Meeting/Event Information

DAMA Philadelphia welcomes Michael Scofield --

Covid-19 Data Quality Case Study

Managing a public health crisis requires reliable metrics on both local and aggregate levels.  Unlike many industrial processes, raw data about a pandemic is captured through a variety of distributed mechanisms, locations, and jurisdiction.  Data quality challenges abound.  Definitions of events, metrics, and timing of aggregates create ambiguities and uncertainties. 

This presentation begins with a discussion of the development of rigorous, data-based science and the various functions of public health in a pandemic.  We will identify the decision-makers in a pandemic, and discuss how they get their information and data.  But this is part of a broader topic of threat assessment—what mechanisms are in place to gather data and alert the nation to all kinds of threats, and will we be alert to clues about the next imported pathogen. 

At an introductory level (“Pandemic-101”) we will examine critical elements of the current pandemic including explaining how a virus works, definitions of antigens, antibodies, co-morbidity, false negatives, and long-haul symptoms resulting from Covid-19 infection.  Those long-haul symptoms in particular present new challenges to the logical data architecture of electronic medical records, as well as how data is captured and verified. 

Mr. Scofield will introduce a graphic model of the chain of events in a patient’s illness, and how we could benefit from more metrics along that chain with greater precision.  He will introduce the concept of the event-to-information supply chain and issues of timing and ambiguity of high-level metrics.  He will show examples of political bias in expression and manipulation of information.  We will look at the quality challenges of vaccine testing and distribution.  Finally, we will discuss what new public health surveillance techniques (and data chains) need to be in place to prevent the needless deaths of 600,000 Americans (or 3.8 million worldwide) from the next pandemic.

About our speaker:

Michael Scofield, M.B.A. is an Assistant Clinical Professor at Loma Linda University.  He has spent most of his career in systems development, data management, and information quality.  He has lectured to over 340 professional audiences around the U.S., Canada, and in the U.K. and Australia.  He has spoken to over 26 DAMA chapters, with over 80 DAMA presentations.  He has over 27 published articles in data management, particularly in data quality assessment.  Recently, his more popular topics include a “Covid-19 Data Quality Case Study”, sources of organizational complexity, semantic data integration, and data visualization.  He also lectures widely to general audiences on topics of travel, history, interpreting satellite imagery, and civics.