Pre-conference workshops are included in the registration fee and require sign-up to secure your seat.
Please select your preferred workshops during the registration process.
Wednesday, May 4
1:00 p.m. – 3:00 p.m.
WS01: Workshop – Innovative Informatics and Analytics in Medicine
Dingcheg Li, Mayo Clinic
Liwei Wang, Mayo Clinic
Hongfang Liu, Mayo Clinic
Health data informatics and analytics have received great attention and has played a critical role in clinical and translational research from various sources including Electronic Health Records (EHRs), online biomedical databases, social media and literature. They have enabled the reuse of the diverse medical data for coordinating and monitoring patient care, analyzing and improving systems of care, conducting research to discover new treatments, assessing the effectiveness of medical interventions, and advancing population health. Research that bridges the latest multimodal measurement technologies with large amounts of health data is increasing. The workshop aims to provide a premier community forum for data miners, informaticians, clinical researchers and stakeholders to share novel findings on their latest investigations in applying innovative informatics and analytics to biomedical and healthcare data.
WS02: Workshop – Agile Clinical Decision Support
DuWayne L. Willet, University of Texas Southwestern Health System
Vaishnavi Kannan, University of Texas Southwestern Health System
Designing effective Clinical Decision Support (CDS) tools in an Electronic Health Record (EHR) can prove challenging, due to complex real-world scenarios and newly-discovered requirements. As such, deploying new CDS EHR tools shares much in common with new product development, where “agile” principles and practices consistently prove more effective than traditional project management. Typical agile principles and practices can thus prove helpful on CDS projects, including time-boxed “sprints” and lightweight requirements gathering with User Stories and acceptance criteria. Modeling CDS behavior removes ambiguity and promotes shared understanding of desired behavior, but risks analysis paralysis: an Agile Modeling approach can foster effective rapid-cycle CDS design and optimization. The agile practice of automated testing for test-driven design and regression testing can be applied to CDS development in EHRs using open-source tools. Ongoing monitoring of CDS behavior once released to production can identify anomalies and prompt rapid-cycle redesign to further enhance CDS effectiveness.
The workshop participant will learn about these topics in interactive didactic sessions, with time for practicing the techniques taught. Learning Objectives: 1. Explain benefits of employing agile principles and practices during new product development; evaluate how CDS development for a local practice environment shares characteristics with new product development. 2. Iteratively refine CDS requirements with requestors using User Stories and acceptance criteria; understand how sizing with relative Story Points improves forecasting of scheduled delivery into production. 3. Identify which models/diagrams prove most helpful during CDS design, and practice applying them to a realistic CDS design and development scenario. 4. Recognize the value of automated testing in iterative development projects, and practice writing CDS "business rules" testable using open-source automated testing software. 5. Design an interactive CDS usage graph/report from EHR-captured data, for monitoring CDS tool behavior following release to production, to help detect anomalies and/or opportunities for further tool refinement.
WS03: Workshop – Data Science, Big Data and Nursings Contribution to Knowledge Value
Connie White Delaney, University of Minnesota School of Nursing
Bonnie Westra, University of Minnesota School of Nursing
Thomas Clancy, University of Minnesota School of Nursing
Karen Monsen, University of Minnesota School of Nursing
In recent years the emergence of large scale, complex electronic data repositories, commonly referred to as “big data”, has created enormous opportunities to improve care and treatment of patients. Fueled by exponential growth in computer processing speed, the shift from analog to digital signal processing, sensor technology, social networks and cloud computing, the field of data science has virtually exploded. This workshop will focus on defining Nursing’s contribution to big data and data science in healthcare, the driving forces behind their growth, and methods and tools used by nurse data scientist to successfully discover and codify knowledge value hidden in the data. Specifically, the workshop will provide a blend of didactic and highly interactive sessions on creating data models, designing studies using large scale data repositories and interpreting the results using data visualization applications. Examples and exercises will be drawn from clinical data repositories (CDR) that include the University of Minnesota’s Clinical Translational Science Institute’s Biomedical CDR, the OptumLabs Data Warehouse and the Omaha System CDR. Participants will learn how to construct data models that enable shareable and comparable outcomes in big data research studies; research designs and approaches used to predict events such as machine learning; and how to analyze large, complex data sets using pattern recognition and visualization tools. Workshop instructors include faculty from the University Of Minnesota School Of Nursing Informatics Program, rated #2 in the country by US News and World Report.
Participants in the workshop should have a working knowledge of electronic health records and healthcare analytics dashboards.
3:30 p.m. – 5:30 p.m.
WS04: Workshop – FHIR: A Workshop for Implementers
Charles Jaffe, HL7
Alistair Erskine, Geisinger
Viet Nguyen, Lockheed Martin
Russ Leftwich, Instersystems
Stan Huff, Intermountain Healthcare
Since its creation in HL7 nearly 5 years ago, the FHIR (Fast Healthcare Interoperability Resources) platform has emerged as the best hope for achieving interoperability. FHIR was created for implementers, focused upon ease of use and rapid, cost-effective solution development. Since its creation by the Joint Standards and Policy Committees in October 2014, the Argonaut Project has fostered a unique environment for and focus upon implementation. Since the release of FHIR 2.0, there has been truly global adoption and implementation among over 300 organizations, including academia, EHR vendors, healthcare systems, BioPharma and genomics companies, the Payer community, clinical professional societies, and government agencies. FHIR 2.0 provided the requisite stack for true intersystem authentication and security. To date, CMS, FDA, CDC, VHA, NIH, and DoD have committed to supporting FHIR implementation.
WS05: Workshop – Bundled Payment Initiatives: Harnessing Data to Realize the Triple Aim
Tara Borlawsky, Aver, Inc., The Ohio State University
Tom Gurgiolo, Aver, Inc.
Tom Aubel, UPMC Health Plan
Bundled or episode-based payment initiatives establish a single price for treating similar conditions and procedures with the goal of increasing quality of care, and improving patient outcomes and care coordination, while reducing overall healthcare costs. This shift from a traditional fee-for-service model has the potential to enable significant healthcare savings as well as align incentives for providers. With the “right” data, healthcare providers and payers can work together to deliver higher-value care to patients and help manage financial risk. However, due to the transactional and disparate nature, and overwhelming volume of healthcare data, organizations are challenged to effectively utilize it to make data-driven decisions that inform the design of episodes of care or drive operational and financial improvements. Risk models and analytic methods can be applied to medical claims and electronic health record (EHR) data to generate actionable insights aimed at improving population health and realizing cost savings. In this workshop, we will provide an overview of the Centers for Medicare and Medicaid Services (CMS) Bundled Payments for Care Improvement initiative (BPCI) and Comprehensive Care for Joint Replacements Model (CJR), as well as the State of Ohio’s Payment Innovation initiative. Additionally, we will review methods for modeling episodes of care under these initiatives and developing analytics solutions for generating actionable knowledge. Workshop participants will be provided with an opportunity to build analytic components, address common challenges in designing an episode of care, and design meaningful visualizations. The Aver Informatics platform, which uses visual logic streams to dynamically build SQL statements, will be utilized to demonstrate analytics solutions as well as conduct the hands-on exercises.