Evidence map›Paper›PMID 37654785›Full record

ArticleDelirium communications2023

Trends in delirium coding rates in older hospital inpatients in England and Scotland: full population data comprising 7.7M patients per year show substantial increases between 2012 and 2020.

Temi Ibitoye, Thomas A Jackson, Daniel Davis, Alasdair M J MacLullich

Open access · hybridAbstract read
In one paragraph

Article in Delirium communications, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.9field-weighted citation impact, top 14% 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

8 citing papers in PubMed, 9 citations in OpenAlex.

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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

4 authors at 3 institutions in 1 country.

Temi IbitoyeEdinburgh Delirium Research Group, Ageing and Health, Usher Institute, The University of Edinburgh.ORCID https://orcid.org/0000-0001-8571-988X
Thomas A JacksonInstitute of Inflammation and Ageing, University of Birmingham.ORCID https://orcid.org/0000-0001-6320-9600
Daniel DavisMRC Unit for Lifelong Health and Ageing, University College London.ORCID https://orcid.org/0000-0002-1560-1955
Alasdair M J MacLullichEdinburgh Delirium Research Group, Ageing and Health, Usher Institute, University of Edinburgh.ORCID https://orcid.org/0000-0003-3159-9370
University of Edinburgh · GBMRC Unit for Lifelong Health and Ageing · GBUniversity of Birmingham · GB

Funding

Medical Research Council MC_UU_00019/1Medical Research Council MC_UU_00019/2Wellcome Trust 107467Wellcome Trust 107467/Z/15/Z
6 · The paper itself

Abstract

Background: Little information is available on change in delirium coding rates over time in major healthcare systems. We examined trends in delirium discharge coding rates in older patients in hospital admissions to the National Health Service (NHS) in England and Scotland between 2012 and 2020. Methods: Hospital administrative coding data were sourced from NHS Digital England and Public Health Scotland. We examined rates of delirium (F05 from ICD-10) in patients aged ≥70 years in 5 year and ≥90 age bands. Results: There were approximately 7,000,000 discharges/year in England and 700,000/year in Scotland. Substantially increased delirium coding was observed for all age bands between 2012/2013 and 2019/2020 (p<0.001, Mann Kendall's tau). In the ≥90 age band, there was a 4-fold increase between 2012 and 2020. Conclusion: Delirium coding rates have shown large increases in the NHS in England and Scotland, likely reflecting several factors including policy initiatives, detection tool implementation and education.

Indexed as

CodingDeliriumGeriatric MedicineHospital Administrative DatabaseICD-10National Data

Identifiers

PMID37654785
PMCPMC7614999
OpenAlexW4385381781

What OpenQuestion holds

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LicenceCC BY
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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.