Evidence map›Paper›PMID 39415208›Full record

ArticleBMC health services research2024

Understanding hospital rehabilitation using electronic health records in patients with and without COVID-19.

Konstantin Georgiev, Dimitrios Doudesis, Joanne McPeake, Nicholas L Mills, Jacques Fleuriot, Susan D Shenkin, Atul Anand

Abstract read
In one paragraph

Article in BMC health services research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
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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

7 authors.

Konstantin GeorgievUniversity of Edinburgh/BHF Centre for Cardiovascular Science, Room SU.226 Chancellor's Building, 49 Little France Crescent, EH16 4SA, Edinburgh, UK.
Dimitrios DoudesisUniversity of Edinburgh/BHF Centre for Cardiovascular Science, Room SU.226 Chancellor's Building, 49 Little France Crescent, EH16 4SA, Edinburgh, UK.
Joanne McPeakeThe Healthcare Improvement Studies Institute, University of Cambridge, Cambridge, UK.
Nicholas L MillsUniversity of Edinburgh/BHF Centre for Cardiovascular Science, Room SU.226 Chancellor's Building, 49 Little France Crescent, EH16 4SA, Edinburgh, UK.
Jacques FleuriotArtificial Intelligence and its Applications Institute, University of Edinburgh, Edinburgh, UK.
Susan D ShenkinAgeing and Health, and Advanced Care Research Centre, Usher Institute, University of Edinburgh, Edinburgh, UK.
Atul AnandUniversity of Edinburgh/BHF Centre for Cardiovascular Science, Room SU.226 Chancellor's Building, 49 Little France Crescent, EH16 4SA, Edinburgh, UK. atul.anand@ed.ac.uk.

Funding

British Heart Foundation CH/F/21/90010Medical Research Council MR/N013166/1Sir Jules Thorn Charitable Trust 21/01PhD
6 · The paper itself

Abstract

backgroundMany hospitalised patients require rehabilitation during recovery from acute illness. We use routine data from Electronic Health Records (EHR) to report the quantity and intensity of rehabilitation required to achieve hospital discharge, comparing patients with and without COVID-19.

methodsWe performed a retrospective cohort study of consecutive adults in whom COVID-19 testing was undertaken between March 2020 and August 2021 across three acute hospitals in Scotland. We defined rehabilitation contacts (physiotherapy, occupational therapy, dietetics and speech and language therapy) from timestamped EHR data and determined contact time from a linked workforce planning dataset. Our aim was to clarify rehabilitation required to achieve hospital discharge and so we excluded patients who died during their admission, and those who did not require rehabilitation (fewer than two specialist contacts). The primary outcome was total rehabilitation time. Secondary outcomes included the number of contacts, admission to first contact, and rehabilitation minutes per day. A multivariate regression analysis for identifying patient characteristics associated with rehabilitation time included age, sex, comorbidities, and socioeconomic status.

resultsWe included 11,591 consecutive unique patient admissions (76 [63,85] years old, 56% female), of which 651 (6%) were with COVID-19, and 10,940 (94%) were admissions with negative testing. There were 128,646 rehabilitation contacts. Patients with COVID-19 received more than double the rehabilitation time compared to those without (365 [165, 772] vs 170 [95, 350] mins, p<0.001), and this was delivered over more specialist contacts (12 [6, 25] vs 6 [3, 11], p<0.001). Admission to first rehabilitation contact was later in patients with COVID-19 (3 [1, 5] vs 2 [1, 4] days from admission). Overall, patients with COVID-19 received fewer minutes of rehabilitation per day of admission (14.1 [9.8, 18.7] vs 15.6 [10.6, 21.3], p<0.001). In our regression analyses, older age and COVID-19 were associated with increased rehabilitation time.

conclusionsPatients with COVID received more rehabilitation contact time than those without COVID, but this was delivered less intensively and was commenced later in an admission. Rehabilitation data derived from the EHR represents a novel measure of delivered hospital care.

Indexed as

COVID-19Electronic Health RecordsSARS-CoV-2AgedAged, 80 and overFemaleHospitalizationHumansMaleMiddle AgedPatient DischargeRetrospective StudiesScotlandCOVID-19Electronic health recordsRehabilitation

Identifiers

PMID39415208
PMCPMC11484221

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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.