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Abstract Background The implementation of Electronic Health Record (EHR) systems is a critical challenge, particularly in low-income countries, where behavioral intention plays a crucial role. To address this issue, we conducted a study to extend and apply the Unified Theory of Acceptance and Use of Technology 3 (UTAUT3) model in predicting health professionals' behavioral intention to use EHR systems. Methods A quantitative research approach was employed among 423 health professionals in Southwest Ethiopia. We assessed the validity of the proposed model through measurement and structural model statistics. Analysis was done using SPSS AMOS version 23. Hypotheses were tested using structural equation modeling (SEM) analysis, and mediation and moderation effects were evaluated. The associations between exogenous and endogenous variables were examined using standardized regression coefficients (β), 95% confidence intervals, and p-values, with a significance level of p-value

Abstract Background Adverse birth outcomes, including preterm birth, low birth weight, and stillbirth, remain a major global health challenge, particularly in developing regions. Understanding the possible risk factors is crucial for designing effective interventions for birth outcomes. Accordingly, this study aimed to develop a predictive model for adverse birth outcomes among childbearing women in Sub-Saharan Africa using advanced machine learning techniques. Additionally, this study aimed to employ a novel data science interpretability techniques to identify the key risk factors and quantify the impact of each feature on the model prediction. Methods The study population involved women of childbearing age from 26 Sub-Saharan African countries who had given birth within five years before the data collection, totaling 139,659 participants. Our data source was a recent Demographic Health Survey (DHS). We utilized various data balancing techniques. Ten advanced machine learning algorithms were employed, with the dataset split into 80% training and 20% testing sets. Model evaluation was conducted using various performance metrics, along with hyperparameter optimization. Association rule mining and SHAP analysis were employed to enhance model interpretability. Results Based on our findings, about 28.59% (95% CI: 28.36, 28.83) of childbearing women in Sub-Saharan Africa experienced adverse birth outcomes. After repeated experimentation and evaluation, the random forest model emerged as the top-performing machine learning algorithm, with an AUC of 0.95 and an accuracy of 88.0%. The key risk factors identified were home deliveries, lack of prenatal iron supplementation, fewer than four antenatal care (ANC) visits, short and long delivery intervals, unwanted pregnancy, primiparous mothers, and geographic location in the West African region. Conclusion The region continues to face persistent adverse birth outcomes, emphasizing the urgent need for increased attention and action. Encouragingly, advanced machine learning methods, particularly the random forest algorithm, have uncovered crucial insights that can guide targeted actions. Specifically, the analysis identifies risky groups, including first-time mothers, women with short or long birth intervals, and those with unwanted pregnancies. To address the needs of these high-risk women, the researchers recommend immediately providing iron supplements, scheduling comprehensive prenatal care, and strongly encouraging facility-based deliveries or skilled birth attendance.

BackgroundDespite the potential of routine health information systems in tackling persistent maternal deaths stemming from poor service quality at health facilities during and around childbirth, research has demonstrated their suboptimal performance, evident from the incomplete and inaccurate data unfit for practical use. There is a consensus that nonfinancial incentives can enhance health care providers’ commitment toward achieving the desired health care quality. However, there is limited evidence regarding the effectiveness of nonfinancial incentives in improving the data quality of institutional birth services in Ethiopia. ObjectiveThis study aimed to evaluate the effect of performance-based nonfinancial incentives on the completeness and consistency of data in the individual medical records of women who availed institutional birth services in northwest Ethiopia. MethodsWe used a quasi-experimental design with a comparator group in the pre-post period, using a sample of 1969 women’s medical records. The study was conducted in the “Wegera” and “Tach-armacheho” districts, which served as the intervention and comparator districts, respectively. The intervention comprised a multicomponent nonfinancial incentive, including smartphones, flash disks, power banks, certificates, and scholarships. Personal records of women who gave birth within 6 months before (April to September 2020) and after (February to July 2021) the intervention were included. Three distinct women’s birth records were examined: the integrated card, integrated individual folder, and delivery register. The completeness of the data was determined by examining the presence of data elements, whereas the consistency check involved evaluating the agreement of data elements among women’s birth records. The average treatment effect on the treated (ATET), with 95% CIs, was computed using a difference-in-differences model. ResultsIn the intervention district, data completeness in women’s personal records was nearly 4 times higher (ATET 3.8, 95% CI 2.2-5.5; P=.02), and consistency was approximately 12 times more likely (ATET 11.6, 95% CI 4.18-19; P=.03) than in the comparator district. ConclusionsThis study indicates that performance-based nonfinancial incentives enhance data quality in the personal records of institutional births. Health care planners can adapt these incentives to improve the data quality of comparable medical records, particularly pregnancy-related data within health care facilities. Future research is needed to assess the effectiveness of nonfinancial incentives across diverse contexts to support successful scale-up.

