Evidence map›Paper›PMID 32948559›Full record

ArticleBMJ open2020

Cohort profile: the East London Health and Care Partnership Data Repository: using novel integrated data to support commissioning and research.

Amy Ronaldson, Evangelos Chandakas, Qiongwen Kang, Katie Brennan, Aminat Akande, Irene Ebyarimpa, Eleanor Wyllie, George Howard, Richard Fradgley, Mark Freestone and 1 more

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMJ open, 2020. 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
0.1field-weighted citation impact, top 47% of its field
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, 4 citations in OpenAlex.

  1. Article
  2. Clinical Data Warehousing: A Scoping Review.Journal of the Society for Clinical Data Management · 2024
    Article
  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

11 authors at 4 institutions in 1 country.

Amy RonaldsonDepartment of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK amy.ronaldson@kcl.ac.uk.ORCID 0000-0001-8369-9168
Evangelos ChandakasNHS Tower Hamlets Clinical Commissioning Group, London, London, UK.
Qiongwen KangNHS Tower Hamlets Clinical Commissioning Group, London, London, UK.
Katie BrennanNHS Tower Hamlets Clinical Commissioning Group, London, London, UK.
Aminat AkandeNHS Tower Hamlets Clinical Commissioning Group, London, London, UK.
Irene EbyarimpaNHS Tower Hamlets Clinical Commissioning Group, London, London, UK.
Eleanor WyllieHealthy London Partnership, London, UK.
George HowardHealthy London Partnership, London, UK.
Richard FradgleyEast London NHS Foundation Trust, London, London, UK.
Mark FreestoneCentre for Psychiatry, Wolfson Institute of Preventive Medicine, Barts & The London School of Medicine, Queen Mary University of London, London, UK.
Kamaldeep BhuiCentre for Psychiatry, Wolfson Institute of Preventive Medicine, Barts & The London School of Medicine, Queen Mary University of London, London, UK.ORCID 0000-0002-9205-2144
London Borough of Tower Hamlets · GBQueen Mary University of London · GBHealthcare Quality Improvement Partnership · GBEast London NHS Foundation Trust · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeThe East London Health and Care Partnership (ELHCP) Data Repository was established to support commissioning decisions in London. This dataset comprises routine clinical data for the general practitioner (GP)-registered populations of two London boroughs, Tower Hamlets and City and Hackney, and provides a rich source of demographic, clinical and health service use data of relevance to clinicians, commissioners, researchers and policy makers. This paper describes the dataset in its current form, its representativeness and data completeness.

participantsThere were 351 749 and 344 511 members of the GP-registered population in the two boroughs, respectively, for the financial year 2017/2018. Demographic information and prevalence data were available for 9 mental health and 15 physical health conditions. Prevalence rates from the cohort were compared with local and national data. In order to illustrate the health service use data available in the dataset, emergency department use across mental health conditions was described. Information about data completeness was provided. FINDINGS TO DATE: The ELHCP Data Repository provides a rich source of information about a relatively young, urban, ethnically diverse, population within areas of socioeconomic deprivation. Prevalence data were in line with local and national statistics with some exceptions. Physical health conditions were more common in those with mental health conditions, reflecting that comorbidities are the norm rather than the exception. This has implications for integrated care. Data completeness for risk factors (eg, blood pressure, cholesterol) was high in patients with long-term conditions. FUTURE PLANS: The data are being further cleaned and evaluated using imputation, Bayesian and economic methods, principally focusing on specific cohorts, including type II diabetes, depression and personality disorder. Data continue to be collected for the foreseeable future to support commissioning decisions, which will also enable more long-term prospective analysis as data become available at the end of each financial year.

Indexed as

Diabetes Mellitus, Type 2Bayes TheoremCohort StudiesHumansLondonMaleProspective Studiescommissioninghealth policyhealth servicesmental healthresearch cohort

Identifiers

PMID32948559
PMCPMC7511638
OpenAlexW3087298421

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

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.