A life-cycle approach to digital health technology assessment

Area of Science:

• Health Technology Assessment
• Digital Health Technologies
• Medical Devices

Background:

• Traditional Health Technology Assessment (HTA) methods, rooted in Evidence-Based Medicine, struggle with the complexity of modern digital health technologies (DHTs) and software-driven devices, including Artificial Intelligence.
• The increasing importance and rapid evolution of DHTs necessitate a shift from single assessments to a more comprehensive evaluation approach.
• Regulators and HTA bodies recognize the need for product life cycle-based evaluations, but practical frameworks are not yet widely implemented.

Purpose of the Study:

• To introduce and describe the Life-Cycle-Based Evaluation (LCBE) framework for assessing Digital Health Technologies (DHTs).
• To address the methodological challenges in evaluating the value of digital health technologies.
• To foster collaboration between developers, regulators, and HTA bodies for adaptive evaluations.

Main Methods:

• Development of the Life-Cycle-Based Evaluation (LCBE) framework under the ASSESS-DHT Horizon Europe 2020 project.
• The framework is designed for early, proportionate, and continuous assessment of DHTs.
• Pilot studies are currently underway to evaluate the LCBE framework's practical application.

Main Results:

• The LCBE framework provides a structured approach to evaluate DHTs throughout their product life cycle.
• It aims to enable timely, rigorous, and adaptive assessments.
• The framework is intended to support collaboration among stakeholders involved in DHT development and regulation.

Conclusions:

• The Life-Cycle-Based Evaluation (LCBE) framework offers a promising approach to address the limitations of traditional HTA for digital health technologies.
• Continuous and adaptive evaluation across the product life cycle is crucial for ensuring the value and safety of DHTs.
• The LCBE framework has the potential to improve the assessment process for rapidly evolving technologies like AI-driven medical devices.