Evidence map›Paper›PMID 31013860›Full record

ArticleInternational journal of environmental research and public health2019

Predictors of Discharge Against Medical Advice in a Tertiary Paediatric Hospital.

Louise Sealy, Karen Zwi, Gordon McDonald, Aldo Saavedra, Lisa Crawford, Hasantha Gunasekera

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in International journal of environmental research and public health, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed, 1 pooled it
5.2field-weighted citation impact, top 5% 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

16 citing papers in PubMed, 1 synthesis or guideline pooled it, 40 citations in OpenAlex.

  1. Pooled it
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  14. Predictors of In-Hospital Mortality in Aboriginal Children Admitted to a Tertiary Paediatric Hospital.International journal of environmental research and public health · 2019
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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 at 3 institutions in 1 country.

Louise SealyCommunity Child Health, Sydney Children's Hospital, Randwick, NSW 2031, Australia. louise.sealy@health.nsw.gov.au.
Karen ZwiCommunity Child Health, Sydney Children's Hospital, Randwick, NSW 2031, Australia. karen.zwi@health.nsw.gov.au.
Gordon McDonaldSydney Informatics Hub, The University of Sydney, Sydney, NSW 2008, Australia. gordon.mcdonald@sydney.edu.au.ORCID 0000-0002-2890-527X
Aldo SaavedraCentre for Translational Data Science; The University of Sydney, Sydney, NSW 2006, Australia. aldo.saavedra@sydney.edu.au.
Lisa CrawfordThe Children's Hospital at Westmead, Sydney, NSW 2145, Australia. dixie@sourcenation.com.au.
Hasantha GunasekeraThe Children's Hospital at Westmead, Sydney, NSW 2145, Australia. hasantha.gunasekera@health.nsw.gov.au.ORCID 0000-0003-4900-1277
The University of Sydney · AUSydney Children's Hospital · AUChildren's Hospital at Westmead · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPatients who discharge against medical advice (DAMA) from hospital carry a significant risk of readmission and have increased rates of morbidity and mortality. We sought to identify the demographic and clinical characteristics of DAMA patients from a tertiary paediatric hospital.

methodsData were extracted retrospectively from electronic medical records for all inpatient admissions over a 5-year period. Demographic characteristics (age, sex, Aboriginality, socioeconomic status and remoteness of residence) and clinical characteristics (admitting hospital site, level of urgency on admission, diagnosis and previous DAMA) were extracted and logistic regression models were used to identify predictors of DAMA with 95% confidence intervals.

resultsThere were 246,359 admissions for 124,757 patients, of which 1871 (0.8%) admissions and 1730 patients (1.4%) DAMA. Predictors of DAMA in a given admission were hospital site (OR 4.8, CI 4.2-5.7,

conclusionsThere are clear predictors of DAMA in this tertiary hospital admission cohort and identification of these provides opportunities for intervention at a practice and policy level in order to prevent adverse outcomes.

Indexed as

Hospitals, PediatricPatient DischargeTertiary Care CentersAgedChildCohort StudiesCounselingDemographyElectronic Health RecordsFemaleHospitalizationHumansInpatientsLogistic ModelsMaleMiddle Ageddischargedischarge against medical advicedischarge at own riskself-dischargetreatment refusal

Identifiers

PMID31013860
PMCPMC6518110
OpenAlexW2938822374

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.