Abstract Background Ensuring the data quality of Individual Medical Records becomes a crucial strategy in mitigating maternal and newborn morbidity and mortality during and around childbirth. However, previous research in Ethiopia primarily focused on studying data quality of institutional birth at the facility level, overlooking the data quality within Individual Medical Records. This study examined the data completeness and consistency within Individual Medical Records of the institutional birth service and associated factors. Methods An institution-based retrospective cross-sectional study was conducted in two districts of Northwest Ethiopia. Data were obtained by reviewing three sets of Individual Medical Records of 651 women: the delivery register, Integrated Individual Folder, and integrated card. The proportions of completeness and consistency were computed. A multilevel binary logistic regression was used to identify factors of completeness and consistency. An odds ratio with a 95% confidence interval was used to assess the level of significance. Results Overall, 74.0% of women’s Individual Medical Records demonstrated good data completeness ( > = 70%), 95%CI (70.5, 77.3), while 26% exhibited good consistency, 95%CI (22.9, 29.7). The presence of trained providers in data quality (AOR = 2.9, 95%CI: (1.5, 5.7)) and supportive supervision (AOR = 11.5, 95%CI: (4.8, 27.2)) were found to be associated with completeness. Health facilities’ practice of root cause analysis on data quality gaps (AOR = 8.7, 9%CI: (1.5, 50.9)) was statistically significantly associated with the consistency. Conclusions Most medical records were found to have good completeness, but nearly only a quarter of them found to contain consistent data. Completeness and consistency varied on the type of medical record. Health facility’s root cause analysis of data quality gaps, the presence of trained providers in data quality, and supportive supervision from higher officials were identified as factors affecting data quality in institutional birth service. These results emphasize the importance of focused efforts to enhance data completeness and consistency within Individual Medical Records, particularly through consideration of Individual Medical Records in future provider training, supervision, and the implementation of root cause analysis practices.

Abstract Background Evidence-based medicine (EBM) bridges research and clinical practice to enhance medical knowledge and improve patient care. However, clinical decisions in many African countries don’t base on the best available scientific evidence. Hence, this study aimed to determine the effect of training interventions on background knowledge and awareness of EBM sources, attitude, competence, and practice of EBM among healthcare professionals. Method We designed a controlled group quasi-experimental pre-post test study to evaluate the effect of capacity-building EBM training. A total of 192 healthcare professionals were recruited in the study (96 from the intervention and 96 from the control group). We used a difference-in-differences (DID) analysis to determine the effect of the training. Along the way, we used a fixed effect panel-data regression model to assess variables that could affect healthcare professionals’ practice of EBM. The cut point to determine the significant effect of EBM training on healthcare professionals’ background knowledge and awareness of EBM sources, attitude, and competence was at a P-value

