Promising
Practices that show evidence of effectiveness in improving public health outcomes in a specific real-life setting, as indicated by achievement of aims consistent with the objectives of the activities, and are suitable for adaptation by other communities.

Coronavirus Disease 2019 (COVID-19) Surveillance System: Development of COVID-19 Minimum Data Set and Interoperable Reporting Framework

Shanbehzadeh, M., Kazemi-Arpanahi, H., Mazhab-Jafari, K., Haghiri, H.

Release Date:

Peer Review Study

Data Collection and Analysis
Tools Included
Outside U.S.
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Data Collection and Reporting

This article explores the methodology for creating a minimum data set and interoperable reporting framework for effective surveillance of COVID-19. The framework was developed by the Iran Ministry of Health and Mental Education to streamline pandemic surveillance capacity. A combination of literature study and expert consensus approach was used to design a COVID-19 minimum data set (MDS), and the definitive data elements of the MDS were determined by applying the Delphi technique. Existing messaging and data standard templates (Health Level Seven-Clinical Document Architecture [HL7-CDA] and SNOMED-CT) were used to design the surveillance interoperable framework. This article looks at employee-based health plan beneficiary data from 2019 and 2020 to quantify changes in telemedicine and office-based care utilization. The study focuses on demographic and socioeconomic measures and found that telehealth utilization was affected disproportionately by age and poverty rate.

Resource Details

Outcomes of Interest

Improve Data Infrastructure

Priority Population(s)

Setting(s) of Implementation

Community

Geographic Area of Implementation

Implementation Period

2020