Factors Affecting the Adoption of Health Management Information Systems (HMIS) Among Health Workers: The case of SmartCare Software in Addis Ababa Regional Public Hospitals
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Date
2013-06
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Addis Ababa University
Abstract
Background: There has been an increasing interest in the area of Electronic Medical Records (EMR) and more and more
hospitals all over the world try to keep their patients’ records electronically. The adoption of EMR has become a
major concern in the healthcare industry, as it is a key factor to the healthcare quality improvement. In Ethiopia, the
implementation of Electronic Medical Record (EMR) is through software called SmartCare. SmartCare software possesses
numerous advantages and features such as Simultaneous, remote access to patient data, Legibility of record, Safer data,
Patient data confidentiality, greater range of data output modalities and Service Integration within the facility (laboratory,
pharmacy, prescription & scheduling). However, these systems are not used by the health workers in Addis Ababa
Regional Public hospitals.
Objective: The objective of this study was to identify and measure the factors affecting the behavioral intention and usage
behavior of health workers EMR-SmartCare Software adoption in public Hospitals of Addis Ababa City Administration.
Methodology: To identify the factors affecting the utilization of EMR-SmartCare software, a cross-sectional descriptive
study which was quantitative were employed and a total of 303 study participants were randomly selected from health
workers based on their population size proportionally in selected 5 regional hospitals of city administration using Selfadministered
questionnaires.
Results: The findings provide strong empirical support for all of the main constructs mentioned in the research model,
which posits five direct determinants of intention to use EMR-SmartCare software and another two direct determinants of
actual Use Behavior as follow: Performance Expectancy(PE), Effort Expectancy(EE), Social Influence (SI), Computer
Attitude(CA), Personal Innovativeness in IT(PIIT) as determinant of Behavioral Intention and; Facilitating
Conditions(FC) and Behavioral Intention(BI) as determinants of Actual Usage Behavior(AUB). These results maintain
enough explanatory power R2 =.702 (Adjusted R squared=.333) to help explain the intentions and actual use behavior of
health workers in adopting EMR- SmartCare software.
Conclusion: These research findings indicate that the variables in the proposed research model significantly and
positively impact the behavioral intention and actual use behavior to adopt EMR-SmartCare software. Among these,
attitude towards computers has the most significant positive impact on adoption intentions. Therefore this study suggests
that in order to enhance the intention to adopt and use EMR-SmartCare software, hospitals should strengthen independent
impact variables, including Attitude towards Computers, Performance Expectancy, Effort Expectancy, Social Influence,
Facilitating Conditions and Personal Innovativeness in IT.
In view of the fact that the achieved conceptual framework considers the particular characteristics of the health workers,
contributions and implications of this study are significant both at the theoretical level as well as the practical level. This
study not only provided some interesting findings and suggestions for practice but also produced a paradigm for scholars
who are interested in the behavior of technology adoption for health care sectors.
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Keywords
Health Management Information Systems, (HMIS) Among Health Workers