Abstract Background Medical imaging plays a vital role in the accurate diagnosis, treatment and outcome prediction of many diseases and injuries. However, in many African countries, deserving populations do not have access to the proper medical imaging specialists’ services. As a result, clinicians continue to struggle to provide medical imaging via consultation. However, little is known about conventional referral consultation practices and their challenges. This study, therefore, aimed to explore the practice and challenges of medical imaging service consultation among health professionals and patients in the context of the Ethiopian public healthcare delivery system. Methods Descriptive phenomenological study was employed to explore the practice of medical imaging service consultation among health professionals and patients in public hospitals of Amhara region from October 12, 2021 to December 29, 2021. Semi-structured interview guides were prepared separately for key-informant and in-depth interviews. A total of 21 participants (6 hospital managers, 4 medical directors, 4 department heads, 3 medical imaging coordinators and 4 patients) were selected using the maximum variation sampling technique. All interviews were audio-recorded, transcribed verbatim and subjected to inductive thematic analysis using Open Code 4.02 software. Results Six major themes emerged following the thematic analysis: (1) medical image service delivery practices; (2) medical imaging consultation modalities; (3) benefits and drawbacks of the consultation modalities; (4) challenges; (5) challenge mitigation strategies; and (6) future recommendations. Image films, compact disks, and telegram apps were the consultation modalities used by the referring clinicians to send the medical images to radiologists. Frequent failure of imaging machines, delayed equipment maintenance, inadequate infrastructure, shortage of budget, lack of radiologists, and low-quality of printed image films were among the challenges influencing the medical imaging consultation service. Conclusions This research explored onsite and referral imaging consultation practices. However, there are many challenges encountered by the referring clinicians and the radiologists during the consultation process. These challenges could potentially affect clinicians’ ability to provide timely diagnosis and treatment services which would ultimately affects patient health status and service delivery. Virtual consultation via teleradiology and enhancing clinicians’ competence through long-term and short-term trainings are recommended to improve the referral consultation practice.

Conclusions: The study highlights the positive user perception of a web-based teleradiology system’s user-friendliness and efficiency. Overcoming challenges and leveraging facilitators are crucial for optimizing teleradiology and improving service delivery and patient outcomes. A centralized consultation center with dedicated radiologists and technical personnel is recommended for maximizing efficiency.

BackgroundConsidering individual differences caused by personality differences is crucial for end users' technology acceptance. However, previous studies overlooked the influence of users' technology readiness on technology acceptance. This study, therefore, aimed to evaluate the influence of technology readiness on teleradiology acceptance in the Amhara Regional State Public Hospitals using a technology readiness acceptance model.MethodsAn institutional-based cross-sectional mixed study design was conducted in September 2021 among 547 health professionals working at sixteen public hospitals in the Amhara region of northwest Ethiopia. Eight key informants were interviewed to explore organizational-related factors. Face-to-face and Google Meet approaches were used to collect the data. We applied structural equation modeling to investigate the influence of technology readiness on health professionals' teleradiology acceptance using Analysis of Moment Structures Version 23 software.ResultsOf the total participants, 70.2% and 85.7% were ready and intended to use teleradiology, respectively. According to technology readiness measuring constructs, optimism and innovativeness positively influenced health professionals' technology acceptance. Perceived ease of use and perceived usefulness showed a statistically positive significant effect on health professionals' intention to use teleradiology. In addition, a statistically significant mediation effect was observed between technology readiness measuring constructs and behavioral intention to use. Furthermore, a shortage of budget, inadequate infrastructure, and users' lack of adequate skills were reported as critical organizational challenges.ConclusionsWe found a higher proportion of readiness and intention to use teleradiology among health professionals. Personality difference measuring constructs and organizational factors played considerable influence on teleradiology acceptance. Therefore, before the actual implementation of teleradiology, ensuring the system's user-friendliness, improving infrastructure, allocating an adequate budget, and availing of capacity-building opportunities are recommended.

