The following content was developed by James Kariuki.
Minimum dataset for HIV use case
- Mapped to standard vocabularies such as ICD, SNOMED, and LOINC
- Source Applications
- EMR, LIS, Pharmacy
- Person identity management: Jembi
- Patient matching algorithm
- Patient matching
- Data Repository
- Linked patient records
- Analytics platform could be an extension of the data repository
- Comprehensive views: patients, geographic and trends
Data Exchange Process
- Extraction of relevant data from different source applications for integration
- Messaging and content format
- Interoperability Software Platform
Privacy Security and confidentiality
Principles and standards for protecting data shared
- Data use agreements of MOUs
Use personally identifiable and sensitive information
- Who should have access to the information?
- How is this information managed, stored, and used?
- Policies and procedures
- cover all aspects of data collection, storage, transmission, and use
- standard approaches to increase awareness among users and support a culture of maintaining privacy
Change management procedures
- Updating minimum dataset for HIV use case
- Managing changes for applications within DISI
- Updates on data exchange processes and workflows
Training requirements for different aspects of DISI
- Technical users: apply knowledge to adapt and implement DISI
- Program users: application of the knowledge for the DISI data use in their context
- Decisions makers: awareness to advocate and make decisions
Capacity Building/Training based on DISI content areas e.g.,
- Privacy Security and confidentiality
- Change management procedures
- Minimum dataset definition for use cases
- User and technical documentation for DISI applications
Guidance on the knowledge, skills, capacity needed to implement, support and maintain the DISI package.
Having client-level HIS infrastructure and Health Information Exchange systems with the ability to uniquely, securely, and confidentially link individual-level patient data to track sentinel events across points of testing, care, clinical monitoring, and treatment sites and deduplicate data is critical to support data collection for Case Surveillance.
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