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Lightning Round Sessions 

Lightning Round sessions are dynamic, quick, 15 minute interactive presentations enabling speakers to share key information and engage in discussions on implementation and hands-on learning experiences.

Group 3

The Intersection of Data Science and CEhp: How Machine Learning and Artificial Intelligence May Shape the Future

Joseph Kim, MD, PhD, MBA

Over the past few years, a key emerging concept in health care has been around the application of “big data” and “data analytics” to improve patient outcomes. Yet, most CEhp professionals have not tapped into these resources to educate clinicians or implement QI projects. CEhp recognize that data science is rapidly emerging as a field that has the potential to improve care delivery, but what do most CEhp professionals understand about data science? What level of technical knowledge do they require to work effectively with informaticists and educators to improve care quality? Where do the worlds of data science and CEhp intersect? Since the complex concepts of data science can quickly get very technical, this session will keep the discussion at a non-technical level and leverage illustrative examples that educators can understand and apply in their profession. The session will review how the worlds of data science and CE are colliding today. The session will also explore how the landscape of CEhp and professional development may evolve as data science becomes integrated into care delivery and shape learning health systems of the future.

Qualitative Analysis: A New Tool in Your Evaluation Toolbox

Michelle Tyner, MS

Qualitative data, an excellent, under-utilized analysis, is becoming more common in healthcare research. However, many are unfamiliar with qualitative data and how impactful these data points can be. This session will review various forms of qualitative data, collection methods as well as various analysis methods. Qualitative data is an important aspect of research and should not be discounted when evaluating educational activities.

Developing Financial Value Models for Quality Improvement Initiatives

Marvin Dewar, MD, JD; Laura Gruber, MBA, MHS; Ted Singer, CHCP

The ACEhp community spends a considerable amount of time discussing outcomes and, more specifically, how to best articulate the impact of the initiatives we organize and execute. The outcomes models we currently utilize (Moore’s, TELMS, Kirkpatrick, Pathman) help us measure individual and group behavior within the working healthcare environment. The highest levels of these outcomes also allow us to describe changes in patient health status, and the health of populations. 

One of the core tenets of the National Quality Strategy is better quality of care at lower cost, with a focus on reducing the per capita cost of healthcare. As such, it is imperative that we, as a community, develop models for measuring the financial impact of our initiatives.

Quality Improvement projects, typically conducted within working health systems, provide an opportunity to measure cost savings as they consist of components with measureable dollar values – clinician and staff time, ordered tests, prescribed therapies, insurance related penalties and incentives, etc.
The University of Florida has been developing models for attaching cost analysis to quality improvement projects. Using an ongoing Heart Failure project as a case study, we will present a methodology that session attendees can utilize to report financial outcomes of quality improvement projects.

Combining Education, a Scorecard, and Technology to Improve Symptom Screening, Assessment, and Management

Beth Faiman; Carrie Tompkins Stricker; Debra Wujcik, PhD, RN 

Symptom screening, assessment, and management is needed to prevent and minimize treatment side effects in high risk populations such as patients with relapsed/refractory multiple myeloma receiving recently approved targeted therapies. Health care providers are challenged to incorporate new information into the clinical setting and to track adherence to national guidelines for care. This presentation describes outcomes of a clinical trial that included 1) certified medical education, 2) a scorecard to measure guideline adherence behavior and 3) technology to improve symptom frequency and severity in patients with relapsed/refractory multiple myeloma. Case studies will illustrate the engagement of expert faculty to develop education content and scorecard metrics. Study outcomes will be presented to show improved provider adherence to guidelines and improved symptoms, such as peripheral neuropathy and venous thromboembolism, that if severe, interfere with treatment continuation.