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Debre Markos University Institutional Research Repository allows users to browse by department to access and explore a wide range of academic outputs, including theses, dissertations, research papers, and other scholarly works. This system not only preserves the university's academic contributions but also enhances knowledge sharing by making research outputs readily available to students, researchers, and the wider community, fostering academic growth and innovation.

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Health care professionals’ intention to use digital health data hub working in East Gojjam Hospitals, Northwest Ethiopia: Technology acceptance modeling
Journal Article
Ayenew Sisay Gebeyew 1 , Sefefe Birhanu Tizie 1 , Bayou Tilahun Assaye 1 , Afework Edmealem 2 , Temesgen Feyu 1 , Habtamu Mekonen 3 , Tirsit Ketsela Zeleke 4 , Melese Getachew 4 , Andualem Fentahun 1 Submitted: May 15, 2025
College of Health Science Health Informatics
Abstract Preview:
Background: Digital health data hubs contribute significantly to finding the right solutions to health problems, which forms the basis for achieving sustainable development goals. However, in Ethiopia, the health system has been coming to one central hub for all data, there is limited evidence of health professionals' intentions to use these systems. Understanding their intentions is crucial, as this can significantly improve the advancement of digital health in healthcare organizations. This study assessed health professionals' intention to use digital health data hubs in hospitals in East Gojjam, northwest Ethiopia, in 2024.
Methods: A cross-sectional study design was used to conduct the study. Eleven hospitals were included in the study area. Using an a priori structural equation modeling sample size calculator, the total sample size was 616. Stratified proportional allocation sampling was performed. The study participants were selected using a systematic sample. Structural equation modeling (SEM) was used for the analysis. Because it is a more powerful multivariate technique for testing and evaluating multivariate causal relationships. The assumptions of SEM-like normality, average variance extracted (AVE), composite reliability (CR), Cronbach's alpha, confirmatory factor analysis (CFA), and model specifications were checked using Amos and Stata version 16.
Full Abstract:
Background: Digital health data hubs contribute significantly to finding the right solutions to health problems, which forms the basis for achieving sustainable development goals. However, in Ethiopia, the health system has been coming to one central hub for all data, there is limited evidence of health professionals' intentions to use these systems. Understanding their intentions is crucial, as this can significantly improve the advancement of digital health in healthcare organizations. This study assessed health professionals' intention to use digital health data hubs in hospitals in East Gojjam, northwest Ethiopia, in 2024.
Methods: A cross-sectional study design was used to conduct the study. Eleven hospitals were included in the study area. Using an a priori structural equation modeling sample size calculator, the total sample size was 616. Stratified proportional allocation sampling was performed. The study participants were selected using a systematic sample. Structural equation modeling (SEM) was used for the analysis. Because it is a more powerful multivariate technique for testing and evaluating multivariate causal relationships. The assumptions of SEM-like normality, average variance extracted (AVE), composite reliability (CR), Cronbach's alpha, confirmatory factor analysis (CFA), and model specifications were checked using Amos and Stata version 16.
Results: This study was conducted with a sample size of 616 healthcare professionals; 591 (95.94%) responded to the survey. The results showed that 57.69% (n = 341) of the healthcare professionals intended to use the digital health data hub. Further analysis showed that perceived usefulness (PU: β = 0.576, p = 0.000), perceived trust (PT: β = 0.116, p = 0.022), and attitude (β = 0.143, p = 0.043) significantly and positively influenced health professionals' intention to use digital health data hubs.
Conclusion: Overall, the findings showed that 42.31% of health professionals have low intention to use digital health data hubs. These shall be needed to improve their intentions to use digital health data hubs through targeted interventions. Therefore, focusing on critical factors, such as perceived usefulness, trust, and attitude are crucial factors to reinforce their intention to use the system. Additionally, overcoming implementation challenges and building trust is critical to the successful integration and use of digital health data hubs.