IntroductionGynecological cancers pose a significant threat to women worldwide, especially those in resource-limited settings. Human analysis of images remains the primary method of diagnosis, but it can be inconsistent and inaccurate. Deep learning (DL) can potentially enhance image-based diagnosis by providing objective and accurate results. This systematic review and meta-analysis aimed to summarize the recent advances of deep learning (DL) techniques for gynecological cancer diagnosis using various images and explore their future implications.MethodsThe study followed the PRISMA-2 guidelines, and the protocol was registered in PROSPERO. Five databases were searched for articles published from January 2018 to December 2022. Articles that focused on five types of gynecological cancer and used DL for diagnosis were selected. Two reviewers assessed the articles for eligibility and quality using the QUADAS-2 tool. Data was extracted from each study, and the performance of DL techniques for gynecological cancer classification was estimated by pooling and transforming sensitivity and specificity values using a random-effects model.ResultsThe review included 48 studies, and the meta-analysis included 24 studies. The studies used different images and models to diagnose different gynecological cancers. The most popular models were ResNet, VGGNet, and UNet. DL algorithms showed more sensitivity but less specificity compared to machine learning (ML) methods. The AUC of the summary receiver operating characteristic plot was higher for DL algorithms than for ML methods. Of the 48 studies included, 41 were at low risk of bias.ConclusionThis review highlights the potential of DL in improving the screening and diagnosis of gynecological cancer, particularly in resource-limited settings. However, the high heterogeneity and quality of the studies could affect the validity of the results. Further research is necessary to validate the findings of this study and to explore the potential of DL in improving gynecological cancer diagnosis.

Abstract Background Low and lower middle-income countries suffer lack of healthcare providers and proper workforce education programs, a greater spread of illnesses, poor surveillance, efficient management, etc., which are addressable by a central policy framework implementation. Accordingly, an eHealth policy framework is required specifically for these countries to successfully implement eHealth solutions. This study explores existing frameworks and fills the gap by proposing an eHealth policy framework in the context of developing countries. Methods This PRISMA-based (PRISMA Preferred Reporting Items For Systematic Reviews and Meta-Analyses) systematic review used Google Scholar, IEEE, Web of Science, and PubMed latest on 23rd May 2022, explored 83 publications regarding eHealth policy frameworks, and extracted 11 publications scrutinizing eHealth policy frameworks in their title, abstract, or keywords. These publications were analyzed by using both expert opinion and Rstudio programming tools. They were explored based on their developing/developed countries’ context, research approach, main contribution, constructs/dimensions of the framework, and related categories. In addition, by using cloudword and latent semantic space techniques, the most discussed concepts and targeted keywords were explored and a correlation test was conducted to depict the important concepts mentioned in the related literature and extract their relation with the targeted keywords in the interest of this study. Results Most of these publications do not develop or synthesize new frameworks for eHealth policy implementation, but rather introduce eHealth implementation frameworks, explain policy dimensions, identify and extract relevant components of existing frameworks or point out legal or other relevant eHealth implementation issues. Conclusion After a thorough exploration of related literature, this study identified the main factors affecting an effective eHealth policy framework, found a gap in the context of developing countries, and proposed a four-step eHealth policy implementation guideline for successful implementation of eHealth in the context of developing. The limitation of this study is the lack of a proper amount of practically implemented eHealth policy framework cases in developing countries published in the literature for the review. Ultimately, this study is part of the BETTEReHEALTH (More information about the BETTEReHEALTH project at https://betterehealth.eu ) project funded by the European Union Horizon’s 2020 under agreement number 101017450.

