Evidence map›Paper›PMID 29267840›Full record

ArticleAge and ageing2018

Accurate identification of hospital admissions from care homes; development and validation of an automated algorithm.

Gemma Housley, Sarah Lewis, Adeela Usman, Adam L Gordon, Dominick E Shaw

Abstract readValidation Study
In one paragraph

Article in Age and ageing, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

  1. Article
  2. Article
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  4. Closing the UK care home data gap - methodological challenges and solutions.International journal of population data science · 2021
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  5. Article
  6. Article
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  8. A novel method for identifying care home residents in England: a validation study.International journal of population data science · 2020
    Article
  9. Article
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors.

Gemma HousleyEast Midlands Academic Health Science Network, Clinical Sciences Building, Nottingham City Hospital Campus, Hucknall Road, Nottingham, UK.
Sarah LewisDivision of Epidemiology and Public Health, School of Medicine, University of Nottingham, Nottingham, UK.
Adeela UsmanDivision of Medical Sciences and Graduate Entry Medicine, University of Nottingham, Derby Medical School, Derby, UK.
Adam L GordonDivision of Medical Sciences and Graduate Entry Medicine, University of Nottingham, Derby Medical School, Derby, UK.
Dominick E ShawEast Midlands Academic Health Science Network, Clinical Sciences Building, Nottingham City Hospital Campus, Hucknall Road, Nottingham, UK.

Funding

The Dunhill Medical Trust FOP1/0115
6 · The paper itself

Abstract

Background: measuring the complex needs of care home residents is crucial for resource allocation. Hospital patient administration systems (PAS) may not accurately identify admissions from care homes. Objective: to develop and validate an accurate, practical method of identifying care home resident hospital admission using routinely collected PAS data. Method: admissions data between 2011 and 2012 (n = 103,105) to an acute Trust were modelled to develop an automated tool which compared the hospital PAS address details with the Care Quality Commission's (CQC) database, producing a likelihood of care home residency. This tool and the Nuffield method (CQC postcode match only) were validated against a manual check of a random sample of admissions (n = 2,000). A dataset from a separate Trust was analysed to assess generalisability. Results: the hospital PAS was inaccurate; none of the admissions from a care home identified on manual check had a care home source of admission recorded on the PAS. Both methods performed well; the automated tool had a higher positive predictive value than the Nuffield method (100% 95% confidence interval (CI) 98.23-100% versus 87.10% 95%CI 82.28-91.00%), meaning those coded as care home residents were more likely to actually be from a care home. Our automated tool had a high level of agreement 99.2% with the second Trust's data (Kappa 0.86 P < 0.001). Conclusions: care home status is not routinely or accurately captured. Automated matching offers an accurate, repeatable, scalable method to identify care home residency and could be used as a tool to benchmark how care home residents use acute hospital resources across the National Health Service.

Indexed as

AlgorithmsDatabases, FactualHomes for the AgedHospitalsNursing HomesPatient AdmissionAged, 80 and overData AccuracyData MiningEnglandFemaleHealth Services Needs and DemandHumansMaleReproducibility of ResultsState Medicine

Identifiers

PMID29267840
PMCPMC5920300

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.