Evidence map›Paper›PMID 40044603›Full record

ArticleAustralasian journal on ageing2025

Health-care staff perspectives in optimising delirium prevention using data-driven interventions.

Swapna Gokhale, Belinda Garth, Melinda Webb-St Mart, David Taylor, Nikolajs Zeps, Joanne Enticott, Helena Teede, Sandy Reeder

Abstract read
In one paragraph

Article in Australasian journal on ageing, 2025. 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
  2. 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.

Swapna GokhaleMonash Centre for Health Research and Implementation, Faculty of Medicine, Nursing, and Health Sciences, Monash University, Clayton, Victoria, Australia.ORCID https://orcid.org/0000-0002-0705-834X
Belinda GarthMonash Centre for Health Research and Implementation, Faculty of Medicine, Nursing, and Health Sciences, Monash University, Clayton, Victoria, Australia.
Melinda Webb-St MartEastern Health, Box Hill, Victoria, Australia.
David TaylorOffice of Research and Ethics, Eastern Health, Box Hill, Victoria, Australia.
Nikolajs ZepsMonash Partners Academic Health Sciences Centre, Clayton, Victoria, Australia.
Joanne EnticottMonash Centre for Health Research and Implementation, Faculty of Medicine, Nursing, and Health Sciences, Monash University, Clayton, Victoria, Australia.
Helena TeedeMonash Centre for Health Research and Implementation, Faculty of Medicine, Nursing, and Health Sciences, Monash University, Clayton, Victoria, Australia.
Sandy ReederMonash Centre for Health Research and Implementation, Faculty of Medicine, Nursing, and Health Sciences, Monash University, Clayton, Victoria, Australia.

Funding

Eastern HealthEpworth HealthcareMonash University
6 · The paper itself

Abstract

objectivesThis study aimed to identify factors influencing delirium prevention (risk identification and screening), from the perspective of health service staff, in order to ascertain the characteristics and implementation strategies critical for the clinical adoption of data-driven optimisations for delirium prevention. This pre-implementation study used the Monash Learning Health System (LHS) paradigm to visualise iterative integrated assimilation of delirium prevention in routine care.

methodsA qualitative study was conducted in a large metropolitan public health network in Australia. Following consultation with organisational leaders, a purposive sample of clinical/non-clinical participants with expertise in delirium care delivery was recruited. Interviews were inductively analysed using a framework approach. The Consolidated Framework for Implementation Research (CFIR) domains underpinned interview questions and guided thematic mapping and analysis of responses.

resultsSemi-structured interviews were conducted with 18 participants (clinical [n = 14] and non-clinical [n = 4]). Key themes included challenges in consistently integrating delirium risk identification and screening processes into clinical workflows, infrastructure-related obstacles hindering the digitisation of decision support, and the need to engage caregivers and staff in designing optimisations to enable appropriate and timely delirium prevention.

conclusionsThis study generated insights into key factors influencing delirium prevention, focusing on the development and implementation of optimisations such as automated delirium risk prediction. Improving hospital information technology infrastructure, supporting workforce digital literacy and ensuring accountability in all professional groups are crucial for implementing automated delirium risk prediction models in clinical practice. Future research should examine the feasibility and efficacy of optimised delirium prevention interventions in pragmatic clinical trials.

Indexed as

Attitude of Health PersonnelDeliriumHealth Knowledge, Attitudes, PracticeHealth PersonnelAdultFemaleHumansInterviews as TopicMaleMiddle AgedPredictive Value of TestsQualitative ResearchRisk AssessmentRisk FactorsWorkflowdata‐driven optimisationdelirium preventionhealth services researchlearning health systempre‐implementation factors

Identifiers

PMID40044603
PMCPMC11882484

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.