The value of artificial intelligence for the treatment of mechanically ventilated intensive care unit patients: an early health technology assessment

  • Highlights • Artificial intelligence systems for mechanically ventilated patients are increasing. • The clinical and financial impact of these models are often unexamined. • We developed a generic health-economic model for artificial intelligence systems. • This model assesses the cost-effectiveness for many different scenarios. • The developed framework is easily adjustable to other (clinical) situations. Abstract Purpose: The health and economic consequences of artificial intelligence (AI) systems for mechanically ventilated intensive care unit patients often remain unstudied. Early health technology assessments (HTA) can examine the potential impact of AI systems by using available data and simulations. Therefore, we developed a generic health-economic model suitable for early HTA of AI systems for mechanically ventilated patients. Materials and methods: Our generic health-economic model simulates mechanically ventilated patients from their hospitalisation until their death. The model simulates two scenarios, care as usual and care with the AI system, and compares these scenarios to estimate their cost-effectiveness. Results: The generic health-economic model we developed is suitable for estimating the cost-effectiveness of various AI systems. By varying input parameters and assumptions, the model can examine the cost-effectiveness of AI systems across a wide range of different clinical settings. Conclusions: Using the proposed generic health-economic model, investors and innovators can easily assess whether implementing a certain AI system is likely to be cost-effective before an exact clinical impact is determined. The results of the early HTA can aid investors and innovators in deployment of AI systems by supporting development decisions, informing value-based pricing, clinical trial design, and selection of target patient groups.

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Author:Leslie R. ZwerwerORCiD, Simon van der PolORCiDGND, Kai ZacharowskiORCiDGND, Maarten J. PostmaORCiD, Jan Andreas KlokaORCiDGND, Benjamin FriedrichsonORCiDGND, Antoinette D. I. van AsseltORCiDGND
URN:urn:nbn:de:hebis:30:3-837414
DOI:https://doi.org/10.1016/j.jcrc.2024.154802
ISSN:0883-9441
Parent Title (English):Journal of critical care
Publisher:Elsevier
Place of publication:Amsterdam
Document Type:Article
Language:English
Date of Publication (online):2024/04/06
Date of first Publication:2024/04/06
Publishing Institution:Universitätsbibliothek Johann Christian Senckenberg
Release Date:2024/04/15
Tag:Artificial intelligence; Cost-effectiveness; Critical care; Health technology assessment; Intensive care; Mechanical ventilation
Volume:82
Issue:154802
Article Number:154802
Page Number:10
HeBIS-PPN:519277759
Institutes:Medizin
Dewey Decimal Classification:6 Technik, Medizin, angewandte Wissenschaften / 61 Medizin und Gesundheit / 610 Medizin und Gesundheit
Sammlungen:Universitätspublikationen
Licence (German):License LogoCreative Commons - CC BY - Namensnennung 4.0 International