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Julia Zarb



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    OS05 - Mining the Gold! (ID 6)

    • Event: e-Health 2019 Virtual Meeting
    • Type: Oral Session
    • Track: Health Business Process
    • Presentations: 1
    • Coordinates: 5/27/2019, 10:30 AM - 11:30 AM, Pod 7
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      OS05.02 - The Role of Health Informatics Professionals in Making AI Happen (ID 347)

      Julia Zarb, IHPME, University of Toronto; Toronto/CA

      • Abstract
      • Slides

      Purpose/Objectives:
      Artificial Intelligence in healthcare is, arguably, a solution in search of a problem. It is rife with potential in the domain of improving patient care and outcomes, yet who is leading the vanguard to make this actually happen? Despite our healthcare community valuation of collaboration, we see a proliferation of silos emerging to lead the challenges of integrating AI into the field. This presentation will consider whether such fragmentation in pursuit of AI excellence risks HI history repeating itself with cycles of missed opportunity, or whether more cohesive models for enhancing the ecosystem can emerge. The presentation will take the perspective that health informatics professionals are well positioned to make AI happen in healthcare?s complex system of systems. We have learned (the hard way via compromised projects and implementations) the critical importance of management and evaluation to prepare for change and ensure viability through adoption. As such, we are uniquely positioned to navigate ?upstream? challenges at organizational and systemic levels, where accountability and accrual of benefits are concentrated, to ensure the ?downstream? move into actual use of AI technologies to maximum advantage.


      Methodology/Approach:
      The presentation will investigate the current landscape of AI advancement in healthcare. It will build perspective from capstone and executive-stream projects underway within the Master of Health Informatics (MHI) at University of Toronto, under the leadership of presenter Julia Zarb. Content may be drawn from alumni contribution of a machine-learning algorithm to evaluate such activities, and will be developed with input from the MHI Modernization Committee. The presenter will draw on work underway as the Director of the MHI program, and in collaboration with Emily Seto, health informatics lead for the Institute of Health Policy, Management and Evaluation.


      Finding/Results:
      The presentation will deliver a comparison of current Canadian models for upstream AI leadership in healthcare, with specific references to viable cases for collaborative activity. The findings will reflect work underway within University of Toronto and within the local community, with extension into the province and nation with possible reference to international cases. The presentation will suggest critical considerations and viable models for building next generations of AI-competent professionals to manage upstream to maximize downstream viability of new technologies.


      Conclusion/Implications/Recommendations:
      Attendees will emerge with an understanding of the current state of AI upstream leadership in Canadian healthcare, and a sense of potential models for collaborative advancement. The presentation will contain recommendations on how to realistically move forward in planning for a full scope of AI integration, using lessons-learned in health informatics.


      140 Character Summary:
      AI in healthcare is a topic filled with hope and hype. HI professionals can use lessons learned about managing upstream to ensure downstream AI success.

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