0      0

2020 Financial, Operations Management / IT (FOM/IT) Virtual Conference


ITuC1 - Making COVID-19 Data Perform Double Duty: Opportunities for COVID-19 Data Reuse


Oct 20, 2020 10:00am ‐ Oct 20, 2020 11:00am

Description

Clinical organizations have rapidly pivoted to provide virtual care during the COVID-19 epidemic; however, there is great opportunity to advance the automation and improvement of other aspects of public health. The CDC in partnership with organizations like Johns Hopkins Bloomberg School of Public Health, has developed electronic approaches to public health reporting on reportable conditions. Public health agencies have similarly rushed to shore up existing systems and innovate and automate public health activities including reporting, contact tracing and public health messaging and control measures that can bend the curve on communicable disease transmission. Here we discuss the available approaches to public health, from the perspective of the federal public health infrastructure, the state/local public health agency and the community health center and their data partners and how interested parties might advance their own clinical enterprise and data towards seamless reuse and downstream public health activities.

Learning Objectives:
  • Describe potential downstream uses for COVID-19 data.
  • Highlight how COVID-19 and other reportable conditions data currently and in the future will flow to public health agencies and CDC.
  • Outline how eCR (Electronic Case Reporting) works and how to start.

Moderator(s):

Speaker(s):

  • Lindsay Dietz, MAPM, Director, Program Services for Collaborative Ventures Network, HealthyArizona
  • John Loonsk, MD, FACMI, Consulting CMIO, Association of Public Health Laboratories Johns Hopkins University Bloomberg School of Public Health
  • Bryant Karras, MD, Chief Information Officer, Washington State Department of Health

You must be logged in and own this session in order to post comments.

Print Certificate
Completed on: token-completed_on
Print Transcript
Please select the appropriate credit type:
/
test_id: 
credits: 
completed on: 
rendered in: 
* - Indicates answer is required.
token-content

token-speaker-name
token-index
token-content
token-index
token-content
token-index
token-content
token-index
token-content
token-index
token-content
token-index
token-content
/
/
token-index
token-content
token-index
token-content