Evidence map›Paper›PMID 38124197›Full record

ArticleJournal of medical ethics2024

As low as reasonably practicable (ALARP): a moral model for clinical risk management in the setting of technology dependence.

Helen Lynne Turnham, Sarah-Jane Bowen, Sitara Ramdas, Andrew Smith, Dominic Wilkinson, Emily Harrop

Abstract read
In one paragraph

Article in Journal of medical ethics, 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

6 authors.

Helen Lynne TurnhamOxford University Hospitals NHS Foundation Trust, Oxford, UK.ORCID 0000-0003-1011-2885
Sarah-Jane BowenOxford University Hospitals NHS Foundation Trust, Oxford, UK.
Sitara RamdasOxford University Hospitals NHS Foundation Trust, Oxford, UK.
Andrew SmithRoyal Aeronautical Society, London, UK.
Dominic WilkinsonOxford University Hospitals NHS Foundation Trust, Oxford, UK dominic.wilkinson@philosophy.ox.ac.uk.
Emily HarropHelen and Douglas House, Oxford, UK.ORCID 0000-0002-2480-2062

Funding

Wellcome TrustWellcome Trust 203132/Z/16/Z
6 · The paper itself

Abstract

Children dependent on life-prolonging medical technology are often subject to a constant background risk of sudden death or catastrophic complications. Such children can be cared for in hospital, in an intensive care environment with highly trained nurses and doctors able to deliver specialised, life-saving care immediately. However, remaining in hospital, when life expectancy is limited, can considered to be a harm in of itself. Discharge home offers the possibility for an improved quality of life for the child and their family but comes with significant medical risks.When making decisions for children, two ethical models predominate, the promotion of the child's best interests or the avoidance of harm. However, in some circumstances, particularly for children with life-limiting and/or life-threatening illness, all options may be associated with risk. There are no good options, only potentially harmful choices.In this paper, we explore decisions made by one family in such circumstances. We describe a model adopted from risk management programmes beyond medicine, which offers a potential framework for identifying risks to the child that are morally permissible. Some risks and harms to a child, not ordinarily permitted, may be acceptable when undertaken in the pursuit of a specified desired good, so long as they are as low as reasonably practicable.

Indexed as

Risk ManagementBiomedical TechnologyChildDecision MakingHumansMoralsQuality of LifeChildDecision MakingEthics- MedicalParental Consent

Identifiers

PMID38124197
PMCPMC11503141

What OpenQuestion holds

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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.