Healthcare Professionals' Attitude to Using Mobile Health Technology and Its Associated Factors in a Resource-Limited Country-An Implication for Digital Health Implementers: A Cross Sectional Study.

Background: Mobile health has become widely used within the healthcare system, and there is an increasing worldwide trend toward employing this innovation for behavior management, disease monitoring, the control and prevention of various health issues, and rising enrollment in healthcare services. Although mHealth is becoming more widely available, there is no evidence about the attitude of healthcare professionals toward mHealth in southwest Ethiopia. Therefore, this study is aimed at assessing the attitude of healthcare professionals to using mHealth technology and associated factors in Ethiopia. Methods: An institutional cross-sectional study was conducted among 422 healthcare professionals. Data were collected using a pretested interviewer-administered questionnaire, and the study was conducted from January 08 to February 10, 2023. EpiData Version 4.6 for entering the data and STATA Version 14 for analyzing the data were used. A multivariable logistic regression analysis was carried out to identify factors associated with healthcare professionals' attitudes to using mobile health technology. Results: A total of 415 study participants were included in the study. About 180 (43.4%) respondents had a favorable attitude toward mHealth technology in southwest public hospitals. Master's degree and above (adjusted odds ratio [AOR]: 3.67; 95% CI: 1.22, 4.10), good knowledge of mobile health technology (AOR: 4.08; 95% CI: 1.35, 5.31), more than 5 years of work experience (AOR: 3.09; 95% CI: 1.76, 5.60), had ICT infrastructure (AOR: 2.70; 95% CI: 1.38, 5.31), had own smart mobile (AOR: 3.67; 95% CI: 3.20, 4.31), and had taken computer-related training (AOR: 1.96; 95% CI: 1.03, 3.73) were positively associated with healthcare professionals' attitude to using mobile health technologies in southwest Ethiopia. Conclusions: Overall, healthcare professionals' attitude to using mobile health technologies in southwest Ethiopia was relatively low. Education level, good knowledge, years of work experience, ICT infrastructure, having a smart mobile, and having taken computer-related training were significant factors of attitude to using mobile health technologies. Considering these factors could provide insight into developing and adopting mobile health technologies in Ethiopia.

Healthcare professionals' willingness to utilize a mobile health application for adverse drug reaction reporting in a limited resource setting: An input for digital health, 2023.

Background: Adverse drug reactions (ADRs) are a significant public health concern, particularly in limited resource settings where underreporting is prevalent due to various challenges. Mobile health applications (mHealth apps) offer a promising solution to enhance pharmacovigilance by facilitating easier and more efficient ADR reporting. However, despite the increasing availability and use of mHealth apps, there is a lack of evidence on healthcare professionals' willingness to adopt them for ADR reporting in resource-constrained environments. Therefore, this study aimed to assess the willingness of healthcare professionals in Ethiopia to utilize mobile health applications for adverse drug reaction reporting and identify associated factors. Methods: We carried out a cross-sectional study involving 422 healthcare professionals working in institutional settings. We gathered data through a pretested questionnaire that participants completed themselves. We inputted the data using Epi Data V.4.6 and analyzed it using SPSS V.26. Our analysis involved conducting multivariable logistic regression to identify the factors influencing the likelihood of healthcare professionals using mobile applications to report adverse drug reactions. Results: The study involved 389 healthcare professionals. Approximately 301 (77.4 %) of them expressed willingness to utilize mobile applications for reporting adverse drug reactions. The willingness to utilize mobile applications was significantly associated with the type of mobile phone (smart: AOR 3.56; 95 % CI 2.15-5.67), basic computer training (AOR 4.43; 95 % CI 2.27-8.64), mobile health-related training (AOR 1.96; 95 % CI 1.01-3.79), attitude (AOR 4.01; 95 % CI 2.19-7.35), perceived ease of use (AOR 2.91; 95 % CI 1.59-5.23), and perceived usefulness (AOR 2.10; 95 % CI 1.15-3.85). Conclusions: Overall, there was a high proportion of healthcare professionals willing to use mobile devices for reporting drug adverse reactions. Their willingness correlated with factors such as the type of mobile phone, perceived ease of use, attitude, training, and perceived usefulness of mobile applications. With the increasing use of smartphones, motivation among healthcare professionals is rising. Basic computer and mHealth-related training are crucial for enhancing the acceptability of such applications and should be incorporated into future implementations. Taking these factors into account could offer insights into the design and implementation of mobile applications for adverse drug reactions in Ethiopia.

