contextual inquiry of enteric disease outbreak investigation processes to improve visualization...
TRANSCRIPT
Contextual Inquiry of Enteric Disease Outbreak Investigation
Processes to Improve Visualization Capacity
for Public Health SurveillanceJonathan Anderson, MPH
Bureau of Epidemiology
Utah Department of Health
INTRODUCTION
Inform visualization tool (Epinome) development & implementation
1 - Describe existing work processes (user stories)
2 - Identify:
- decision making milestones
- intervention steps
- wish-list items
- limitations
METHODS
Data collection: Contextual inquiry
Participants:
Domain expert – UDOH Enteric Diseases Epi
Interviewer – UDOH Epi
UDOH Deputy State Epi
CoE Project Manager
Computer Scientist
Other CoE members
RESULTS
61-Step “Work Process” Document:Steps in enteric disease investigation.
Wish list items
Limitations
Possible Intervention Steps
Q & A
Appendices (Artifacts)
Work process stepsWork process steps
Links to AppendicesLinks to Appendices
Wish list itemWish list item
RESULTS
61-step Work Process Document
LHD Involvement 22 steps (36%)
UPHL Involvement 12 steps (20%)
UT-NEDSS data used 13 steps (21%)
Non-NEDSS data used 26 steps (43%)
Manual data entry 15 steps (25%)
Data analysis & visualization 10 steps (16%)
ExampleNEDSS Database Use:
38.The Enteric Disease Epidemiologist uses NEDSS as a record keeping tool, a place to enter/record: a) lab results, b) outbreak names/codes, and c) case status (e.g. Confirmed, Not a Case, Suspect, Probable, etc).The Enteric Disease Epidemiologist enters
information into a spreadsheet (Appendix H) from NEDSS. However, NEDSS is typically not updated with information on risk factors & exposures in the spreadsheet. Therefore, as the investigation progresses the spreadsheet becomes the most current source of data.
ExampleData analysis & visualization:
36. The Enteric Disease Epidemiologist uses the spreadsheet (Appendix H) to analyze the outbreaks. “Analysis” is an ongoing process, beginning as soon
as two cases with matching PFGE patterns are identified.
Analysis in this sense involves searching the spreadsheet (Appendix H) for commonalities.
Variables that are commonly analyzed include: Age, Exposures, Date of onset, Location.
IMPACT Enhanced communication of ideas among
participants
Unique approach/model:
“This approach to design provides an important model for other researchers and practitioners to design usable systems that fit with and expand on existing practice.”
“Academic informatics does not have a good insight into how departments of health function so this paper nicely addresses this gap.”
Created map for development team
Able to compare & validate with other epis