Abstract Background We already know that incorporating information and Communication technology (ICT) into every aspect of human activity result in significant change and makes tasks easier to complete. It can help in areas of healthcare systems and medical education. Therefore, this study aimed to assess utilization ICT and its associated factors among Arba Minch University College Medicine and Health Science students. Methods A cross sectional study design was conducted in June through August 2021 among under graduate students in college of medicine and health science at Arba Minch University, Ethiopia. A self-administered questionnaire was used to collect information on the students’ socio-demographic factors as well as the utilization ICT. The data entry form was prepared with Epi-data 3.1 versions software and STATA version 14 software was used to analyze the data. Results A total of 355 participants enrolled in the study, with a response rate of 98.34%. The percentage of students who used ICT was 55.77% [95% CI, 0.50, 0.60]. Regarding of field of study, health informatics students (84%) used the most ICT, while midwifery students (52%) used the least. Urban resident [AOR = 1.85, 95% CI = 1.08, 3.16], ICT knowledge [AOR = 3.8, 95% CI = 2.25, 6.40], having formal training of ICT [AOR = 1.9, 95% CI = 1.06,3.48], having IT in current course study [AOR = 2.2, 95% CI = 1.23, 3.84], and had good IT skill [AOR = 2.4, 95% CI = 1.34, 4.23] revealed a significant and positive correlation with the use of ICT. Conclusion In the current study previous residence, ICT knowledge, having formal training, having IT in current courses, and IT skill were significantly associated with student ICT utilization. Therefore, the university should continue to invest in professional development in order to improve teaching and student performance, as well as provide the college with student-centered ICT computer labs to encourage students to use technology.

Plain language summary Sexually Transmitted Infections (STIs) are infections commonly spread through sexual contact and transmitted by bacteria, viruses, or parasites and are the most common cause of illness among university students. Information-seeking behavior related to STIs is a means by which individuals sought information related to sexual health, disease, health risk, and health promotion. Communicating STIs and sexual risk behaviors during youth, particularly among university students, is effective in reducing STI-related problems. Lack of access to health information, lack of communication, and insufficient information about STIs are key issues that have contributed to the high prevalence of STIs. In Ethiopia, information-seeking behavior related to STIs and information use culture for improving the sexual health of individuals and the communities is limited. Therefore, the purpose of this study was to assess STI information-seeking behavior and its associated factors among students at the University of Gondar. More than half of the students sought STI-related information seeking in the past year. From those STI-related information seekers, the majority of students preferred the internet as a primary source for STI-related information. Field of study, year of study, internet access, digital literacy, sexual experiences, had STI symptoms, Perceived susceptibility, and perceived severity of STI were significant factors associated with STI information-seeking. Students' STI information-seeking behavior could be improved by increasing digital literacy and enhancing computer and internet access.

IntroductionDespite the high expectations of electronic medical records as a great prospect for improving performance in healthcare, the level of adoption and utilization, particularly in a developing country, is low. Knowing the willingness to use the electronic medical record system in the private hospital has an impact on the future implementation status and utilization of the electronic medical record in Ethiopia. However, there was no evidence of the status of the willingness to use electronic medical record systems in private hospitals in the Amhara region. This study aimed to assess the willingness to use electronic medical record Systems and its associated factors among health professionals working in Amhara Region Private Hospitals.MethodsA cross-sectional institutional study was performed among 406 health professionals selected using proportional allocation with a simple random sampling technique in Amhara region private hospitals by using self-administered structured questionnaires. The data were analyzed using SPSS version 20 software. Descriptive statistics and binary logistic regression were performed to estimate the crude and adjusted odds ratios with a 95% Confidence interval.ResultsOut of the 406 participants included in the analysis, 307 (75.6%) showed a willingness to use the electronic medical record system. About three hundred twelve (76.8%) health professionals had good knowledge of electronic medical record systems, and 257 (63.3%) had good computer skills in electronic medical record systems. Health professionals who had electronic medical record knowledge (AOR = 1.85, 95% CI (1.004-3.409)), EMR training (3.29, 95% CI (1.353-8.003)), technical support personnel (1.92, 95% CI (1.122-3.305)), supportive supervision (AOR = 1.97, 95% CI (1.072-3.628)), and computer skill on electronic medical record (1.77, 95% CI (1.002-3.148)) were significantly associated with the outcome variable.ConclusionsThis finding shows a good proportion of willingness to use the electronic medical record system. The most significant factors associated with willingness to use the electronic medical record system were a lack of computer skills, computer training, and knowledge of the electronic medical record system.

