Evidence map›Paper›PMID 39471234›Full record

ArticlePloS one2024

Clinical and socioeconomic predictors of hospital use and emergency department visits among children with medical complexity: A machine learning approach using administrative data.

Michael Sidra, Matthew Pietrosanu, Jennifer Zwicker, David Wyatt Johnson, Jeff Round, Arto Ohinmaa

Abstract read
In one paragraph

Article in PloS one, 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

6 authors.

Michael SidraSchool of Public Health, University of Alberta, Edmonton, Canada.ORCID 0000-0003-3485-4437
Matthew PietrosanuDepartment of Mathematical and Statistical Sciences, University of Alberta, Edmonton, Canada.
Jennifer ZwickerFaculty of Kinesiology, School of Public Policy, University of Calgary, Calgary, Canada.ORCID 0000-0002-0722-5929
David Wyatt JohnsonDepartment of Pediatrics, University of Calgary, Calgary, Canada.
Jeff RoundSchool of Public Health, University of Alberta, Edmonton, Canada.
Arto OhinmaaSchool of Public Health, University of Alberta, Edmonton, Canada.ORCID 0000-0002-7094-1573

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesThe primary objective of this study was to identify clinical and socioeconomic predictors of hospital and ED use among children with medical complexity within 1 and 5 years of an initial discharge between 2010 and 2013. A secondary objective was to estimate marginal associations between important predictors and resource use.

methodsThis retrospective, population-cohort study of children with medical complexity in Alberta linked administrative health data with Canadian census data and used tree-based, gradient-boosted regression models to identify clinical and socioeconomic predictors of resource use. Separate analyses of cumulative numbers of hospital days and ED visits modeled the probability of any resource use and, when present, the amount of resource use. We used relative importance in each analysis to identify important predictors.

resultsThe analytic sample included 11 105 children with medical complexity. The best short- and long-term predictors of having a hospital stay and number of hospital days were initial length of stay and clinical classification. Initial length of stay, residence rurality, and other socioeconomic factors were top predictors of short-term ED use. The top predictors of ED use in the long term were almost exclusively socioeconomic, with rurality a top predictor of number of ED visits. Estimates of marginal associations between initial length of stay and resource use showed that average number of hospital days increases as initial length of stay increases up to approximately 90 days. Children with medical complexity living in rural areas had more ED visits on average than those living in urban or metropolitan areas.

conclusionsClinical factors are generally better predictors of hospital use whereas socioeconomic factors are more predictive of ED use among children with medical complexity in Alberta. The results confirm existing literature on the importance of socioeconomic factors with respect to health care use by children with medical complexity.

Indexed as

Emergency Service, HospitalLength of StayMachine LearningSocioeconomic FactorsAdolescentAlbertaChildChild, PreschoolEmergency Room VisitsFemaleHospitalizationHumansInfantInfant, NewbornMaleRetrospective Studies

Identifiers

PMID39471234
PMCPMC11521260

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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.