Birth preparedness and pregnancy complication readiness and associated factors among pregnant women in Ethiopia: A multilevel analysis.

Maternal and child deaths occur during pregnancy and delivery. Timely information on signs of pregnancy complications and ways to plan for normal birth is a strategy to reduce maternal and child deaths. The purpose of this study was to assess birth preparedness, and pregnancy complications readiness and identify associated factors in Ethiopia. A cross-sectional study design was used. A total of 1635 weighted samples of pregnant women were included for analysis from the 2016 Ethiopian demographic and health survey data set. Multilevel mixed-effect logistic regression was used to estimate the effects of potential variables on birth preparedness and complication readiness. STATA version 15 software was used for data processing and analysis. A variable with a p-value < 0.05 with a 95% confidence interval was considered a significant factor. Pregnant women were informed about convulsions (8.02%), fever (35.95%), abdominal pain (28.92%), leaking fluid from the vagina (28.21%), and blurred vision (17.98%). Pregnant women prepared for supplies needed for birth (38.70%), transportation (20.04%), money (18.97%), people's support for birth (5.03%), and blood donors (3.11%). Only 56% and 44.91% of pregnant women had good birth preparedness and were informed about pregnancy complications respectively. Educational status, antenatal care visits, and region were significant factors associated with birth preparedness and complication readiness. Distance to health facility and residency were significantly associated with birth and complication readiness, respectively. Birth preparedness and complication readiness among pregnant women were low in Ethiopia. Empowering women with education, installing safe roads, building accessible health facilities, and emphasizing pregnancy complications and birth preparedness plans during antenatal care visits are important interventions to enhance birth preparedness and pregnancy complication readiness.

Evaluating digital literacy of health professionals in Ethiopian health sectors: A systematic review and meta-analysis.

BACKGROUND: Digital literacy refers to the capacity to critically assess digital content, use digital tools in professional settings, and operate digital devices with proficiency. The healthcare sector has rapidly digitized in the last few decades. This systematic review and meta-analysis aimed to assess the digital literacy level of health professionals in the Ethiopian health sector and identify associated factors. The study reviewed relevant literature and analyzed the data to provide a comprehensive understanding of the current state of digital literacy among health professionals in Ethiopia. METHODS: The study was examined by using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) criteria. Evidence was gathered from the databases of Google Scholar, Pub Med, Cochrane Library, Hinari, CINAHL, and Global Health. Consequently, five articles met the eligible criteria for inclusion. The analysis was carried out using STATA version 11. The heterogeneity was evaluated using the I2 test, while the funnel plot and Egger's regression test statistic were used to examine for potential publication bias. The pooled effect size of each trial is evaluated using a random effect model meta-analysis, which provides a 95% confidence interval. RESULT: A total of five articles were included in this meta-analysis and the overall pooled prevalence of this study was 49.85% (95% CI: 37.22-62.47). six variables, Monthly incomes AOR = 3.89 (95% CI: 1.03-14.66), computer literacy 2.93 (95% CI: 1.27-6.74), perceived usefulness 1.68 (95% CI: 1.59-4.52), educational status 2.56 (95% CI: 1.59-4.13), attitude 2.23 (95% CI: 1.49-3.35), perceived ease of use 2.22 (95% CI: 1.52-3.23) were significantly associated with the outcome variable. CONCLUSION: The findings of the study revealed that the overall digital literacy level among health professionals in Ethiopia was relatively low. The study highlights the importance of addressing the digital literacy gap among health professionals in Ethiopia. It suggests the need for targeted interventions, such as increasing monthly incomes, giving computer training, creating a positive attitude, and educational initiatives, to enhance digital literacy skills among health professionals. By improving digital literacy, health professionals can effectively utilize digital technologies and contribute to the advancement of healthcare services in Ethiopia.

Machine learning algorithms' application to predict childhood vaccination among children aged 12-23 months in Ethiopia: Evidence 2016 Ethiopian Demographic and Health Survey dataset.

