A multivariate statistical evaluation of actual use of electronic health record systems implementations in Kenya

These EHRs implementations promise to improve quality of patient care, patient safety, and to reduce costs. In Kenya, the national EHRs system, known as KenyaEMR, was implemented in healthcare facilities offering HIV services. The study assessed the state of 376 KenyaEMR system implementations in these facilities, focusing on seven EHRs use indicators. Six of the seven indicators were programmed and packaged into a query script for execution within each KenyaEMR system implementation to collect monthly server-log data for each indicator for the period 2012-2019. The indicators included staff system use, observations (clinical data volume), data exchange, standardized terminologies, patient identification, and automatic reports. The seventh indicator, EHR variable Completeness, was derived from routine data quality reports within the EHRs. Data analysis revealed that the mean number of authorized users who actively used the KenyaEMR system was 18.1% across the facilities. On average, the volume of clinical data captured in the EHRs was 3363, with only a few facilities having health data exchange capability. The majority of EHRs concept dictionary terms mapped to standardized terminologies such as CIEL. However, only 50.5% of patients had the nationally endorsed patient identifier number recorded. Multiple regression analysis indicated the need for improvement in the mode of EHRs use of implementation. The results suggest that most of the EHRs use areas assessed need improvement, especially in relation to active usage of the system and data exchange readiness. The standard EHRs use indicators can effectively measure EHRs use and consequently determine the success of EHRs implementations. The study demonstrates that through the use of standardized indicators, key new insights and gaps on actual status of EHRs implementations within countries can be identified. Aspects of national-level EHRs usage assessments need not be time- or resource-intensive, as assessments can be automated using data already within the EHRs. Mechanisms that allow efficient EHRs usage assessments offer insights to enable any identified EHRs usage gaps to be addressed in a timely manner. The findings of this study have implications for the evaluation of EHRs implementations in Kenya and other low- and middle-income countries. The study highlights the need for regular assessments of EHRs use to inform approaches to improve success of existing and subsequent implementations. The use of standardized indicators and automated data analysis can provide valuable insights into the actual status of EHRs implementations and identify areas for improvement.