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Digital health data security practices among health professionals in low-resource settings: cross-sectional study in Amhara Region, Ethiopia
Journal Article
Ayenew Sisay Gebeyew1,2*, Wondwossen Zemene2, Binyam Chaklu Tilahun2, Nebyu Demeke Mengestie2, BerhanuFikade Endehabtu2, Zegeye Regasa Wordofa1, Mitiku Kassaw Takillo1, Gedefaw Belete Ashagrie3 and MelakuMolla Sisay4 Submitted: Feb 05, 2025
College of Health Science Health Informatics
Abstract Preview:
Introduction Protecting digital health data from unauthorized access, alteration, and destruction is a crucial aspectof healthcare digitalization. Currently, digital security breaches are becoming more common. Healthcare databreaches have compromised over 50 million medical records per year. In Ethiopia, health digitization has growngradually. However, there is a limitation of study in digital health security. Studying digital health data security helpsindividuals protect digital data as a baseline and contributes to developing a digital health security policy.Objective To assess the practice of healthcare professionals in digital health data security among specializedteaching referral hospitals in Amhara Region, Ethiopia.Method A cross-sectional study design supplemented by a qualitative purposive sampling method was usedto measure the digital data security practices of health professionals. The sample size was determined via singlepopulation proportion formula. A simple random sampling technique was used for the study participants. Then, self-administered questionnaires were administered. Multivariable logistic analysis was used to identify associated factorsusing STATA software. For the qualitative study, key informant interviews were used and analyzed using thematicanalysis approach via open-code software.Results Out of the 423 health professionals, 95.0% were involved in the survey. The finding indicates digital healthdata security practice of health professionals working at specialized teaching hospitals were 45.0%, CI: (40, 50). Healthprofessionals 41–45-year age group (AOR = 0.107), master’s degree (AOR = 2.45), postmaster’s degree (AOR = 3.87),time to visit the internet for more than two hours (AOR = 2.46), basic computer training (AOR = 2.77), training indigital data security (AOR = 2.14), and knowledge (AOR = 1.76) were associated with the practice of digital health datasecurity. For the qualitative study, three teams were prepared. The findings indicate digital health data security can beimproved through training, advanced knowledge and working with digital security.
Conclusion The practice of digital health data security in specialized teaching hospitals in the Amhara region wasinadequate. Therefore, it can be improved through enhancing education status, increasing the time needed to visitthe internet, providing computer training, and updating health professionals’ knowledge toward digital health datasecurity.Keywords Practice, Digital health, Digital data security, Health profession
Full Abstract:
Introduction Protecting digital health data from unauthorized access, alteration, and destruction is a crucial aspectof healthcare digitalization. Currently, digital security breaches are becoming more common. Healthcare databreaches have compromised over 50 million medical records per year. In Ethiopia, health digitization has growngradually. However, there is a limitation of study in digital health security. Studying digital health data security helpsindividuals protect digital data as a baseline and contributes to developing a digital health security policy.Objective To assess the practice of healthcare professionals in digital health data security among specializedteaching referral hospitals in Amhara Region, Ethiopia.Method A cross-sectional study design supplemented by a qualitative purposive sampling method was usedto measure the digital data security practices of health professionals. The sample size was determined via singlepopulation proportion formula. A simple random sampling technique was used for the study participants. Then, self-administered questionnaires were administered. Multivariable logistic analysis was used to identify associated factorsusing STATA software. For the qualitative study, key informant interviews were used and analyzed using thematicanalysis approach via open-code software.Results Out of the 423 health professionals, 95.0% were involved in the survey. The finding indicates digital healthdata security practice of health professionals working at specialized teaching hospitals were 45.0%, CI: (40, 50). Healthprofessionals 41–45-year age group (AOR = 0.107), master’s degree (AOR = 2.45), postmaster’s degree (AOR = 3.87),time to visit the internet for more than two hours (AOR = 2.46), basic computer training (AOR = 2.77), training indigital data security (AOR = 2.14), and knowledge (AOR = 1.76) were associated with the practice of digital health datasecurity. For the qualitative study, three teams were prepared. The findings indicate digital health data security can beimproved through training, advanced knowledge and working with digital security.
