Evidence map›Paper›PMID 40526627›Full record

ArticleSociology of health & illness2025

Relational Ethics in the Administration of Healthcare Technology: AI, Automation and Proper Distance.

Frances Shaw, Anthony McCosker

Abstract read
In one paragraph

Article in Sociology of health & illness, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
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

2 authors.

Frances ShawARC Centre of Excellence for Automated Decision-Making and Society (ADM+S), Swinburne University of Technology, Hawthorn, Australia.ORCID 0000-0001-8690-653X
Anthony McCoskerARC Centre of Excellence for Automated Decision-Making and Society (ADM+S), Swinburne University of Technology, Hawthorn, Australia.

Funding

Australian Research Council CE200100005
6 · The paper itself

Abstract

Automation and AI-driven decision support systems are increasingly reshaping healthcare, particularly in diagnostic and clinical management contexts. Although their potential to enhance access, efficiency and personalisation is widely recognised, there remain ethical concerns especially around the shifting dynamics of healthcare relationships. This article proposes a conceptual framework for understanding the relational ethics of healthcare automation, drawing on the work of Levinas and Silverstone to interrogate the ethical implications embedded in regulatory processes. Focusing on the Australian Therapeutic Goods Administration (TGA) database, we analyse clinical decision support system (CDSS) approvals to examine how healthcare relationships are discursively constructed within regulatory documentation. Through close reading of these technical and administrative texts, we investigate how ethical concerns such as patient autonomy, informed consent and trust are acknowledged or elided. Our findings reveal a limited framing of relational dimensions in regulatory discourse, raising important questions about how ethics are operationalised in the oversight of automated systems. By making visible the administrative practices shaping healthcare automation, this study contributes to emerging debates on AI governance and the ethical integration of automation into clinical practice.

Indexed as

Artificial IntelligenceAutomationDecision Support Systems, ClinicalDelivery of Health CareAustraliaHumansInformed ConsentPersonal AutonomyTrust

Identifiers

PMID40526627
PMCPMC12173213

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.