Factors influencing the adoption of electronic medical records technology in public health institutions in Kenya: A case of Hospitals in Nairobi county

Abstract

The application of Electronic Medical Records Technology has gained much prominence and is widely used in Kenyan hospitals today. This technology agitates for paperless transactions health care. Many studies have been done in other countries to study the factors influencing adoption and utilisation of EMR technology, but a small number of studies exist in Kenyan situation. This study sought to examine why the application of EMR technology has not kept pace with its demand. This study sought to answer four key research questions derived from the study objectives which include the influence of resource availability, accessibility to network infrastructure, capacity building and staff levels of education on the adoption of electronic medical records technology in public health institutions in Nairobi County. This study was guided by four hypotheses derived from study objectives. Empirical literature of the works of widely published scholars was reviewed. The study was guided by diffusion and technology acceptance model as its theoretical framework. The study adopted across sectional survey design with a target population of 200 respondents. Using the Krejcie and Morgan table to determine the sample size, 127 respondents were sampled for this study. To achieve a desired representation, simple random sampling was used. A questionnaire with a 5-point Likert scale was constructed and used. The data obtained was analysed by descriptive statistics using SPSS Version 20.0 and the findings was appropriated to the research questions. Qualitative data was analysed by inferential methods and presented descriptively. Both content and construct validity were used to ensure validity of the research instrument‟s while reliability was determined by using the Cronbach-Alpha Coefficient. Pilot testing to pre-test and validate the research instruments was done prior to the main study. Two of the four hypothesis were rejected, there seemed to exist no significant relationship between accessibility to network and adoption of EMR technology with (p = 0.836 > 0.05), no significant relationship between staff level of education and competencies and adoption of EMR technology with (p = 0.151 > 0.05) and two hypothesis were accepted, there seemed to exist a significant relationship between resource availability and adoption of EMR technology with (p = 0.027 < 0.05) and a high significant relationship between capacity building with adoption and use of EMR in public health institutions in Nairobi with (p = 0.000 < 0.05). Computed MLR results showed that the four factors studied accounted for 28.5% of variance with adoption of EMR. The study recommends that health facilities should increase infrastructure and resources that support EMR use, employees should be supported for further training on EMR operation and suppliers should regularly support and training health staff on how to use EMR usage. The study results may be useful to hospitals as they gear towards integrating all their process by using technology.