• Nonprofit health system UC Health has formed an innovation lab focused on developing more effective ways to use decision support science to reduce clinical variation, streamline provider workflows, enhance clinician decision making and improve overall patient care. The UCHealth CARE Innovation Center’s new   will collaborate with both internal and external innovators, as well as industry partners, to better understand how these stakeholders can both contribute to decision support science, and to help collaborators understand how the application of this new decision support science will transform their business’ existing and emerging business models.

    As the volume of big data from multiple sources becomes available to inform health care practices, providers are increasingly challenged to ingest all of this information to personalize care for each patient. As an innovation incubator, the ADSL examines how to make this complex data easy to use by clinicians, driving lower costs and better outcomes for patients. Clinical decision support technology will also be the required infrastructure to effectively apply AI and machine learning in the clinical workflow in the future.

    ADSL’s Decision Support R&D Ecosystem

    UCHealth Launches Innovation Center to Develop AI-Powered Decision Support Solutions

    By leveraging established best practices, big data, artificial intelligence (AI) and machine learning, ADSL will develop ways to dynamically inform clinicians in their EHR-based clinical workflows, including:

    – Supporting clinicians in utilizing the best and most current evidence-based standards through rules-based algorithms.

    – Developing methods to effectively utilize learning-based algorithms (AI and machine learning) to integrate into decision support technologies.

    – Improving the provider experience and reducing clinician burnout from difficult-to-use technology.

    – Helping other industry stakeholders understand how clinical decision support technology will change clinician behavior at the point of care.

    “Making this data actionable in the real-world clinical workflow is incredibly challenging. We must focus on the point of care application of all this knowledge we generate as well as how artificial intelligence can effectively impact decision making. This must be done in ways clinicians will embrace and use or this knowledge is wasted.” – Dr. Richard Zane, UCHealth chief innovation officer and professor and chair of Emergency Medicine at the CU School of Medicine in a statement.

    Progress to Date

    The lab has already made significant progress in improving clinician adoption of decision support technology in its work with Silicon Valley startup LeanTaaS to apply data science and predictive analytics to healthcare operations. The collaboration has resulted in  improved efficiencies in OR utilization and a significant reduction in wait times and increased capacity at their infusion centers.In addition, UCHealth has partnered with digital health company RxRevu to integrate with its existing Epic EHR to provide critical prescription information to providers within the clinical workflow.

    For UCHealth, the ADSL will help put them at the forefront of transforming healthcare through AI.

    We recommend

    1. HIT Consultant, 2017
    2. HIT Consultant, 2014
    3. HIT Consultant, 2017
    4. HIT Consultant, 2017
    5. HIT Consultant, 2017
    1. Maribel Cifuentes, RN, BSN, et al., Medscape, 2015
    2. 360Dx, 2017
    3. Neil Versel, Medscape, 2014
    4. Blake Lesselroth et al., Medscape, 2008
    5. Sanjeev P. Bhavnani et al., Medscape, 2016
     
     

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