Situational Awareness for Novel Epidemic Response
1.0.1 - CI Build International flag

Situational Awareness for Novel Epidemic Response, published by HL7 International / Public Health. This guide is not an authorized publication; it is the continuous build for version 1.0.1 built by the FHIR (HL7® FHIR® Standard) CI Build. This version is based on the current content of https://github.com/HL7/fhir-saner/ and changes regularly. See the Directory of published versions

Automation Testing Examples

Test data for the Automation Test Data Set includes a Measure, Location, and Organization resources for a single facility, and test data representing two days of patient activity for a small group of test cases, designed to illustrate the capability of the automated system to distinguish the difference between cases to be included or excluded from the measure.

Automation Test Data

The test data were developed with the following questions in mind. Using data gathered electronically from an EHR:

  • Can it accurately and consistently be discerned that an inpatient with COVID-19 was admitted on the previous day?
  • Can it accurately and consistently be discerned that an inpatient had a positive viral laboratory result for SARS-Co-V-2, the organisms causing COVID-19? Likewise can it accurately and consistently be discerned when they did not?
  • Can it accurately and consistently be discerned if a patient is suspected of COVID-19 by ICD-10-CM / SNOMED CT diagnosis or problem list codes in the absence of a positive laboratory test for SARS-Co-V-2, the organisms causing COVID-19? Likewise can it accurately and consistently be discerned when they did not?
  • Can it accurately and consistently be determined that a patient has had a specimen collected in the previous 14 days that was positive for SARS-Co-V-2, the organisms causing COVID-19? The scenarios tested will include those where specimens were collected prior to admission. Likewise can it accurately and consistently be discerned when they did not?
  • Can it accurately and consistently be determined that the only prior positive viral laboratory result for SARS-Co-V-2, the organisms causing COVID-19 was collected on the day of Connectathon?
  • Can it be identified accurately and consistently that an inpatient’s location is or is not an intensive care unit?
  • Can it accurately and consistently be determined that a patient is located in the Emergency Department at the time of Connectathon, or that patient is not?
  • Can it accurately and consistently be determined that a patient was on a mechanical ventilator on the day of Connectathon, or that he was not?

This data can be be used to prepopulate a FHIR Server to support test cases for the Measure Computer Actor.

Predefined Measure for the Automation Test Data Set

This implementation guide includes a sample measure describing the measurements that were required to be reported to CDC/NHSN earlier this year for Patient Impact and Hospital Capacity. It is similar to the measure provided for the hospital capacity examples, but includes the necessary features to automate computation from data available via a FHIR Server.