Evidence map›Paper›PMID 41332487›Full record

ArticleInternational journal of population data science2025

Estimating households and populations from primary care electronic health records: comparison with Office for National Statistics Census 2021 aggregated estimates.

Marta Wilk, Gill Harper, Nicola Firman, Chris Dibben, Rich Fry, Carol Dezateux

Abstract readComparative Study
PubMed Full text at PMC Publisher
In one paragraph

Article in International journal of population data science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Observational
  3. 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.

Marta WilkCentre for Primary Care, Wolfson Institute of Population Health, Faculty of Medicine and Dentistry, Queen Mary University of London, Yvonne Carter Building, 58 Turner Street, London, E1 2AB.
Gill HarperCentre for Primary Care, Wolfson Institute of Population Health, Faculty of Medicine and Dentistry, Queen Mary University of London, Yvonne Carter Building, 58 Turner Street, London, E1 2AB.
Nicola FirmanCentre for Primary Care, Wolfson Institute of Population Health, Faculty of Medicine and Dentistry, Queen Mary University of London, Yvonne Carter Building, 58 Turner Street, London, E1 2AB.
Chris DibbenThe University of Edinburgh, School of Geosciences.
Rich FrySwansea University, Medical School.
Carol DezateuxCentre for Primary Care, Wolfson Institute of Population Health, Faculty of Medicine and Dentistry, Queen Mary University of London, Yvonne Carter Building, 58 Turner Street, London, E1 2AB.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Up-to-date, high-quality estimates of population and households are essential for planning the provision of local and central infrastructure. Objectives: We aimed to derive estimates of population size, and household numbers and size on Census date (21/03/2021) using north-east London primary care Electronic Health Records (EHR) and calculate levels of their agreement with the publicly available official Census 2021 estimates to assess if health data have the potential to be used to create reliable statistics. Methods: We compared EHR and Census population estimates by sex, age, local authority, and IMD quintile, and EHR and Census household estimates by number, size, and local authority. We estimated 95% Limits of Agreement between EHR and Census household and population estimates using the Bland and Altman method. In sensitivity analyses, we excluded people with no General Practice encounter within 12 months and compared the adjusted population's size to Census estimate.We compared EHR and administrative Statistical Population Dataset (SPD) to Census population estimates by sex and age, and EHR and Admin-based Occupied Address Dataset (ABOAD) to Census household estimates by local authority and household size. Results: EHR population estimate was 2,130,965, i.e. 7.1% higher than Census of 1,990,087. EHR household estimate was 658,264, i.e. 9.1% lower than Census of 724,045. The estimate of population with recent GP encounter was 11.6% lower than the Census estimate.Compared to Census, both SPD and EHR overcounted population of males (10.7%, 7.9% respectively) and females (3.6%, 2.7% respectively). Both ABOAD and EHR had undercounted households compared to Census (-7.3%; -9.1% respectively). Conclusions: Reliable, up-to-date populations and households estimates can be derived from health records. High residential mobility increases the complexity of deriving these estimates. Excluding people without GP encounters does not improve agreement with Census. Future work will focus on comparing Census and EHR estimates using individual-level data.

Indexed as

CensusesElectronic Health RecordsFamily CharacteristicsPopulation DensityPrimary Health CareAdolescentAdultAgedChildChild, PreschoolFemaleHumansInfantLondonMaleMiddle Agedcensus comparison studydata representativenesselectronic health recordshousehold estimatesPopulation estimates

Identifiers

PMID41332487
PMCPMC12668252

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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.