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Presenting and Reporting Data: Improving Presentation of Your Data to Inspire Results

Learn how data visualization affects comprehension and drives better decision-making. Gain insights from various industries, including healthcare. Improve your data reporting techniques to enhance understanding and engagement.

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Presenting and Reporting Data: Improving Presentation of Your Data to Inspire Results

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  1. Presenting and Reporting Data: Improving Presentation of Your Data to Inspire Results APIC MT Spring Conference Friday, April 12, 2019 Helena, MT Presented by: Laura Bermel, BSN, RN, CIC--Kalispell Erika Baldry, Communicable Disease Epidemiologist

  2. Objectives • Understand how data presentation affects understanding and next steps for information being presented • Learn from examples outside of healthcare for data visualization • Recognize how understanding improves when data presentation is improved

  3. Give Credit!

  4. Example from “2017: The Year in Charts”; New York Times: 12/29/2017

  5. Score Bug

  6. Display of Increasing Rates of Influenza https://www.cdc.gov/flu/weekly/usmap.htm

  7. Display of Increasing Rates of Influenza https://www.cdc.gov/flu/weekly/usmap.htm

  8. WNV Progression

  9. Data Presentation “Hall of Fame”

  10. “Florence Nightingale’s Rose” -- Florence Nightingale's most famous infographic (1858)

  11. Anyone watch “Victoria” on PBS this season? Water Pump

  12. Additional Challenges in Montana: • Having enough data to create meaningful results • CAHs • Reactive vs proactive with data

  13. Even the Experts Can Have Issues Presenting Their Data • https://www.businessinsider.com/the-27-worst-charts-of-all-time-2013-6#want-more-28

  14. Montana Examples

  15. Infographics https://dphhs.mt.gov/publichealth/cdepi/infographics

  16. HAI Data • Create scorecards on a quarterly basis • Scorecards include data for 12 IPPS facilities • Allows facilities of similar size to compare themselves to one another using the standardized infection ratio (SIR) • SIR>1 means that the number of events (HAIs) reported to NHSN were greater than predicted • SIR<1 means that the number of events (HAIs) reported to NHSN were less than predicted • SIR=1.0 means that the number of events (HAIs) reported to NHSN were the same as predicted • Predicted value is based upon facility’s response to the annual Patient Safety Survey in NHSN and the 2015 national aggregate data

  17. CLABSI

  18. CLABSI

  19. CAUTI

  20. CAUTI

  21. CDI

  22. CDI

  23. 1 NHSN (TAP Report)

  24. 2 NHSN (TAP Report) 3

  25. NHSN TAP ReportCLABSI (State) Group SIR for CLABSI is 0.6 (>goal of 0.4) Group CAD for CLABSI is 13

  26. NHSN TAP Report CLABSI + CAD • CAD= Cumulative Attributable Difference • Number of infections that need to be prevented to meet your SIR goal (for example, in the first location, 6 infections would need to be prevented to meet the DPHHS goal of 0.4 for CLABSI). - CAD

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