Evidence map›Paper›PMID 38816052›Full record

ArticleBMJ open2024

Protocol for the Development and Analysis of the Oxford and Reading Cognitive Comorbidity, Frailty and Ageing Research Database-Electronic Patient Records (ORCHARD-EPR).

Emily Boucher, Aimee Jell, Sudhir Singh, Jim Davies, Tanya Smith, Adam Pill, Kinga Varnai, Kerrie Woods, David Walliker, Aubretia McColl and 2 more

Abstract read
In one paragraph

Article in BMJ open, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Observational
  4. 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

12 authors.

Emily BoucherWolfson Centre for Prevention of Stroke and Dementia, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.ORCID 0000-0002-9854-3462
Aimee JellInformatics Department, Oxford University Hospitals NHS Foundation Trust, Oxford, UK.
Sudhir SinghDepartment of Acute General (Internal) Medicine, Oxford University Hospitals NHS Foundation Trust, Oxford, UK.
Jim DaviesDepartment of Computer Science, University of Oxford, Oxford, UK.
Tanya SmithResearch Informatics Team, Research and Development Department, Oxford Health NHS Foundation Trust, Oxford, UK.
Adam PillResearch Informatics Team, Research and Development Department, Oxford Health NHS Foundation Trust, Oxford, UK.
Kinga VarnaiResearch and Development Clinical Informatics, Oxford University Hospitals NHS Foundation Trust, Oxford, UK.
Kerrie WoodsResearch and Development Clinical Informatics, Oxford University Hospitals NHS Foundation Trust, Oxford, UK.
David WallikerResearch and Development Clinical Informatics, Oxford University Hospitals NHS Foundation Trust, Oxford, UK.
Aubretia McCollDepartment of Acute Medicine, Royal Berkshire NHS Foundation Trust, Reading, UK.
Sasha ShepperdNuffield Department of Population Health, University of Oxford, Oxford, UK.ORCID 0000-0001-6384-8322
Sarah PendleburyWolfson Centre for Prevention of Stroke and Dementia, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK sarah.pendlebury@ndcn.ox.ac.uk.ORCID 0000-0003-3603-8388

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHospital electronic patient records (EPRs) offer the opportunity to exploit large-scale routinely acquired data at relatively low cost and without selection. EPRs provide considerably richer data, and in real-time, than retrospective administrative data sets in which clinical complexity is often poorly captured. With population ageing, a wide range of hospital specialties now manage older people with multimorbidity, frailty and associated poor outcomes. We, therefore, set-up the Oxford and Reading Cognitive Comorbidity, Frailty and Ageing Research Database-Electronic Patient Records (ORCHARD-EPR) to facilitate clinically meaningful research in older hospital patients, including algorithm development, and to aid medical decision-making, implementation of guidelines, and inform policy. METHODS AND ANALYSIS: ORCHARD-EPR uses routinely acquired individual patient data on all patients aged ≥65 years with unplanned admission or Same Day Emergency Care unit attendance at four acute general hospitals serving a population of >800 000 (Oxfordshire, UK) with planned extension to the neighbouring Berkshire regional hospitals (>1 000 000). Data fields include diagnosis, comorbidities, nursing risk assessments, frailty, observations, illness acuity, laboratory tests and brain scan images. Importantly, ORCHARD-EPR contains the results from mandatory hospital-wide cognitive screening (≥70 years) comprising the 10-point Abbreviated-Mental-Test and dementia and delirium diagnosis (Confusion Assessment Method-CAM). Outcomes include length of stay, delayed transfers of care, discharge destination, readmissions and death. The rich multimodal data are further enhanced by linkage to secondary care electronic mental health records. Selection of appropriate subgroups or linkage to existing cohorts allows disease-specific studies. Over 200 000 patient episodes are included to date with data collection ongoing of which 129 248 are admissions with a length of stay ≥1 day in 64 641 unique patients. ETHICS AND DISSEMINATION: ORCHARD-EPR is approved by the South Central Oxford C Research Ethics Committee (ref: 23/SC/0258). Results will be widely disseminated through peer-reviewed publications and presentations at conferences, and regional meetings to improve hospital data quality and clinical services.

Indexed as

ComorbidityElectronic Health RecordsAgedAged, 80 and overAgingDatabases, FactualFemaleFrailtyGeriatric AssessmentHumansMaleUnited KingdomDecision MakingDementiaElectronic Health RecordsFrailtyHospitals

Identifiers

PMID38816052
PMCPMC11141189

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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.