Aschalew Arega

Work place: Faculty of Computing and Software Engineering, Arba Minch University, Arba Minch, Ethiopia

E-mail: aschalew.arega1@gmail.com

Website:

Research Interests: Information Security, Cloud Computing, Information Technology

Biography

Aschalew Arega Ademe earned his M.Sc. in Information Systems from the Kobe Institute of Computing, Graduate School of Information Technology, KOBE, Japan, in 2017 and his B.Sc. in Information Systems from Addis Ababa University, Ethiopia, in 2012. He also holds a diploma in computer applications from Alpha College, Hawassa, Ethiopia, obtained in 2008. Currently, he is pursuing a Ph.D. in Computing and Information Technology at the Faculty of Computing and Software Engineering, Arba Minch University, Ethiopia. His prior experience includes serving as an assistant lecturer from 2012 to 2015 and a lecturer from 2018 to 2020 at Madda Walabu University, where he was also the Head of the Information Systems Department during two separate terms: 2013-2015 and 2019-2020. His research interests encompass cloud computing, information technology, computer applications technology, and information security.

Author Articles
Enhancing Healthcare Information Systems in Ethiopian Hospitals: Exploring Challenges and Prospects of a Cloud-based Model for Smart and Sustainable Information Services

By Aschalew Arega Durga Prasad Sharma

DOI: https://doi.org/10.5815/ijitcs.2024.05.01, Pub. Date: 8 Oct. 2024

Hospitals are the primary hubs for healthcare service providers in Ethiopia; however, hospitals face significant challenges in adopting digital health information systems solutions due to disparate, non-interoperable systems and limited access. Information technology, especially via cloud computing, is crucial in healthcare for efficient data management, secure storage, real-time access to critical information, seamless provider communication, enhanced collaboration, and scalable IT infrastructure. This study investigated the challenges to standardizing smart and green healthcare information services and proposed a cloud-based model for overcoming them. We conducted a mixed-methods study in 11 public hospitals, employing quantitative and qualitative approaches with diverse stakeholders (N = 103). The data was collected through surveys, interviews, and technical observations by purposive quota sampling with the Raosoft platform and analyzed using IBM SPSS. Findings revealed several shortcomings in existing information systems, including limited storage, scalability, and security; impaired data sharing and collaboration; accessibility issues; no interoperability; ownership ambiguity; unreliable data recovery; environmental concerns; affordability challenges; and inadequate policy enforcement. Notably, hospitals lacked a centralized data management system, cloud-enabled systems for remote access, and modern data recovery strategies. Despite these challenges, 90.3% of respondents expressed interest in adopting cloud-enabled data recovery systems. However, infrastructure limitations, inadequate cloud computing/IT knowledge, lack of top management support, digital illiteracy, limited innovation, and data security concerns were identified as challenges to cloud adoption. The study further identified three existing healthcare information systems: paper-based methods, electronic medical catalog systems, and district health information systems2. Limitations of the paper-based method include error-proneness, significant cost, data fragmentation, and restricted remote access. Growing hospital congestion and carbon footprint highlighted the need for sustainable solutions.  Based on these findings, we proposed a cloud-based model tailored to the Ethiopian context. This six-layered model, delivered as a Software-as-a-Service within a community cloud deployment, aims to improve healthcare services through instant access, unified data management, and evidence-based medical practices. The model demonstrates high acceptability and potential for improving healthcare delivery, and implementation recommendations are suggested based on the proposed model.

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