Evidence map›Paper›PMID 36494574›Full record

ArticleApplied health economics and health policy2023

Cost-Effectiveness and Value of Information Analysis of an Ambient Intelligent Geriatric Management (AmbIGeM) System Compared to Usual Care to Prevent Falls in Older People in Hospitals.

Clarabelle T Pham, Renuka Visvanathan, Mark Strong, Edward C F Wilson, Kylie Lange, Joanne Dollard, Damith Ranasinghe, Keith Hill, Anne Wilson, Jonathan Karnon

Open access · greenAbstract read
PubMed Publisher
In one paragraph

Article in Applied health economics and health policy, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 2 pooled it
1.2field-weighted citation impact, top 21% 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

7 citing papers in PubMed, 2 syntheses or guidelines pooled it, 8 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Review
  5. Article
  6. Article
  7. 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

10 authors at 7 institutions in 2 countries.

Clarabelle T PhamFlinders Health and Medical Research Institute, Flinders University, Bedford Park, SA, Australia. clara.pham@flinders.edu.au.ORCID http://orcid.org/0000-0003-4509-5368
Renuka VisvanathanAged and Extended Care Services, The Queen Elizabeth Hospital, Central Adelaide Local Health Network and Adelaide Geriatrics Training and Research with Aged Care (GTRAC) Centre, Adelaide Medical School, Faculty of Health and Medical Sciences, University of Adelaide, Adelaide, SA, Australia.
Mark StrongSchool of Health and Related Research, The University of Sheffield, Sheffield, UK.
Edward C F WilsonPeninsula Technology Assessment Group, College of Medicine and Health, University of Exeter, Exeter, UK.
Kylie LangeCentre of Research Excellence in Translating Nutritional Science to Good Health, Adelaide Medical School, The University of Adelaide, Adelaide, SA, Australia.
Joanne DollardAdelaide Geriatrics Training and Research with Aged Care (GTRAC) Centre, Adelaide Medical School, Faculty of Health and Medical Sciences, University of Adelaide, Basil Hetzel Institute for Translational Health Research, Central Adelaide Local Health Network, Adelaide, SA, Australia.
Damith RanasingheThe Auto-ID Lab, The School of Computer Science, University of Adelaide, Adelaide, SA, Australia.
Keith HillRehabilitation Ageing and Independent Living (RAIL) Research Centre, Monash University, Melbourne, VIC, Australia.
Anne WilsonCollege of Medicine and Public Health, Flinders University, Bedford Park, SA, Australia.
Jonathan KarnonFlinders Health and Medical Research Institute, Flinders University, Bedford Park, SA, Australia.
Flinders University · AUThe University of Adelaide · AUBasil Hetzel Institute · AUMonash University · AUQueen Elizabeth Hospital · AUUniversity of Exeter · GBUniversity of Sheffield · GB

Funding

National Health and Medical Research Council of Australia 1082197
6 · The paper itself

Abstract

backgroundThe Ambient Intelligent Geriatric Management (AmbIGeM) system combines wearable sensors with artificial intelligence to trigger alerts to hospital staff before a fall. A clinical trial found no effect across a heterogenous population, but reported a reduction in the injurious falls rate in a post hoc analysis of patients on Geriatric Evaluation Management Unit (GEMU) wards. Cost-effectiveness and Value of Information (VoI) analyses of the AmbIGeM system in GEMU wards was undertaken.

methodsAn Australian health-care system perspective and 5-year time horizon were used for the cost-effectiveness analysis. Implementation costs, inpatient costs and falls data were collected. Injurious falls were defined as causing bruising, laceration, fracture, loss of consciousness, or if the patient reported persistent pain. To compare costs and outcomes, generalised linear regression models were used to adjust for baseline differences between the intervention and usual care groups. Bootstrapping was used to represent uncertainty. For the VoI analysis, 10,000 different sample sizes with randomly sampled values ranging from 1 to 50,000 were tested to estimate the optimal sample size of a new trial that maximised the Expected Net Benefits of Sampling.

resultsAn adjusted 0.036 fewer injurious falls (adjusted rate ratio of 0.56) and AUD$4554 lower costs were seen in the intervention group. However, uncertainty that the intervention is cost effective for the prevention of an injurious fall was present at all monetary values of this effectiveness outcome. A new trial with a sample of 4376 patients was estimated to maximise the Expected Net Benefit of Sampling, generating a net benefit of AUD$186,632 at a benefit-to-cost ratio of 1.1.

conclusionsThe benefits to cost ratio suggests that a new trial of the AmbIGeM system in GEMU wards may not be high-value compared to other potential trials, and that the system should be implemented. However, a broader analysis of options for preventing falls in GEMU is required to fully inform decision making.

trial registrationAustralian and New Zealand Clinical Trial Registry (ACTRN 12617000981325).

Indexed as

Accidental FallsArtificial IntelligenceAgedAustraliaCost-Benefit AnalysisHospitalsHumans

Identifiers

PMID36494574
OpenAlexW4311024064

What OpenQuestion holds

Textmetadata
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.