BackgroundDigital health literacy is the use of information and communication technology to support health and health care. Digital health literacy is becoming increasingly important as individuals continue to seek medical advice from various web-based sources, especially social media, during the pandemics such as COVID-19. ObjectiveThe study aimed to assess health professionals’ digital health literacy level and associated factors in Southwest Ethiopia in 2021. MethodsAn institution-based cross-sectional study was conducted from January to April 2021 in Ethiopia. Simple random sampling technique was used to select 423 study participants among health professionals. SPSS (version 20) software was used for data entry and analysis. A pretested self-administered questionnaire was used to collect the required data. Multivariable logistic regression was used to examine the association between the digital health literacy skill and associated factors. Significance value was obtained at 95% CI and P15,000 Ethiopian birr (>US $283.68; AOR 7.55, 95% CI 6.43-9.44; P15,000 Ethiopian birr (>US $283.68), good knowledge of digital health literacy, favorable attitude, and perceived usefulness were the most determinant factors in the study. Having high computer literacy, frequent use of internet, perceived ease of use, perceived usefulness, favorable attitude, and a high level of education will help to promote a high level of digital health literacy.

BackgroundWeak health information systems (HISs) hobble countries’ abilities to effectively manage and distribute their resources to match the burden of disease. The Capacity Building and Mentorship Program (CBMP) was implemented in select districts of the Amhara region of Ethiopia to improve HIS performance; however, evidence about the effectiveness of the intervention was meager. ObjectiveThis study aimed to determine the effectiveness of routine health information use for evidence-based decision-making among health facility and department heads in the Amhara region, Northwest Ethiopia. MethodsThe study was conducted in 10 districts of the Amhara region: five were in the intervention group and five were in the comparison group. We employed a quasi-experimental study design in the form of a pretest-posttest comparison group. Data were collected from June to July 2020 from the heads of departments and facilities in 36 intervention and 43 comparison facilities. The sample size was calculated using the double population formula, and we recruited 172 participants from each group. We applied a difference-in-differences analysis approach to determine the effectiveness of the intervention. Heterogeneity of program effect among subgroups was assessed using a triple differences method (ie, difference-in-difference-in-differences [DIDID] method). Thus, the β coefficients, 95% CIs, and P values were calculated for each parameter, and we determined that the program was effective if the interaction term was significant at P

Abstract Background Electronic Medical Records (EMRs) are systems to store patient information like medical histories, test results, and medications electronically. It helps to give quality service by improving data handling and communication in healthcare setting. EMR implementation in developing countries is increasing exponentially. But, only few of them are successfully implemented. Intention to use EMRs by health care provider is crucial for successful implementation and adoption of EMRs. However, intention of health care providers to use EMR in Ethiopia is unknown. Objective The aim of this study was to assess health care provider’s intention to use and its predictors towards Electronic Medical Record systems at three referral hospitals in north-west, Ethiopia, 2019. Methods Institutional based cross-sectional explanatory study design was conducted from March to September among 420 health care providers working at three referral hospitals in north-west Ethiopia. Data were analyzed using structural equation model (SEM). Simple and multiple SEM were used to assess the determinants of health care providers intention to use EMRs. Critical ratio and standardized coefficients were used to measure the association of dependent and independent variables, 95% confidence intervals and P-value were calculated to evaluate statistical significance. Qualitative data was analyzed using thematic analysis. Result The mean age of the study subjects was 32.4 years ±8.3 SD. More than two-third 293(69.8%) of the participants were male. Among 420 health care providers, only 167 (39.8%) were scored above the mean of intention to use EMRs. Factors positively associated with intention to use EMRs were performance expectancy (β = 0.39, p