INTRODUCTION: Childhood vaccination is a cost-effective public health intervention to reduce child mortality and morbidity. But, vaccination coverage remains low, and previous similar studies have not focused on machine learning algorithms to predict childhood vaccination. Therefore, knowledge extraction, association rule formulation, and discovering insights from hidden patterns in vaccination data are limited. Therefore, this study aimed to predict childhood vaccination among children aged 12-23 months using the best machine learning algorithm. METHODS: A cross-sectional study design with a two-stage sampling technique was used. A total of 1617 samples of living children aged 12-23 months were used from the 2016 Ethiopian Demographic and Health Survey dataset. The data was pre-processed, and 70% and 30% of the observations were used for training, and evaluating the model, respectively. Eight machine learning algorithms were included for consideration of model building and comparison. All the included algorithms were evaluated using confusion matrix elements. The synthetic minority oversampling technique was used for imbalanced data management. Informational gain value was used to select important attributes to predict childhood vaccination. The If/ then logical association was used to generate rules based on relationships among attributes, and Weka version 3.8.6 software was used to perform all the prediction analyses. RESULTS: PART was the first best machine learning algorithm to predict childhood vaccination with 95.53% accuracy. J48, multilayer perceptron, and random forest models were the consecutively best machine learning algorithms to predict childhood vaccination with 89.24%, 87.20%, and 82.37% accuracy, respectively. ANC visits, institutional delivery, health facility visits, higher education, and being rich were the top five attributes to predict childhood vaccination. A total of seven rules were generated that could jointly determine the magnitude of childhood vaccination. Of these, if wealth status = 3 (Rich), adequate ANC visits = 1 (yes), and residency = 2 (Urban), then the probability of childhood vaccination would be 86.73%. CONCLUSIONS: The PART, J48, multilayer perceptron, and random forest algorithms were important algorithms for predicting childhood vaccination. The findings would provide insight into childhood vaccination and serve as a framework for further studies. Strengthening mothers' ANC visits, institutional delivery, improving maternal education, and creating income opportunities for mothers could be important interventions to enhance childhood vaccination.

The effect of capacity building evidence-based medicine training on its implementation among healthcare professionals in Southwest Ethiopia: a controlled quasi-experimental outcome evaluation.

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 < 0.05. RESULT: The DID estimator showed a significant net change of 8.0%, 17.1%, and 11.4% at P < 0.01 on attitude, competence, and practice of EBM, respectively, whereas no significant increment in the background knowledge and awareness of EBM sources. The fixed effect regression model showed that the attitude [OR = 2.288, 95% CI: (1.049, 4.989)], competence [OR = 4.174, 95% CI: 1.984, 8.780)], technical support [OR = 2.222, 95% CI: (1.043, 3.401)], and internet access [OR = 1.984, 95% CI: (1.073, 4.048)] were significantly affected EBM practice. CONCLUSION: The capacity-building training improved attitude, competence, and EBM practice. Policymakers, government, and other concerned bodies recommended focusing on a well-designed training strategy to enhance the attitude, competence, and practice towards EBM among healthcare professionals. It was also recommended to enhance internet access and set mechanisms to provide technical support at health facilities.

Exploring facilitators and barriers of the sustainable acceptance of e-health system solutions in Ethiopia: A systematic review.

BACKGROUND: eHealth is the use of information and communications technologies in support of health and health-related fields, including healthcare services, health surveillance, health literature, and health education knowledge and research, has the potential to improve the delivery and support of healthcare services by promoting information sharing and evidence-based health practice. Acceptance of e-health in Ethiopia using systematic review is uncertain. As a result, this study aimed to assess barriers and facilitators of the sustainable acceptance of e-health system adoption in Ethiopia through a systematic review of the literature. METHODS: The Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) checklist was used to conduct this study. Relevant articles have been searched in Google Scholar, Medline, PubMed, Embrace, Web of Science, Scopus, Cochrane Library, and empirical research done in Ethiopia is the main emphasis of the search strategy. The total number of studies that satisfied the criteria for inclusion was ten. In this research, empirical data related to e-health acceptance factors were retrieved, examined, and summarized by the authors. RESULTS: This systematic review identified a total of 25 predictors that have been found in the ten studies. The identified facilitators were effort expectancy, performance expectancy, facilitating conditions, social influences, attitude, computer literacy, participant age, perceived enjoyment, and educational status, duration of mobile device use, organizational culture, and habit. Moreover, technology anxiety was the most barrier to sustainable acceptance of e-health systems in Ethiopia. CONCLUSIONS: The most common facilitator identified from the predictors was effort expectancy, which played a major role in the adoption of the e-health system in Ethiopia. Therefore, eHealth implementers and managers in those settings should give users of the system priority in improving the technical infrastructure by regularly providing them with basic facilitating conditions. They should also pay attention to the system they want to implement because doing so will improve the users' perception of the system's value and attitude.

