TY - JOUR
T1 - 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
AU - Pham, Clarabelle T.
AU - Visvanathan, Renuka
AU - Strong, Mark
AU - Wilson, Edward C.F.
AU - Lange, Kylie
AU - Dollard, Joanne
AU - Ranasinghe, Damith
AU - Hill, Keith
AU - Wilson, Anne
AU - Karnon, Jonathan
N1 - Funding Information:
We would like to thank SA Health (Tomi Adejoro) and WA Health (Ian Massingham) for support and provision of data. We would also like to acknowledge the clinical, administrative and information technology staff from both hospitals, the research staff and students that supported the conduct of the trial.
Publisher Copyright:
© 2022, The Author(s), under exclusive licence to Springer Nature Switzerland AG.
PY - 2023/3
Y1 - 2023/3
N2 - Background: The 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. Methods: An 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. Results: An 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. Conclusions: The 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 Registration: Australian and New Zealand Clinical Trial Registry (ACTRN 12617000981325).
AB - Background: The 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. Methods: An 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. Results: An 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. Conclusions: The 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 Registration: Australian and New Zealand Clinical Trial Registry (ACTRN 12617000981325).
UR - http://www.scopus.com/inward/record.url?scp=85143590613&partnerID=8YFLogxK
U2 - 10.1007/s40258-022-00773-6
DO - 10.1007/s40258-022-00773-6
M3 - Article
C2 - 36494574
AN - SCOPUS:85143590613
SN - 1175-5652
VL - 21
SP - 315
EP - 325
JO - Applied Health Economics and Health Policy
JF - Applied Health Economics and Health Policy
IS - 2
ER -