Track 2: Computable Guidelines in the 21st Century

Computable Guidelines in the 21st Century:  Evidence-Based Knowledge Assets and Digital Quality

About This Track

The digital quality enterprise is increasingly supporting implementation of clinical practice recommendations at the point of care through transformation of evidence into computable guidelines. The new digital quality ecosystem is improving the value of the performance measurement process through its ability to generate knowledge that feeds computable clinical guidance.  The main question is at what threshold does the evidence point to the need to update this knowledge.

Learn how current crises are accelerating movement towards a learning health system where clinical effectiveness findings from the front lines can be effectively disseminated to improve care quality.

Track Leads

Maria Michaels

Maria Michaels is a Public Health Advisor at the Centers for Disease Control and Prevention, bringing health IT, health care, and research perspectives. She has served as Technical Lead/Program Manager for HITECH Clinical Quality Measure Policy and Operations at the Centers for Medicare and Medicaid Services and as Program Manager at the National Cancer Institute’s Cancer Human Biobank as well as with the health systems of Virginia Commonwealth University, where she directed Meaningful Use, and the Johns Hopkins University, where she developed and managed a large research program. She holds a BS in Biology and BS in Psychology from Virginia Commonwealth University, MBA from the Johns Hopkins University, and a PMP from the Project Management Institute.

Kristin Kostka

Kristin Kostka is an Associate Director at IQVIA running the OMOP Data Network and a perennial collaborator within the Observational Health Sciences and Informatics (OHDSI) community – a global, multi-disciplinary community of more than 200 organizations aimed at improving patient outcomes through large scale analytics. In her work, Kristin partners with hospitals, payers and healthcare providers to help organizations unlock the power of institutional data and connect with the world’s largest observational health data network.

Kristin has over 10 years of experience leading real-world evidence generation studies, designing and implementing enterprise patient data lakes, conducting large-scale multinational clinical trials and preparing regularly submissions. She is considered a preeminent voice in observational health research and data science traveling across the US, Europe, Middle East and Asia to deliver presentations on open science methodologies – including at the University of Oxford, Tufts Clinical and Translational Science Institute, Northwestern University and Fudan University. Kristin co-authored three chapters for the world’s first observational health open science textbook, the Book of OHDSI and has co-presented research on the world’s largest observational study predicting individual risk of developing breast cancer after a negative mammography.

Kristin is a recipient of many industry awards including: 2020 Elon University Young Alumni Council “Top 10 Under 10” Alumni Award, 2018 OHDSI Titan Award in Community Collaboration, a 3- time recipient of Deloitte Outstanding Performance Award and an 8-time recipient of the Deloitte Applause Award for exceptional client service. She holds a Bachelor’s degree in Exercise Science from Elon University and a Master’s in Public Health in Epidemiology from Boston University School of Public Health.

Track Faculty

Bryn Rhodes

Bryn Rhodes is a key contributor and Subject Matter Expert in HL7’s Clinical Quality Framework Initiative, primarily involved with the development and support of the Clinical Quality Language Specification. His expertise in Clinical Decision Support stems from implementation experience building a real-time Clinical Decision Support system for an industry leading Electronic Health Records system. With 20 years in software development, he has a broad range of implementation experience, from desktop client/server line-of-business and medical applications to enterprise and web-scale information systems. His career has focused on the expression and implementation of logic systems, from simple printer-command and build automation interpreters, through full-scale database query compilers and 4GL interface engines. This focus brings a unique and important perspective to bear on the problem of accurate and automatable sharing of clinical quality logic as expressed in knowledge artifacts for Clinical Decision Support and Clinical Quality Measurement.

 

Benjamin N. Hamlin, MPH

Benjamin N. Hamlin, MPH is the Senior Research Informaticist in the Department of Performance Measurement at NCQA specializing in clinical quality, context-specific decision support and the use of predictive analytics for quality improvement. He is a nationally recognized leader in transformative quality strategies and the principal architect of the HEDIS electronic clinical data system (ECDS) quality measure reporting protocol (www.ncqa.org/ecds). A specialist in application of Clinical Quality Language (CQL) and Fast Healthcare Interoperability Resource (FHIR) standards to quality measurement, he currently leads the initiative to digitalize NCQA’s entire portfolio of measurement products.

Throughout his career, Mr. Hamlin has conducted a wide array of health-related research including strategies for comprehensive chronic disease management, facilitating community-based clinical translational research, identifying health disparities, and designing strategies for the development of healthcare infrastructure in underserved and/or underdeveloped areas.

His principal area of expertise is in quality measurement using multidimensional assessment models for assessing quality of patient-centered care. His research encompasses the cognitive theorems for human-technology interfaces and how these can augment comprehension of healthcare information.

 

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