Systematic review and meta-analysis of knowledge on PMTCT of HIV/AIDS and Association factors among reproductive age women in Ethiopia, 2022.

BACKGROUND: Despite increased interventions implemented for the prevention of mother-to-child transmission of HIV, There is still a vertical transmission. Hence, this study tried to assess the pooled prevalence of knowledge on PMTCT and factors associated with residence, ANC follow-up, and knowledge about HIV/AIDS among reproductive age women in Ethiopia. METHODS: The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guideline was followed to review either published or unpublished studies in Ethiopia regarding knowledge on PMTCT. A comprehensive search of international databases, including Google Scholar, Cochrane Library, PubMed, HINARI, Embrace, Web of Science, Scopus, ProQuest, CINAHL, and Global Health, were searched. The data were analyzed using STATA/SE version 14. The random-effect model was used to estimate the effect size, and I-squared statistics and Egger's test were used to assess the heterogeneity and publication bias, respectively. RESULTS: 14 out of 14,091 assessed articles met inclusion criteria and were included in the analysis. The estimated pooled level of knowledge on PMTCT among reproductive-age groups was 62.15% [(95% CI: 43.63-80.66)]. Residence [(OR = 4.8, 95%CI: 2.99, 7.85)], ANC follow-up [(OR = 4.2, 95%CI: 2.21, 7.98)], and having sufficient knowledge about the diseases [(OR = 4.9, 95% CI: 3.6, 6.66)] were found to be significant predictors of knowledge on PMTCT among reproductive-age groups. CONCLUSION: Strategies to improve the knowledge of PMTCT in Ethiopia should focus on rural women, improving knowledge about HIV/AIDS, and ANC follow-up. Efforts are also needed to involve husbands and related organization in the prevention of mother to child transmission of HIV.

Spatial distribution of short birth interval and associated factors among reproductive age women in Ethiopia: spatial and multilevel analysis of 2019 Ethiopian mini demographic and health survey.

BACKGROUND: Short Birth Interval negatively affects the health of both mothers and children in developing countries. Studies conducted in Ethiopia on the spatial variation and determinants of individual and community-level factors about short birth intervals were limited. Thus, this study was intended to assess the spatial variation of the short birth interval and its determinants in Ethiopia. METHODS: This study is a secondary analysis of the Ethiopian Demographic and Health Survey (mini EDHS 2019). A total of 1784 reproductive-age women were included in the analysis. The global spatial autocorrelation (Global Moran's I) and the Getis-Ord statistics tool were used to detect the presence of clustering and the high/low hotspot areas of SBI respectively. Ordinary kriging was used to interpolate short birth intervals, and spatial scan statistics were employed to identify spatial clusters with high and low SBI. A multilevel multivariable model was used to identify predictors of a short birth interval. RESULTS: The prevalence of SBI was 62.89% (95%CI: 59.3, 69.7) in Ethiopia. High clustering of SBI was observed in all parts of Somali, in Afar (zones 1, 3, 4, &5), Oromia (Guje, Bale, & West Harerge), and northern Tigray. The most likely significant primary cluster was observed in the Somali region. Women who lived in the primary cluster were 24% more likely to have a short birth interval than those who lived outside the window. In the multilevel mixed-effect analysis age 25-34 [(AOR = 0.40, 95% CI: 0.35, 0.45)], 35-49 [(AOR = 0.44, 95% CI: 0.38, 0.51)], Muslim religion follower [(AOR = 3.5, 95% CI: 2.7, 4.69)], no formal education [(AOR = 0.5, 95% CI: 0.37, 0.70)], primary education[(AOR = 0.4, 95%CI: 0.28, 0.53)], and secondary education [(AOR = 0.3, 95% CI: 0.24, 0.48)], middle [(AOR: 1.3, 95% CI: 1.2, 1.52)], rich wealth status [(AOR: 1.4, 95% CI: 1.3, 1.68)], female sex children [(AOR: 1.2, 95% CI: 1.09, 1.42)], and two or fewer ideal number of children [(AOR = 0.2, 95% CI: 0.25, 0.32)] were found to be significant predictors of SBI. CONCLUSION: Overall, SBI was high and significantly clustered across the region of Ethiopia. Age, religion, education, wealth status, the sex of the indexed child, and the ideal number of children were found to be significantly associated with short birth intervals. Hence, the government should design a health promotion strategy and public health awareness in the identified hotspot areas of SBI and should scale up family planning and the wealth status of reproductive-age women.

