FHIR can facilitate interoperability between different healthcare systems and applications, making it easier to exchange data and generate reports. The usage workflow for COVID19 reporting may involve the following steps:

• Data collection: The first step in the FHIR workflow is to collect the necessary data related to COVID19. This may involve healthcare providers or public health authorities gathering information on COVID19 cases, vaccinations, or other relevant data points (such as patient demographics, clinical observations, laboratory test results, and medications).
• Data mapping: The collected data needs to be mapped to FHIR resources and elements. This step involves identifying the relevant FHIR resources, such as Patient, Observation, Diagnostic Report, and Medication Request, and mapping the data to the appropriate FHIR elements.
• Data exchange: Once the data is mapped to FHIR, it can be exchanged between different healthcare systems and applications using FHIR messaging or API.
• Data retrieval: Once the data is stored in the FHIR server, it can be retrieved by authorized users using FHIR APIs . These APIs allow users to query the server and retrieve specific FHIR resources.
• Data processing: After the data is exchanged, it needs to be processed by the receiving system or application. This may involve validating the data, performing transformations, and storing the data in a database.
• Data analysis: Once the data is processed, it can be analyzed to identify trends and patterns. This analysis may be conducted using statistical software or other specialized tools.
• Report generation: Based on the data analysis, reports can be generated to communicate key findings to stakeholders. These reports may include charts, graphs, or other visual aids to help illustrate the data.
• Report dissemination: Finally, the reports need to be disseminated to the appropriate stakeholders. This may involve sharing reports with healthcare providers, public health authorities, or government agencies.

It is important to maintain data security and privacy throughout the workflow. This may involve using encryption to protect sensitive data, limiting access to authorized personnel, and following best practices for data storage and transmission. Additionally, data quality should be regularly monitored and maintained to ensure accuracy and consistency over time.