Abstract Background Chronic patients persistently seek for health information on the internet for medication information seeking, nutrition, disease management, information regarding disease preventive actions and so on. Consumers ability to search, find, appraise and use health information from the internet is known as eHealth literacy skill. eHealth literacy is a congregate set of six basic skills (traditional literacy, health literacy, information literacy, scientific literacy, media literacy and computer literacy). The aim of this study was to assess eHealth literacy level and associated factors among internet user chronic patients in North-west Ethiopia. Methods Institutional based cross-sectional study design was conducted. Stratified sampling technique was used to select 423 study participants among chronic patients. The eHealth literacy scale (eHEALS) was used for data collection. The eHEALS is a validated eight-item Likert scaled questionnaire used to asses self-reported capability of eHealth consumers to find, appraise, and use health related information from the internet to solve health problems. Statistical Package for Social science version 20 was used for data entry and further analysis. Multivariable logistic regression was used to examine the association between the eHealth literacy skill and associated factors. Significance was obtained at 95% CI and p

Background The World Health Organization (WHO) encourages breastfeeding to begin within the first hour after birth in order to save children’s lives. In Ethiopia, different studies are done on the prevalence and determinants of breastfeeding initiation, up to our knowledge, the spatial distribution and the spatial determinants of breast feeding initiation over time are not investigated. Therefore, the objectives of this study were to assess spatial variation and its spatial determinant of delayed initiation of breastfeeding in Ethiopia using Geographically Weighted Regression (GWR). Methods A cross-sectional study was undertaken using the nationally representative 2016 Ethiopian Demographic and Health Survey (EDHS) dataset. Global Moran’s I statistic was used to measure whether delayed breastfeeding initiation was dispersed, clustered, or randomly distributed in study area. Ordinary Least Squares (OLS) regression was used to identify factors explaining the geographic variation in delayed breastfeeding initiation. Besides, spatial variability of relationships between dependent and selected predictors was investigated using geographically weighted regression. Result A total weighted sample of 4169 children of aged 0 to 23 months was included in this study. Delayed initiation of breastfeeding was spatially varies across the country with a global Moran’s I value of 0.158 at (p-valueConclusion In Ethiopia initiation of breastfeeding varies geographically across region. A significant hotspot was identified in the Amhara, Afar, and Tigray regions. The GWR analysis revealed that orthodox religion, poor wealth index, caesarian section, baby postnatal checkup, and small birth weight were spatially significant factors.

BackgroundIn almost all lower and lower middle-income countries, the healthcare system is structured in the customary model of in-person or face to face model of care. With the current global COVID-19 pandemics, the usual health care service has been significantly altered in many aspects. Given the fragile health system and high number of immunocompromised populations in lower and lower-middle income countries, the economic impacts of COVID-19 are anticipated to be worse. In such scenarios, technological solutions like, Telemedicine which is defined as the delivery of healthcare service remotely using telecommunication technologies for exchange of medical information, diagnosis, consultation and treatment is critical. The aim of this study was to assess healthcare providers' acceptance and preferred modality of telemedicine and factors thereof among health professionals working in Ethiopia.MethodsA multi-centric online survey was conducted via social media platforms such as telegram channels, Facebook groups/pages and email during Jul 1- Sep 21, 2020. The questionnaire was adopted from previously validated model in low income setting. Internal consistency of items was assessed using Cronbach alpha (α), composite reliability (CR) and average variance extracted (AVE) to evaluate both discriminant and convergent validity of constructs. The extent of relationship among variables were evaluated by Structural equation modeling (SEM) using SPSS Amos version 23.ResultsFrom the expected 423 responses, 319 (75.4%) participants responded to the survey questionnaire during the data collection period. The majority of participants were male (78.1%), age ConclusionThis study found that effort expectancy and attitude were significantly predictors of healthcare professionals' acceptance of telemedicine. Attitude toward using telemedicine systems was also highly influenced by performance expectancy, self-efficacy and facilitating conditions. effort expectancy and attitude were also significant mediators in predicting users' acceptance of telemedicine. In addition, mHealth approach was the most preferred modality of telemedicine and this opens an opportunity to integrate telemedicine systems in the health system during and post pandemic health services in low-income countries.