Health professionals' routine practice documentation and its associated factors in a resource-limited setting: a cross-sectional study.

OBJECTIVES: Documenting routine practice is significant for better diagnosis, treatment, continuity of care and medicolegal issues. However, health professionals' routine practice documentation is poorly practised. Therefore, this study aimed to assess health professionals' routine practice documentation and associated factors in a resource-limited setting. METHODS: An institution-based cross-sectional study design was used from 24 March up to 19 April 2022. Stratified random sampling and a pretested self-administered questionnaire were used among 423 samples. Epi Info V.7.1 and STATA V.15 software were used for data entry and analysis, respectively. Descriptive statistics and a logistic regression model were employed to describe the study subjects and to measure the strength of association between dependent and independent variables, respectively. A variable with a p value of <0.2 in bivariate logistic regression was considered for multivariable logistic regression. In multivariable logistic regression, ORs with 95% CIs and a p value of <0.05 were considered to determine the strength of association between dependent and independent variables. RESULTS: Health professionals' documentation practice was 51.1% (95% CI: 48.64 to 53.1). Lack of motivation (adjusted OR (AOR): 0.41, 95% CI: 0.22 to 0.76), good knowledge (AOR: 1.35, 95% CI: 0.72 to 2.97), taking training (AOR: 4.18, 95% CI: 2.99 to 8.28), using electronic systems (AOR: 2.19, 95% CI: 1.36 to 3.28), availability of standard documentation tools (AOR: 2.45, 95% CI: 1.35 to 4.43) were statistically associated factors. CONCLUSIONS: Health professionals' documentation practice is good. Lack of motivation, good knowledge, taking training, using electronic systems and the availability of documentation tools were significant factors. Stakeholders should provide additional training, and encourage professionals to use an electronic system for documentation practices.

Spatial distribution of vitamin A rich foods intake and associated factors among children aged 6-23 months in Ethiopia: spatial and multilevel analysis of 2019 Ethiopian mini demographic and health survey.

BACKGROUND: Inadequate micronutrients in the diet and vitamin A deficiency are worldwide public health problems. In developing regions, many preschool children are undernourished, become blind every year and died before the age of 23 months. This study was aimed to explore the spatial distribution of vitamin A rich foods intake among children aged 6-23 months and identify associated factors in Ethiopia. METHODS: Ethiopian Mini Demographic and Health Survey 2019 dataset with a total 1407 children aged 6-23 months was used. Data management and processing were done using STATA version 15 software and Microsoft Office Excel. ArcMap version 10.7 software was used for mapping and spatial visualization of the distribution. Spatial scan statistics was performed using SaTScan version 9.5 software for Bernoulli-based model. Multilevel mixed effect logistic regression model was employed to identify associated factors. RESULTS: Overall, 38.99% (95% CI: 36.46-41.62) of children aged 6- 23 months took vitamin A rich foods. Poor intake of vitamin A rich foods was significantly clustered Dire Dawa city, Somali and Harari regions of Ethiopia. Children aged 6-23 months lived in the primary cluster were 70% (RR = 1.70, P-value < 0.001) more likely to intake vitamin A rich foods than children lived outside the window. In the multilevel mixed effect logistic regression analysis, Primary educational status (AOR:1.42, 95% CI: 1.05, 1.93) and higher educational status (AOR:3.0, 95% CI: 1.59, 5.65) of mother, Dire Dawa (AOR:0.49, 95% CI: 0.22, 1.12) city, Afar (AOR: 0.16, 95% CI: 0.07, 0.36), Amhara (AOR: 0.37, 95% CI: 0.19, 0.71) and Somali (AOR: 0.02, 95% CI: 0.003, 0.08) regions of Ethiopia, children aged 13-23 months (AOR: 1.80, 95% CI: 1.28, 2.36), Mothers' exposure to media (AOR: 1.41, 95% CI: 1.04, 1.92) were statistically significant factors for vitamin A rich foods intake among children aged 6-23 months. CONCLUSIONS: Only 4 out of ten children took vitamin A rich foods which is too low compared to the national target and significantly clustered in Ethiopia. Mother's educational status, Region, Child age and Mother's media exposure are significant factors vitamin A rich foods intake. Stakeholders should strengthen mothers' education status, creating awareness for mothers on child feeding and using locally available natural resource to produce vitamin A rich foods.

