TY  - JOUR
A1  - Zwerwer, Leslie R.
A1  - Pol, Simon van der
A1  - Zacharowski, Kai
A1  - Postma, Maarten J.
A1  - Kloka, Jan Andreas
A1  - Friedrichson, Benjamin
A1  - Asselt, Antoinette D. I. van
T1  - The value of artificial intelligence for the treatment of mechanically ventilated intensive care unit patients: an early health technology assessment
T2  - Journal of critical care
N2  - 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.
KW  - Artificial intelligence
KW  - Critical care
KW  - Intensive care
KW  - Mechanical ventilation
KW  - Cost-effectiveness
KW  - Health technology assessment
Y1  - 2024
UR  - http://publikationen.ub.uni-frankfurt.de/frontdoor/index/index/docId/83741
UR  - https://nbn-resolving.org/urn:nbn:de:hebis:30:3-837414
SN  - 0883-9441
VL  - 82
IS  - 154802
PB  - Elsevier
CY  - Amsterdam
ER  -