Understanding the Interoperability between Electronic Medical Records (EMRs) and the District Health Information System (DHIS2) in Kenya

This abstract has been accepted at the 2024 DHIS2 Annual Conference

Understanding the Interoperability between Electronic Medical Records (EMRs) and the District Health Information System (DHIS2) in Kenya

Introduction Kenya is developing a new Electronic Medical Records (EMR). While the EMR was designed to integrate with the DHIS2, preliminary findings show that there was limited integration We conducted a study to understand the existing barriers and potential facilitators of data exchange. Methods We applied a cross-sectional study design at the hospital piloting the new EMR. Data collection was through key informant interviews, evaluation of electronic systems and discussions during a stakeholder’s data review meeting. A semi-structured guide was used to ensure consistency in topics covered, such as information needs of key health leaders, current practices related to data use and barriers to interoperability. Data analysis involved placing data in various recurring themes and discussing them with health leaders for consensus-building. Consent was sought from participants and confidentiality was observed. Results The DHIS2 had successful integration with TIBU for tuberculosis and Chanjo for COVID-19 vaccination. However, it had limited integration with the EMR, even though both were built with interoperability standards. To get data into DHIS2, data were downloaded from the EMR and entered manually. Common constraints included the naming of data sets, data elements and disaggregation which were dissimilar between the systems. The arrangement of data in the EMR was dissimilar to the tools in the DHIS2 affecting integration. Unlike DHIS2, the EMR used ICD11 to classify diseases. The system developers of both systems didn’t work together. The use of both EMR and DHIS2 raised data quality issues. There were more missing data in DHIS2 after the EMR was introduced. Capacity-building challenges were observed; data managers were not adequately trained in both systems. Discussion This paper contributes to Kenya’s efforts to enable data exchange between health information systems. Interoperability, though highly talked about in meetings, is difficult to implement in practice. It is easy to integrate a one-disease system but challenging for a complex EMR. Even though the systems used interoperability standards, there was a lack of use of common terminologies/dictionaries to support integration. There is a need to think about the future of the DHIS2 if the EMR picks up countrywide. We recommend that system developers for both systems work together to develop common dictionaries/terminologies to ease integration. Capacity building is critical.

Primary Author: Ayub Manya

Interoperability, integration, Data dictionary, Electronic medical records, capacity building