Over the past decade, digital health solutions and those relying on artificial intelligence (hereafter called “D/AI solutions”) have exponentially grown and expanded research and health care practices in ways that were previously unthinkable. As health care providers and health systems worldwide will be on the frontline tackling the health effects of climate change and growing social and economic disparities, our team aimed to develop a rigorous tool that can measure the degree of responsibility of D/AI solutions by adapting the multidimensional and already validated Responsible Innovation in Health (RIH) Tool.
To do so, we conducted a three-phase mixed method study:
- In Phase 1, we performed a scoping review of practice-oriented tools (n=57) developed since 2015 to support the development and use of responsible and ethical D/AI solutions. We extracted from these tools up to 40 principles that were mapped against the RIH Tool to identify issues that are specific to D/AI solutions and were not covered in the RIH Tool. This mapping process led to a preliminary version of the ‘Responsible D/AI Solutions Assessment Tool.’
- In Phase 2, an international two-round e-Delphi expert panel rated on a five-level scale the importance, clarity, and appropriateness of the new Tool’s components (i.e., its premises, screening criteria, and assessment attributes).
- In Phase 3, two raters independently applied the revised Tool to a sample of D/AI solutions (n=25), interrater reliability was measured, and final minor changes were brought to the Tool.
The results of the scoping review were published (see below) and confirmed the need for a comprehensive, valid, and reliable tool to assess the degree of responsibility of D/AI health solutions. Because regulation remains limited in this rapidly evolving field, we believe that the new tool we developed has the potential to change practice towards more equitable as well as economically and environmentally sustainable digital health care.
Publications of interest to this project:
- Alami, H., Lehoux, P., Denis, JL., Motulsky, A., Petitgrand, C., Savoldelli, M., Rouquet, R., Gagnon, MP., Roy, D., Fortin, JP. (2020). Organizational readiness for artificial intelligence in health care: Insights for decision-making and practice. Journal of Health Organization and Management.
- Alami, H., Rivard, L., de Oliveira, R.R., Lehoux, P., Cadeddu, S., Savoldelli, M., Ag Ahmed, M.A., Fortin, J.-P. (2020). Extracting value from the way we live? Guiding health insurance models towards responsible digital innovations. Journal of Participatory Medicine. 12(3), e19586.
- Alami, H., Rivard, L., Lehoux, P., Hoffman, S. J., Cadeddu, SBM., Savoldelli, M., Samri, MA., Ag Ahmed, MA., Fleet, R., Fortin, JP. (2020). Artificial intelligence in health care: Laying the Foundation for Responsible, sustainable, and inclusive innovation in low- and middle-income countries. Globalization and Health. 16(1): 52.
- Lehoux, P. & Rivard, L. (2022). Major public works ahead for a healthy data-centric NHS, The BMJ.
- Lehoux, P., Rivard, L., de Oliveira, R. R., Mörch, C. M., & Alami, H. (2022). Tools to foster responsibility in digital solutions that operate with or without artificial intelligence: A scoping review for health and innovation policymakers. International Journal of Medical Informatics.
- Rivard, L., Lehoux, P. (2023). AI is not ready for the 21st century: What can business leaders do? The European Business Review. January 11, 2023.
- Rivard. L., Lehoux, P., Rocha de Oliveira, R., Alami, H. (2023). Thematic analysis of tools for health innovators and organisation leaders to develop digital health solutions fit for climate change. BMJ Leader.
- Lehoux, P., Rocha de Oliveira, R., Rivard, L., Silva, H. P., Alami, H. Mörch, C.-M., Malas, K. (2023). A comprehensive, valid, and reliable tool to assess the degree of responsibility of digital solutions that operate with or without artificial intelligence. 3-phase mixed methods study. Journal of Medical Internet Research.
Project Team Members: Lysanne Rivard
