Module 1 Electronic health records (EHR) introduction
Unit 1
Unit 2
Module 2 Making the value case
Unit 1
Unit 2
Unit 3
Module 3 Clarifying legal and policy issues
Unit 1
Unit 2
Unit 3
Module 4 Forming partnerships
Unit 1
Unit 2
Unit 3
Module 5 Analyzing clinical data and workflows
Unit 1
Unit 2
Unit 3
Module 6 Analyzing technical options
Unit 1
Unit 2
Unit 3
Module 7 Implementing data exchange
Unit 1
Unit 2
Module 8 Optimizing data quality and use
Unit 1
Unit 2
Unit 3
Module 9 All toolkit downloads
Unit 1

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Section overview

Once you create the value case, build the necessary partnerships, and verify legal authority for your EHR-based surveillance program, you can begin the more technical design considerations of the program. A key step is to come to agreement among the partners on which data elements are necessary to meet program goals and expectations. This planning phase also includes assessing how the data will be used and what type of surveillance reports will be generated.

After articulating what data will be sourced from EHR systems, analysts and developers can then assess the clinical processes that lead to encoded EHR data. This allows a better understanding of the data’s availability and provenance (who collected it, how and for what purpose(s)), as well as an assessment of its reliability, validity and limitations for the surveillance activity.

Ultimately, you must understand the entire workflow from the origination of the EHR data to its use in the public health surveillance system.

Questions addressed in this section:

  • What data elements are necessary to surveil the condition, disease, or risk factor of interest?
  • Are those data captured in the EHR in standardized, consistent ways? If not, can they be mapped to a single standard vocabulary?
  • Who collects/records the data and for what purpose(s)?
  • How might the clinical workflows impact the quality and utility of the data for surveillance purposes?
  • How might working a Health Information Exchange impact information exchange?

Likely stakeholders and participants:

  • Programmatic and IT public health representatives, including business analysts and informaticians
  • Clinical representatives who understand data provenance and data quality issues. This might include quality improvement/quality assurance staff.
  • Clinical IT and/or EHR vendor staff
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