Accepted for/Published in: JMIR Human Factors
Date Submitted: Mar 7, 2023
Date Accepted: Oct 5, 2023
Intention to use electronic community health information system among health extension workers in rural northwest Ethiopia: using unified theory of acceptance and use technology 2(UTAUT2) model
ABSTRACT
Background:
Background:
Globally, information technology has brought remarkable change in bridging the digital gap in resource-constrained regions and advancing the healthcare system. Community-based information systems and mobile applications have been extensively developed and deployed to quantify and support health services delivered by community health workers. The success and failure of a digital health information system depend on the intention of health workers to use the technology. Ethiopia is scaling up its electronic Community Health Information System (eCHIS) to support the work of health extension workers (HEWs). However, evidence on behavioral intention to use eCHIS by HEWs for community health information system is not known to successful implementation and inform scale-up efforts. Therefore, this study was aimed to assess HEWs intention to use eCHIS among health extension workers in Northwest Ethiopia.
Objective:
To assess health extension workers intention to use electronic community health information system (eCHIS) in Northwest Ethiopia
Methods:
Methods:
A cross-sectional study design was conducted among 456 health extension workers in six pilot districts of the central Gondar zone, Northwest Ethiopia. A unified theory of acceptance and use technology model was used to investigate health extension workers’ intention to use electronic community health information system. Data were cleaned and entered into Epi-data 4.02 and exported to SPSS 26 version for analysis using AMOS 23 Structural Equation Model. Statistical significance of endogenous and exogenous variables in the model was reported using a 95% confidence interval with its corresponding P<0.05.
Results:
Results:
456 health extension workers participated in the study, with a response rate of 99%. The mean age of the study participants was 28 years +4.8 SD. Our study revealed that about 179 (39.3%) [95% CI: 34.7–43.9] of participants intended to use eCHIS for community health data generation, use, and service provision. Effort expectancy (β=0.256, P=.007), self-expectancy (β=0.096, P=.042), social influence (β=0.203, P=.017), and hedonic motivation (β=0.217, P=.030) were significantly associated with HEWs' intention to use eCHIS.
Conclusions:
Conclusion: The findings confirm that effort expectancy, self-expectancy, social influence, and hedonic motivation were statistically significant predictors of intention to use eCHIS. Enhancing ease of use, improving HEWs computer literacy, understanding the importance of people in the health system, and increasing motivation of HEWs towards using technology would help to be more effective in implementation of eCHIS program at community setting for health data management and service provision.
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