Early-stage assessment of investigational digital technologies in mental health: a guide for innovators

Digital technologies, including artificial intelligence, hold great promise for transforming mental health care by enhancing diagnosis, personalizing treatments, and improving patient support. However, many innovations fail to reach clinical practice due to challenges in development and implementation. In this paper we address the implementation issue, whereby we introduce Early-stage Health Technology Assessment (eHTA) as a systematic approach to guide the development of digital technologies in mental health care. eHTA involves evaluating a technology's potential clinical benefits, economic value, and feasibility at an early stage. We present a five-step framework to assist developers of these inventions: (1) assessing the degree of innovation by determining how the new technology differs from existing solutions; (2) defining the target product profile by outlining its intended use, target population, and key features; (3) selecting an appropriate payment model by identifying who will pay for the technology and understanding their expectations; (4) translating clinical benefits into economically meaningful outcomes important to payers, such as improved clinical outcomes or cost savings; and (5) determining a pricing strategy that reflects the technology's value while remaining acceptable to payers and accessible to patients. By following these steps, innovators can align their technologies with clinical needs, generate necessary evidence, and create strategies for successful integration into mental health services. Incorporating early HTA in the development process is crucial for maximizing both the clinical impact and the successful adoption of digital technologies in mental health care.