Conclusion The practice of digital health data security in specialized teaching hospitals in the Amhara region wasinadequate. Therefore, it can be improved through enhancing education status, increasing the time needed to visitthe internet, providing computer training, and updating health professionals’ knowledge toward digital health datasecurity.Keywords Practice, Digital health, Digital data security, Health profession
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Attitudes of Health Professionals Toward Digital Health Data Security in Northwest Ethiopia: Cross-Sectional Study
Journal Article
Ayenew Sisay Gebeyew 1,✉, Zegeye Regasa Wordofa 1, Ayana Alebachew Muluneh 2, Adamu Ambachew Shibabaw 3, Agmasie Damtew Walle 3, Sefefe Birhanu Tizie 1, Muluken Belachew Mengistie 1, Mitiku Kassaw Takillo 1, Bayou Tilahun Assaye 1, Adualem Fentahun Senishaw 1, Gizaw Hailye 1, Aynadis Worku Shimie 1, Fikadu Wake Butta 3 Submitted: Nov 06, 2024
College of Health Science Health Informatics
Abstract Preview:
Background
Digital health is a new health field initiative. Health professionals require security in digital places because cybercriminals target health care professionals. Therefore, millions of medical records have been breached for money. Regarding digital security, there is a gap in studies in limited-resource countries. Therefore, surveying health professionals’ attitudes toward digital health data security has a significant purpose for interventions.
Full Abstract:
Background
Digital health is a new health field initiative. Health professionals require security in digital places because cybercriminals target health care professionals. Therefore, millions of medical records have been breached for money. Regarding digital security, there is a gap in studies in limited-resource countries. Therefore, surveying health professionals’ attitudes toward digital health data security has a significant purpose for interventions.


Objective
This study aimed to assess the attitudes of health professionals toward digital health data security and their associated factors in a resource-limited country.


Methods
A cross-sectional study was conducted to measure health professionals’ attitudes toward digital health data security. The sample size was calculated using a single population. A pretest was conducted to measure consistency. Binary logistic regression was used to identify associated factors. For multivariable logistic analysis, a P value ≤.20 was selected using Stata software (version 16; StataCorp LP).


Results
Of the total sample, 95% (402/423) of health professionals participated in the study. Of all participants, 63.2% (254/402) were male, and the mean age of the respondents was 34.5 (SD 5.87) years. The proportion of health professionals who had a favorable attitude toward digital health data security at specialized teaching hospitals was 60.9% (95% CI 56.0%‐65.6%). Educational status (adjusted odds ratio [AOR] 3.292, 95% CI 1.16‐9.34), basic computer skills (AOR 1.807, 95% CI 1.11‐2.938), knowledge (AOR 3.238, 95% CI 2.0‐5.218), and perceived usefulness (AOR 1.965, 95% CI 1.063‐3.632) were factors associated with attitudes toward digital health data security.


Conclusions
This study aimed to assess health professionals’ attitudes toward digital health data security. Interventions on educational status, basic computer skills, knowledge, and perceived usefulness are important for improving health professionals’ attitudes. Improving the attitudes of health professionals related to digital data security is necessary for digitalization in the health care arena.
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Readiness of big health data analytics by technology-organization-environment (TOE) framework in Ethiopian health sectors
Journal Article
Bayou Tilahun Assaye a,*, Bekalu Endalew b, Maru Meseret Tadele a, Gizaw hailiye Teferie a, Abraham Teym c, Yidersal hune Melese d, Andualem fentahun senishaw a, Sisay Maru Wubante e, Habtamu Setegn Ngusie f, Aysheshim Belaineh Haimanot Submitted: Sep 27, 2024
College of Health Science Health Informatics
Abstract Preview:
Background: Big health data is a large and complex dataset that the health sector has collected andstored continuously to generate healthcare evidence for intervening the future healthcare un-certainty. However, data use for decision-making practices has been significantly low in devel-oping countries, especially in Ethiopia. Hence, it is critical to ascertain which elements influencethe health sector’s decision to adopt big health data analytics in health sectors. The aim of thisstudy was to identify the level of readiness for big health data analytics and its associated factorsin healthcare sectors.Methods: A cross-sectional study design was conducted among 845 target employees using thestructural equation modeling approach by using technological, organizational, and environ-mental (TOE) frameworks. The target population of the study was health sector managers, di-rectors, team leaders, healthcare planning officers, ICT/IT managers, and health professionals.For data analysis, exploratory factor analysis using SPSS 20.0 and structural equation modelingusing AMOS software were used.Result: 58.85 % of the study participants had big health data analytics readiness. Complexity (CX),Top management support (TMS), training (TR) and government law policies and legislation(GLAL) and government IT policies (GITP) had positive direct effect, compatibility (CT), andoptimism (OP) had negative direct effect on BD readiness (BDR)Conclusion: The technological, organizational, and environmental factors significantly contributedto big health data readiness in the healthcare sector. The Complexity, compatibility, optimism,Top management support, training (TR) and government law and IT policies (GITP) had effect onbig health data analytics readiness. Formulating efficient reform in healthcare sectors, especially
or evidence-based decision-making and jointly working with stakeholders will be more relevantfor effective implementation of big health data analytics in healthcare sectors.
