Selection of Key Performance Indicators for an Economic Evaluation of Artificial Intelligence Technologies: The Case of Hosmartai (HORIZON 2020 Funded Program)
Author(s)
Hatzikou M, O’ Byrne D, Latsou D
PharmEcons Easy Access Ltd, York, A1, UK
BACKGROUND: Artificial intelligence (AI) is mentioned as a facilitator for more personalized and safer healthcare services. The economic evaluation of AI has been addressed only sporadically, although used by policymakers for adopting new technology. Key Performance Indicators (KPIs) have long been utilized as measurable landmarks to evaluate the benefit for patients and society of AI. HosmartAI project combines in one platform an agglomeration of AI technologies, disease areas and healthcare settings.
OBJECTIVES:
The study aimed to identify the most important KPIs to perform an economic evaluation of 8 pilots, 11 medical scenarios and 1 administrative scenario.METHODS:
A challenge in the identification of KPIs for HosmartAI, was due to the diversity of technologies involved, requiring a variety of instruments for one or more KPIs for each specific technology on a proof of concept basis. Thus, a comprehensive selection of KPIs was performed, covering the whole spectrum of outcomes. The KPI pillars were: a) Clinical Efficacy/Effectiveness, b) Patient Reported Outcome Measures (PROMs), c) Patient/User Reported Experiences Measures (PREMs/UREMs), d) Productivity (hospital/healthcare setting) and e) Economic.RESULTS:
Based on the proposed KPIs, the pilots chose the appropriate ones to assess the economic evaluation of each technology. All pilots have chosen the following outcomes’ metrics: clinical effectiveness, hospital productivity, UREMs and economic analysis (100%), since they believed that the new AI technology will be more or similar efficacious to current practice, while reducing the examination time in a more user-friendly way. The second and third chosen outcome was PREM (41,6%) and PROM (27.3%) respectively.CONCLUSIONS:
In AI technologies, the choice of KPIs is not as straightforward as in other medical technologies/pharmaceuticals. KPIs represent an integral part of AI technologies to monitor effectively and optimize punctually healthcare services, improving patient outcomes and facilitating the reimbursement processes. However, outcomes should encompass both medical and engineering KPIs.Conference/Value in Health Info
2022-11, ISPOR Europe 2022, Vienna, Austria
Value in Health, Volume 25, Issue 12S (December 2022)
Code
EE32
Topic
Economic Evaluation, Health Policy & Regulatory, Methodological & Statistical Research
Topic Subcategory
Artificial Intelligence, Machine Learning, Predictive Analytics, Cost-comparison, Effectiveness, Utility, Benefit Analysis, Reimbursement & Access Policy
Disease
No Additional Disease & Conditions/Specialized Treatment Areas