Aurora, Colo.-based UCHealth is collaborating with industry innovators and startups within a virtual lab to research and develop emerging health care technologies. The UCHealth CARE Innovation Center’s new Applied Decision Science Lab (ADSL) will focus 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 brings together experts in clinical care delivery, informatics analytics, process, quality, outcomes and implementation science to partner with industry to create innovative solutions to modern health care challenges, according to a press release. The ADSL focuses on using established best practices, big data, artificial intelligence (AI) and machine learning to develop ways to dynamically inform clinicians in their electronic health record (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.
"We as health care providers are overwhelmed with data on how best to treat patients, and it’s only getting more acute. No human can possibly ingest, retain and apply this volume of data on an ongoing basis,” Richard Zane, M.D., UCHealth chief innovation officer and professor and chair of emergency medicine at the CU School of Medicine, said in a statement “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 data as well as the emerging use of artificial intelligence. Unless this is done in ways clinicians will embrace and use, the knowledge is wasted.”
The ADSL has already made progress in improving clinician adoption of decision support technology while eliminating unwanted and commonly ignored alerts that lead to “alert fatigue,” as widely documented, according to UCHealth. One example includes UCHealth’s work with Silicon Valley startup LeanTaaS to apply data science and predictive analytics to health care operations – resulting in improved efficiencies in OR utilization and a significant reduction in wait times and increased capacity at infusion centers. Another success is UCHealth’s partnership with digital health company RxRevu. Their technology integrates directly with the EHR to provide critical prescription information to providers within the clinical workflow.
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