Part of the Integrating tracker and aggregate data in DHIS2 DAC2021 Session: Wednesday 23nd June 14:00
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My name is Vlad Shioshvili, and I am a tech lead for PEFPAR data exchange and interoperability group at ICF. I am based in Tbilisi, Georgia, and would like to share about work we have been involved in to create workflow to support patient level data aggregation using standards and computable guides.
Patient-level data collection systems range from disease surveillance systems, to Electronic Medical Record (EMRs), laboratory systems, pharmacy systems, and community health information systems. Today, these systems are supporting a wide range of health care needs and collecting patient datasets that vary in their levels of detail and complexity. In this diverse environment, many of these systems are focused on patient care and may not be designed to support additional health system data analytics such as calculation of aggregate metrics or supporting surveillance activities.
As PEPFAR and its partner countries continue to strive towards epidemic control and achieving the 95-95-95 goal in each country, patient-level data has become a crucial piece of the puzzle to track HIV patient testing, treatment, and viral suppression. Patient-level data is necessary to track continuity of care from testing to treatment. More countries are using EMRs at health facilities to track patient care, and there is a growing need to use patient-level data collection systems that support broader health system needs, leveraging terminology standards and standard processes for calculation of metrics, defining sentinel events and calculation of frequency of such sentinel events.
PEPFAR has created the Data Aggregation Service for Health (DASH). DASH consists of a suite of custom digital tools and using standards that addresses the challenges that the current environment is facing. By offering these workflows and tools, future users are being provided with an infrastructure that converts the minimum data set for an indicator into an aggregated and standardized message that can be shared with a Health Management Information System (HMIS) such as DHIS2.