📣: 𝗪𝗵𝗼 𝗶𝘀 𝘁𝗵𝗶𝘀 𝗳𝗼𝗿? Healthcare leaders designing, implementing, or evaluating AI-enabled solutions who need a rigorous, systems-level approach that complements technical validation — one that accounts for operational realities, governance, regulations, privacy, and stakeholder engagement. 𝗪𝗵𝗮𝘁 𝗶𝘀 𝗶𝘁? Using a real-world leadership context, this use case features Dr. Kathleen Pajer, Director of the Precision Child and Youth Mental Health (PCYMH) Collaboratory at the CHEO Research Institute. It documents how Dr. Pajer, Christina Honeywell (Co-Director), and their team worked with me, as the external evaluation specialist at Vitus Consulting, to apply the RECAP© framework and make their program more legible for decision-making. 𝗥𝗘𝗖𝗔𝗣© (RISK, EVIDENCE, CONTEXT, ASSUMPTIONS, PEOPLE) is a structured analytic tool grounded in Results-Based Management. 𝗪𝗵𝘆 𝗶𝘁 𝗺𝗮𝘁𝘁𝗲𝗿𝘀? Recent systematic reviews (in comments) on AI implementation in healthcare have identified comprehensive monitoring and evaluation (M&E) as a critical enabler of success. Yet evaluations beyond model metrics or patient satisfaction are rare. A systems perspective is needed — one that makes the work visible to all stakeholders, and creates a shared understanding of what real-world implementation entails. As Dr. Pajer explains: 𝘐𝘯 𝘢 𝘯𝘦𝘸 𝘧𝘪𝘦𝘭𝘥 𝘭𝘪𝘬𝘦 𝘱𝘳𝘦𝘤𝘪𝘴𝘪𝘰𝘯 𝘮𝘦𝘯𝘵𝘢𝘭 𝘩𝘦𝘢𝘭𝘵𝘩, 𝘳𝘦𝘴𝘶𝘭𝘵𝘴 𝘥𝘰𝘯'𝘵 𝘧𝘭𝘰𝘸 𝘢𝘶𝘵𝘰𝘮𝘢𝘵𝘪𝘤𝘢𝘭𝘭𝘺 𝘧𝘳𝘰𝘮 𝘢𝘤𝘵𝘪𝘷𝘪𝘵𝘪𝘦𝘴; 𝘵𝘩𝘦 𝘱𝘢𝘵𝘩𝘸𝘢𝘺𝘴 𝘣𝘦𝘵𝘸𝘦𝘦𝘯 𝘵𝘩𝘦𝘮 𝘴𝘩𝘪𝘧𝘵 𝘢𝘴 𝘦𝘷𝘪𝘥𝘦𝘯𝘤𝘦, 𝘱𝘢𝘳𝘵𝘯𝘦𝘳𝘴, 𝘢𝘯𝘥 𝘤𝘰𝘯𝘵𝘦𝘹𝘵 𝘤𝘩𝘢𝘯𝘨𝘦. 𝘞𝘦 𝘶𝘴𝘦𝘥 𝘙𝘌𝘊𝘈𝘗© 𝘵𝘰 𝘪𝘯𝘵𝘦𝘳𝘳𝘰𝘨𝘢𝘵𝘦 𝘵𝘩𝘢𝘵 '𝘪𝘯-𝘣𝘦𝘵𝘸𝘦𝘦𝘯' 𝘴𝘱𝘢𝘤𝘦. 𝘐𝘵 𝘨𝘢𝘷𝘦 𝘶𝘴 𝘢 𝘴𝘵𝘳𝘶𝘤𝘵𝘶𝘳𝘦𝘥 𝘸𝘢𝘺 𝘵𝘰 𝘴𝘶𝘳𝘧𝘢𝘤𝘦 𝘢𝘯𝘥 𝘵𝘦𝘴𝘵 𝘵𝘩𝘦 𝘳𝘪𝘴𝘬𝘴, 𝘦𝘷𝘪𝘥𝘦𝘯𝘤𝘦 𝘨𝘢𝘱𝘴, 𝘤𝘰𝘯𝘵𝘦𝘹𝘵𝘶𝘢𝘭 𝘳𝘦𝘢𝘭𝘪𝘵𝘪𝘦𝘴, 𝘢𝘴𝘴𝘶𝘮𝘱𝘵𝘪𝘰𝘯𝘴, 𝘢𝘯𝘥 𝘱𝘦𝘰𝘱𝘭𝘦-𝘳𝘦𝘭𝘢𝘵𝘦𝘥 𝘧𝘢𝘤𝘵𝘰𝘳𝘴 𝘵𝘩𝘢𝘵 𝘥𝘦𝘵𝘦𝘳𝘮𝘪𝘯𝘦 𝘸𝘩𝘦𝘵𝘩𝘦𝘳 𝘢𝘤𝘵𝘪𝘷𝘪𝘵𝘪𝘦𝘴 𝘢𝘤𝘵𝘶𝘢𝘭𝘭𝘺 𝘵𝘳𝘢𝘯𝘴𝘭𝘢𝘵𝘦 𝘪𝘯𝘵𝘰 𝘳𝘦𝘴𝘶𝘭𝘵𝘴. 𝗥𝗘𝗖𝗔𝗣© 𝗘𝘅𝗮𝗺𝗽𝗹𝗲: 𝗥𝗶𝘀𝗸: e.g., Data privacy 𝗘𝘃𝗶𝗱𝗲𝗻𝗰𝗲: e.g., Research article by [Author X] 𝗖𝗼𝗻𝘁𝗲𝘅𝘁: e.g., Canadian & Indigenous data sovereignty 𝗔𝘀𝘀𝘂𝗺𝗽𝘁𝗶𝗼𝗻: e.g., No major changes to AI regulation in Canada in the next 2 years 𝗣𝗲𝗼𝗽𝗹𝗲: e.g., Children & youth; caregivers 𝗪𝗵𝗮𝘁 𝘁𝗼 𝗱𝗼 𝗻𝗲𝘅𝘁? Both this leadership use case and the RECAP© framework are open access with citation (in comments). We hope it helps you in your work. Feel free to contact us with questions.

PCYMH Collaboratory is supported by funding from Waverley House Foundation