1st Edition

Storytelling with Data in Healthcare

By Kevin Masick, Eric Bouillon Copyright 2021
    192 Pages 39 B/W Illustrations
    by Routledge

    192 Pages 39 B/W Illustrations
    by Routledge

    With the constant evolution of change in healthcare from both a technology and governmental perspective, it is imperative to take a step back and view the big picture. Relying on hunches or beliefs is no longer sustainable, so avoid jumping to conclusions and making decisions without thoroughly understanding the statistics being analyzed. The triple aim of statistics is a conceptual model laying the foundation for improving healthcare outcomes through statistics. This foundation is: know your numbers; develop behavioral interventions; and set goals to drive change.

    With the availability of electronic data sources, the quantity and quality of data have grown exponentially to the point of information overload. Translating all this data into words that tell a meaningful story is overwhelming. This book takes the reader on a journey that navigates through this data to tell a story that everyone can understand and use to drive improvement. Readers will learn to tell a narrative story based on data, to develop creative, innovative and effective solutions to improve processes and outcomes utilizing the authors’ tools. Topics include mortality and readmission, patient experience, patient safety survey, governmental initiatives, CMS Star Rating and Hospital Compare.

    Storytelling with Data in Healthcare combines methodology and statistics in the same course material, making it coherent and easier to put into practice. It uses storytelling as a tool for knowledge acquisition and retention and will be valuable for courses in nursing schools, medical schools, pharmacy schools or any healthcare profession that has a research design or statistics course offered to students. The book will be of interest to researchers, academics, healthcare professionals, and students in the fields of healthcare management and operations as well as statistics and data visualization.

    Table of Contents

    1. Introduction
      1. Evolution of Healthcare Analytics
      2. Know Your Numbers
      3. Develop Behavioral Interventions
      4. Set Goals to Drive Change

    2. Research Methods
      1. Reliability
      2. Validity
      3. Scales of Measurement
      4. Sampling Techniques
      5. Research Methodology

    3. Statistical Analysis
      1. Alpha and Type I Error
      2. Beta and Type II Error
      3. Power
      4. Statistical Significance vs Clinical Significance
      5. Descriptive/Inferential Statistics
      6. Measures of Central Tendency
      7. Measures of Dispersion
      8. Parametric/Non-Parametric Statistics
      9. Bridging the Gap between Statistical Methods and Healthcare
      10. Run Charts
      11. Control Charts

    4. Mortality and Readmission
      1. Process and Outcome Metrics
      2. Run/Control Chart Contradiction
      3. Methodologically Testing Your Creativity with Data
      4. Run Charts Methodology
      5. Control Chart Methodology

    5. Patient Satisfaction
      1. Press Ganey
      2. Patient Experience
      3. Behaviors and State of Mind
      4. Survey Methodology
      5. HCAHPS Survey
      6. Results

    6. AHRQ Safety Survey
      1. Why Focus on Patient Safety
      2. Survey Methodology
      3. AHRQ Hospital Survey Methodology

    7. The Past, Present, and Future
      1. Government initiatives/programs
      2. Core Measures and Bundled Treatments
      3. Methodology
      4. Infection/Safety Domain Methodology

    8. CMS STAR rating
      1. Composite an Summary Scores
      2. Process and Outcome Metrics
      3. CMS Star Rating Methodology
      4. Statistical Concepts
      5. CMS Star Statistical Methodology

    9. CMS Hospital Compare
      1. Methodology
      2. Methodology of Data Definitions
      3. Methodology of Statistics

    10. Turn Data Into Action
      1. The Art of a Question
      2. Step Back and Don’t Jump to Conclusions
      3. Think Methodologically
      4. Analyze the Metric
      5. Test Your Creativity with Understanding the Data
      6. Insights – Use the Skills Learned to Question What You See
      7. Search for the Critical Questions to Ask
      8. Trending Data to Understand Past, Present, and Future
      9. Inquire Others to Have a Complete Picture of What is Happening
      10. Conclusions – Use All Available Information to Derive Conclusions
      11. Sustainable Solutions – Create Solutions

     

    Biography

    Kevin D. Masick, Ph D.

    Kevin has 15+ years of experience in both academia and practice. He has taught at 5 universities in both the business school and psychology department teaching undergraduate and graduate courses in-person and online in research methodology and statistics. He has worked for 3 healthcare systems in human resources, quality management, and strategic planning where he has led a team of healthcare professionals in improving patient outcomes through innovative analytics and dashboards, research, and education. In addition to his full time work, he has published an advanced research methods textbook, built multiple training programs both in-person and online, and published in peer reviewed journals. He received his Ph D in Applied Organizational Psychology and masters in Industrial/Organizational Psychology both from Hofstra University and his bachelor’s degree in psychology from SUNY Albany.

    Eric Bouillon, Ph D.

    Eric has 4 years of experience working as a dissertation coach using his expertise in research design and statistics to coach doctoral students. He has also worked with Kevin to develop a online and in-person training program to help healthcare employees how to interpret and utilize statistics in practice. Recently, while writing this book, Eric was finishing up his Ph.D. at Hofstra University in Organizational Psychology. His dissertation focused on creating a scale that utilized psychometric and scale development best practices to measure how well individuals use statistics to find data-driven solutions in organizations. Most recently, Eric has branched out of academia and was hired as a People Scientist at a recruitments firm to help develop tailored assessments for selection and recruitment. He also spearheaded the development of a new tool that measures organizational purpose through psychometric testing.