, OX2 6GG, United Kingdom, 44 1865 617855.ORCID 0000-0001-6589-5456
Sylvia TaylorVaccines and Immune Therapies, BioPharmaceuticals R&D, AstraZeneca, Cambridge, United Kingdom.ORCID 0000-0001-7803-0611
F D Richard HobbsNuffield Department of Primary Care Health Sciences, University of Oxford, Radcliffe Observatory Quarter, Woodstock Road, Oxford, OX2 6GG, United Kingdom, 44 1865 617855.ORCID 0000-0001-7976-7172
Sneha N AnandNuffield Department of Primary Care Health Sciences, University of Oxford, Radcliffe Observatory Quarter, Woodstock Road, Oxford, OX2 6GG, United Kingdom, 44 1865 617855.ORCID 0000-0002-0538-3974
Chris RobertsonDepartment of Mathematics and Statistics, University of Strathclyde, Glasgow, United Kingdom.ORCID 0000-0001-6848-5241
Simon de LusignanNuffield Department of Primary Care Health Sciences, University of Oxford, Radcliffe Observatory Quarter, Woodstock Road, Oxford, OX2 6GG, United Kingdom, 44 1865 617855.ORCID 0000-0002-8553-2641

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Electronic health care databases are widely used for epidemiological studies. However, they may contain inactive records of individuals no longer participating in the health care system. These inactive records create a methodological challenge as they systematically appear as unexposed with no recorded outcomes. Given the widespread health care system engagement during the COVID-19 pandemic, the English National Health Service (NHS), which hosts a national pandemic planning and research dataset with linkage to COVID-19 vaccination and emergency care data, makes it an ideal setting to identify the extent of overrepresentation due to inactive health care records and assess ways to mitigate them. Objective: The objective of this study is to report any differences between the general practitioner-registered adult population size based on health care records compared to census estimates for England and to apply methodology that could be used to correct for such differences. Methods: We compared the number of adult patients within the General Practice Extraction Service Data for Pandemic Planning and Research (GDPPR) with a valid general practitioner registration as of 1st October 2021, with estimates published by the Office for National Statistics (ONS) for the English population. We used an approach adapted from a weighting method to correct for non-response bias in surveys and down-weighted individuals with no evidence of recent activity in their records. Results: There were 61,194,033 registered NHS patients (in the GDPPR) compared with 56,550,138 in the ONS census-based population. De-duplication on NHS number reduced the population to 57,876,641, including 46,835,968 adults, with the biggest overrepresented group aged 30-45 years. Of the 46,835,986, 1,121,954 (2.4%) individuals had their initial weights down-weighted due to non-engagement with the health care system since January 2019. The down-weighting removed most of the differences between NHS and ONS populations. Conclusions: There are notable differences in the adult population size as per GDPPR when compared to census estimates. While the overall population size in the GDPPR data was seen to be inflated when compared to ONS census estimates, this was differential with respect to sociodemographic variables. A weighting-based approach can be applied to correct for the inflated denominator. Not correcting for it in large health care datasets, including the English NHS data, could introduce selection bias in epidemiological studies.

Indexed as

COVID-19Databases, FactualAdolescentAdultAgedCensusesCohort StudiesEnglandFemaleHumansMaleMiddle AgedState MedicineYoung AdultcensusCOVID-19 vaccinesemergency medical servicesgeneral practitionersHealth InformaticsnationalNHSpandemic planningpopulationrecordregisterregistrationselection biasservicesizeweighting

Identifiers

PMID41144579
PMCPMC12559012

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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.