Keywords: Big health data, Data analytics, Data management, Health information revolution, Health sectors, Readiness
Full Abstract:
Background: Big health data is a large and complex dataset that the health sector has collected andstored continuously to generate healthcare evidence for intervening the future healthcare un-certainty. However, data use for decision-making practices has been significantly low in devel-oping countries, especially in Ethiopia. Hence, it is critical to ascertain which elements influencethe health sector’s decision to adopt big health data analytics in health sectors. The aim of thisstudy was to identify the level of readiness for big health data analytics and its associated factorsin healthcare sectors.Methods: A cross-sectional study design was conducted among 845 target employees using thestructural equation modeling approach by using technological, organizational, and environ-mental (TOE) frameworks. The target population of the study was health sector managers, di-rectors, team leaders, healthcare planning officers, ICT/IT managers, and health professionals.For data analysis, exploratory factor analysis using SPSS 20.0 and structural equation modelingusing AMOS software were used.Result: 58.85 % of the study participants had big health data analytics readiness. Complexity (CX),Top management support (TMS), training (TR) and government law policies and legislation(GLAL) and government IT policies (GITP) had positive direct effect, compatibility (CT), andoptimism (OP) had negative direct effect on BD readiness (BDR)Conclusion: The technological, organizational, and environmental factors significantly contributedto big health data readiness in the healthcare sector. The Complexity, compatibility, optimism,Top management support, training (TR) and government law and IT policies (GITP) had effect onbig health data analytics readiness. Formulating efficient reform in healthcare sectors, especially
or evidence-based decision-making and jointly working with stakeholders will be more relevantfor effective implementation of big health data analytics in healthcare sectors.
Keywords: Big health data, Data analytics, Data management, Health information revolution, Health sectors, Readiness
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Willingness to use remote patient monitoring among cardiovascular patients in a resource-limited setting: a cross-sectional study
Journal Article
Mitiku Kassaw 1 , Getasew Amare 2 , Kegnie Shitu 3 , Binyam Tilahun 4 , Bayou Tilahun Assaye 1 Submitted: Sep 17, 2024
College of Health Science Health Informatics
Abstract Preview:
Introduction: Currently, mortality by non-communicable diseases is increasing alarmingly. They account for approximately 35 million deaths each year, of which 14% are due to cardiovascular disease and 9.2% occur in Africa. Patients do not have access to healthcare services outside the healthcare setting, resulting in missed follow-ups and appointments and adverse outcomes. This study aimed to assess the willingness to use remote monitoring among cardiovascular patients in a resource-limited setting in Ethiopia.
Method: An institution-based cross-sectional study was conducted from April to June 2021 among cardiovascular patients at referral hospitals in Ethiopia. A structured interview questionnaire was used to collect the data. A systematic random sampling technique was used to select 397 study participants. Binary and multivariable logistic regression analyses were employed and a 95% confidence level with a p-value
Full Abstract:
Introduction: Currently, mortality by non-communicable diseases is increasing alarmingly. They account for approximately 35 million deaths each year, of which 14% are due to cardiovascular disease and 9.2% occur in Africa. Patients do not have access to healthcare services outside the healthcare setting, resulting in missed follow-ups and appointments and adverse outcomes. This study aimed to assess the willingness to use remote monitoring among cardiovascular patients in a resource-limited setting in Ethiopia.
Method: An institution-based cross-sectional study was conducted from April to June 2021 among cardiovascular patients at referral hospitals in Ethiopia. A structured interview questionnaire was used to collect the data. A systematic random sampling technique was used to select 397 study participants. Binary and multivariable logistic regression analyses were employed and a 95% confidence level with a p-value
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