Facilitators and barriers to the adoption of Electronic Medical Records Systems by healthcare providers healthcare providers in HIV clinics in Kisumu County Kenya

Abstract

Background: EMRs adoption faces numerous challenges and the benefits in healthcare delivery in Kenya remain scanty; particularly in HIV/AIDS treatment and management. Consequently, it was important to identify enabling factors and perceived barriers by healthcare providers towards EMR use in HIV clinics Objective: The study investigated factors that influence healthcare providers‘ use of EMR in HIV clinics in Kisumu County. The specific objectives were to describe facilitators to the use of EMR and to explore barriers to the use of EMR by healthcare providers working in HIV clinics in Kisumu County. Study Site: HIV clinics in Kisumu County, Kenya Study design: This study employed a qualitative research design. In-depth interviews were used to elicit views on reasons for and against EMR use, using an interview guide. Subjects: Clinical officers and nurses. Methods: The participants for this study were purposively selected from 18 HIV clinics and had to have interacted with an EMR for at least 6 months prior to the data collection period. Data was audio recorded, transcribed, and content analysis performed using both deductive and inductive codes. Themes generated were organized using the Andersen-Newman Framework of Health Services Utilization. This framework permits systematic identification of factors that influence individual decisions to use (or not use) available health care services. Facilitators and barriers were categorized as predisposing characteristics, enabling/disabling resources and need factors. Results: A total of 42 participants were interviewed; clinical officers (n=27) and nurses (n=15). Facilitators of EMR use include personal initiative, ease of EMR operation, Human Resource Information Officers (HRIO‘s), technical support, environmental factors, management support, capacity building and resource availability. Barriers identified were: negative attitude, resource scarcity, intermittent connectivity, EMR technical issues, unstable electricity, staff rotations, inadequate training, lack of support supervision from County Health Management Team (CHMT), workload, integration of services, ergonometric support, poor infrastructure and time factor. Conclusion: Factors influencing EMR use were identified such as personal initiative, attitude, management support, ease of EMR operation, heavy workload and hardware support. With this knowledge, policy makers, Ministry of Health and EMR implementors can potentially formulate mechanisms that can be put in place to enhance the facilitators as well as address the barriers for successful EMR adoption. Recommendation: The study findings suggest that to enhance EMR use, intervention mechanisms that stakeholders can adopt include organizing for refresher training, providing adequate computer resources, enacting policies to support integration of health services at the clinics and include EMR support v supervision as an element of CHMT evaluation.