Evidence map›Paper›PMID 39689107›Full record

ArticlePLOS digital health2024

Differential behaviour of a risk score for emergency hospital admission by demographics in Scotland-A retrospective study.

Ioanna Thoma, Simon Rogers, Jillian Ireland, Rachel Porteous, Katie Borland, Catalina A Vallejos, Louis J M Aslett, James Liley

Abstract read
In one paragraph

Article in PLOS digital health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

8 authors.

Ioanna ThomaAlan Turing Institute, London, United Kingdom.ORCID https://orcid.org/0000-0001-6928-2198
Simon RogersNHS National Services Scotland, United Kingdom.ORCID https://orcid.org/0000-0003-3578-4477
Jillian IrelandPublic Health Scotland (PHS), Edinburgh, Scotland.
Rachel PorteousPublic Health Scotland (PHS), Edinburgh, Scotland.
Katie BorlandPublic Health Scotland (PHS), Edinburgh, Scotland.
Catalina A VallejosAlan Turing Institute, London, United Kingdom.ORCID https://orcid.org/0000-0003-3638-1960
Louis J M AslettAlan Turing Institute, London, United Kingdom.ORCID https://orcid.org/0000-0003-2211-233X
James LileyAlan Turing Institute, London, United Kingdom.ORCID https://orcid.org/0000-0002-0049-8238

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The Scottish Patients at Risk of Re-Admission and Admission (SPARRA) score predicts individual risk of emergency hospital admission for approximately 80% of the Scottish population. It was developed using routinely collected electronic health records, and is used by primary care practitioners to inform anticipatory care, particularly for individuals with high healthcare needs. We comprehensively assess the SPARRA score across population subgroups defined by age, sex, ethnicity, socioeconomic deprivation, and geographic location. For these subgroups, we consider differences in overall performance, score distribution, and false positive and negative rates, using causal methods to identify effects mediated through age, sex, and deprivation. We show that the score is well-calibrated across subgroups, but that rates of false positives and negatives vary widely, mediated by various causes including variability in demographic characteristics, admission reasons, and potentially differential data availability. Our work assists practitioners in the application and interpretation of the SPARRA score in population subgroups.

Identifiers

PMID39689107
PMCPMC11651550

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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.