International Consortium for Artificial Intelligence (AI) and Shared Decision Making (SDM)


There are several validated measurement methods to assess the extent to which health professionals use SDM-related behaviors and engage patients in decision-making from an observer perspective.  For example, OPTION and MAPPIN-SDM are widely used validated observational methods for this purpose.

Over the years, researchers internationally have created databases of observer ratings and associated audio/video recordings.

Artificial intelligence (AI) has the potential to standardize and streamline observer-based analysis and feedback from consultation recordings and could be incorporated into training programs, potentially enhancing efficiency, scale and spread.

Our consortium aims to develop research projects to support the implementation of SDM using AI.

Members and their students will have access to knowledge, networks and resources that can help them obtain research funding, conduct research projects, and collaborate with other stakeholders interested in exploring potential AI applications in SDM.

We are starting with a project on using AI to standardize the assessment of SDM processes during clinical consultations. Special Interest group members may have a range of interest areas within AI / SDM and are encouraged to explore these also.

  • Collaborative, with and utilizing strengths of the ISDM Society;
  • Equity, diversity, inclusion: from management to administration, partnership development, funding, ensuring diversity among staff, researchers, patient and public contributors and students, to attention to equity and diversity in its interdisciplinary research itself.
  • Diversity across career stage, researcher demographics and countries, disciplines supported
  • Inclusive for participation and outputs;

Becoming a member

You are warmly invited to register your interest and to become a member of the ISDM Special Interest Group on use of AI in SDM.

We encourage members with interests from both AI and SDM domains.

Please contact Justine Laloux:  justine.laloux.1@ulaval.ca 

Options for participation

To achieve the specific objectives, we are currently seeking to recruit three types of participants who will complete a survey or act as key informants in individual interviews.

To participate you should have:

  • Experience of using / researching AI applications in healthcare and/or
  • Experience of SDM training / research / implementation and/or
  • Databases of observer-based ratings and associated audio/video recordings

We will ask you which category-ies you identify with.  Ethical approval is being sought and full information will be provided, and your consent requested.

To participate, contact  justine.laloux.1@ulaval.ca

To develop grant applications on the use of AI for observer-based assessment of SDM processes during healthcare encounters as a basis for feedback and clinician training, we are currently seeking to form a research team.

To participate, applicants should be:

  • Researchers or
  • Supervised by a member or
  • A patient/consumer/citizen partner.

Member categories:

  • Research development group: researchers who wish to participate as co-investigators in the funding proposal (subject to receiving funding for salary, if allowed by the funding stream, and doing the work).
  • Collaborators: SDM experts whoown data from observational instruments and agree to collaborate with the consortium, or experts who wish to participate to networking activities and be listed as collaborators with grant application (without receiving salary)
  • Partner organization: We also invite organizations or networks to partner with us and to provide indication of support to the grant application.

Specifically, members are invited to participate virtually in two workshops over the next year, with a view to the grant application.

The first virtual workshop took place on 2-3 October 2023, and the second on 22 January 2024.  Future meeting dates are currently being planned.

We hope to be able to invite colleagues to participate in the funding proposal that will come out of this consortium, subject to the scale and eligibility of a chosen grant opportunity (please see Values).

To explore the potential of AI in SDM, including professional training and measurement, we have received a small funding award from the governments of Wales (UK) and Quebec (Canada).

Specific objectives for next year

  1. To establish a consortium of SDM and AI experts
  2. To develop an international inventory of existing observer-based SDM assessment data.
  3. To conduct an environmental scan to identify key experts, existing AI applications in SDM.
  4. To conduct interviews with key experts and to explore and prioritize areas where AI could support SDM training or implementation.
  5. To develop a proposal for a larger research project based on the results of the preliminary study.

The award recipients are:

Anik Giguere, Co-lead
Université Laval, Quebec City, Canada






Adrian Edwards, Co-lead
Cardiff University, Cardiff, UK






Denitza Williams
Cardiff University, Cardiff, UK





Samira Abbasgholizadeh-Rahimi
McGill University, Montreal, Canada






Natalie Joseph-Williams
Cardiff University, Cardiff, UK





France Légaré
Université Laval, Quebec City, Canada





Patient Partners

    Patient partner, Wales, UK

    Patient partner, Ontario, Canada

    Patient partner, Quebec, Canada

Other Researchers

    Amsterdam University Medical Centers, Amsterdam, The Netherlands

    Plateforme de Recherche, Données, Intelligence et Santé (PREDIS), Quebec City, Canada

    University of Exeter Medical School, Exeter, UK

    Université de Sherbrooke, Sherbrooke, Canada

    Université Laval, Quebec City, Canada

    Plateforme de Recherche, Données, Intelligence et Santé (PREDIS), Quebec City, Canada

    The Dartmouth Institute for Health Policy and Clinical Practice, USA, Lebanon, New Hampshire, USA

    The Netherlands Cancer Institute, Amsterdam, The Netherlands

    Susan B. Meister Child Health Evaluation and Research Center, Ann Arbor, Michigan, USA

    Institute for Evidence-Based Health, Bond University, Gold Coast, Australia

    Leiden University Medical Center, Leiden, The Netherlands / Mayo Clinic, Rochester, Minnesota, USA

    Plateforme de Recherche, Données, Intelligence et Santé (PREDIS), Quebec City, Canada

    Knowledge and Evaluation Research Unit, Mayo Clinic, Rochester, Minnesota, USA

    Lillebaelt Hospital-University Hospital of Southern Denmark, Vejle, Denmark

    UW-Madison School of Nursing, Madison, Wisconsin, USA

    Generative AI Team, Tempus AI, Redwood City, California, USA.

    University of Southampton, Southampton, UK

    Maastricht University, Maastricht, The Netherlands

    Lillebaelt Hospital-University Hospital of Southern Denmark, Vejle, Denmark

    Susan B. Meister Child Health Evaluation and Research Center, Ann Arbor, Michigan, USA

    Massachusetts General Hospital – Harvard Medical School, Boston, Massachusetts, USA

    Amsterdam University Medical Centers, Amsterdam, The Netherlan

    Monash University, Melbourne, Australia