Presentation 7:00 p.m.
Adjourn 8:00 p.m.
Contact: Fred Cramer
Please note: Webinar information will be emailed to registered participants the evening before the event.
Covid-19 Data Quality Case Study: An Update
Much has happened since we previously discussed Covid-19. We know more about the virus and its symptoms. We have some more metrics to work with. And now, we are rolling out vaccines not available back in October. This presentation will expand on the nature of the virus, and how it invades the human cells. We will examine updated metrics of infection rate, morbidity. We now know more about the “long haul” symptoms of victims released from the hospital but still unable to go back to work, especially because of neurological challenges. We will discuss how it is so difficult to get good data on these victims, mainly due to the fragmented nature of data collection and distributed databases. Good quality data requires consistent definitions and capture.
We will give particular attention to the vaccine characteristics of efficacy and safety, and how the tests are conducted, and we measure quality in those issues. Proper management of the pandemic requires adequate metrics of high quality and consistently defined. We will suggest additional metrics of the various stages of an infection, and subsequent illness and hospitalization. Finally, if we have time, we shall look at metrics of the impact of the pandemic on the U.S. economy.
This presentation discusses the emerging need for new metrics for the patients and victims of the pandemic. Flexibility and creativity become important in gathering data and reporting it, ensuring high quality of information delivery. Because of “warp speed” of vaccines, good management of the pandemic by public health authorities requires on-going measurement of infections and recoveries in the general population (not just in a controlled test). Given the international economy and travel, new metrics and surveillance of emerging diseases which may become the next pandemic should be developed.
Michael Scofield, M.B.A. is an Assistant Clinical Professor at Loma Linda University. He is a frequent speaker and author in topics of data management, data quality, data visualization, and data warehousing. He has spoken in over 27 states, Canada, Australia, and the U.K. Audiences have included 24 DAMA chapters, 5 TDWI chapters, 14 ASQ sections and many accounting professional organizations. He also does guest lectures at several universities. His career experience includes some time with a CPA firm, developing an accounting and general ledger system for a major California bank, as well as experience in government, manufacturing, finance, and software development. Now semi-retired, he still does pro bono data mining and data quality analysis for non-profit organizations. His greatest interest currently is data visualization, data quality assessment, and using graphic techniques to reveal business and economic behavior. He also has humor published in the Los Angeles Times, and other journals.