Digital health literacy to share COVID-19 related information and associated factors among healthcare providers worked at COVID-19 treatment centers in Amhara region, Ethiopia: A cross-sectional survey.

Background: Coronavirus (CoV) is a novel respiratory virus that can cause severe acute respiratory syndrome (SARS). It affects millions of people in the world and thousands of people in Ethiopia. In responding to this, digital health technologies help to reduce COVID-19 outbreaks by sharing accurate and timely COVID-19 related information. Additionally, digital solutions are used for remote consulting during the pandemic, in creating COVID-19 related awareness, for distribution of the vaccine, and so on. Therefore, this study aimed to assess digital health literacy to share COVID-19 related information and associated factors among healthcare providers who worked at COVID-19 treatment centers in the Amhara region, Northwest Ethiopia. Method: An institutional-based cross-sectional survey was conducted from April 4 to May 4, 2021. The study included 476 healthcare providers who worked at COVID-19 treatment centers in the Amhara region. A pretested, structured self-administered questionnaire was used to collect data. EpiData 4.6 and SPSS version 26 were used for data entry and analysis respectively. Bi-variable and Multivariable logistic regression analysis was used to identify factors associated with the dependent variable. A P-value of less than 0.05 was used to declare statistical significance. Result: A total of 456 respondents were participated in the study, with 95.8% response rate. Digital health literacy to share COVID-19 related information found to be 50.4% (95% CI: 46-55). Educational status [AOR = 4.37, 95% CI(2.08-9.17)], training [AOR = 3.00, 95% CI (1.80-5.00)], attitude [AOR = 1.99, 95% CI(1.18-3.36)], perceived usefulness [AOR = 2.01, 95% CI(1.22-3.32)], perceived ease of use [AOR = 2.00, 95% CI(1.25-3.21)] and smartphone access [AOR = 5.21, 95% CI(2.34-9.62)] were significantly associated with digital health literacy to sharing of COVID-19 related information at P-value less than 0.05. Conclusion: This finding indicated that approximately half of the respondents had digital health literacy to share COVID-19 related information which was inadequate. Improving respondents' educational status, computer training, smartphone access, perceived usefulness, perceived ease of use, and attitude was necessary to measure digital health literacy to sharing of COVID-19 related information.

Information seeking about COVID-19 and associated factors among chronic patients in Bahir Dar city public hospitals, Northwest Ethiopia: a cross-sectional study.

BACKGROUND: The health impacts of COVID-19 are not evenly distributed in societies. Chronic patients are highly affected and develop dangerous symptoms of COVID-19. Understanding their information seeking about COVID-19 may help to improve the effectiveness of public health strategies in the future, the adoption of safety measures, and minimize the spread of the pandemic. However, there is little evidence on information seeking specifically on COVID-19 in this study setting. Therefore, this study aimed to assess information seeking about COVID-19 and associated factors among chronic patients. METHOD: An institutional-based cross-sectional study supplemented with qualitative data was conducted at Bahir Dar city public hospitals in Northwest Ethiopia from April 8 to June 15, 2021. A total of 423 chronic patients were selected using systematic random sampling techniques with an interval of 5. Bi-variable and multivariable logistic regression analysis was fitted to identify factors associated with information seeking about COVID-19. A p-value < 0.05 was used to declare statistical significance. Qualitative data were analyzed using a thematic approach. Finally, it was triangulated with quantitative findings. RESULT: The proportion of information seeking about COVID-19 among chronic patients was 44.0% (95% CI = 39.0, 49.0). Being living in urban [AOR = 4.4, 95% CI (2.01, 9.58)], having high perceived susceptibility to COVID-19 [AOR = 3.4, 95%CI (1.98, 5.70)], having high perceived severity to COVID-19 [AOR = 1.7, 95%CI (1.04, 2.91)], having high self-efficacy to COVID-19 [AOR = 4.3, 95%CI (2.52, 7.34)], and having adequate health literacy [AOR = 1.8, 95%CI (1.10, 3.03)] were significant factors associated with information-seeking about COVID-19. CONCLUSION: The overall proportion of information seeking about COVID-19 among chronic patients was low. Thus, health promotion programs should emphasize the chronic patients living in a rural area; enhance perceived risk and severity of COVID-19, enhancing self-efficacy and health literacy interventions to improve information seeking.

Healthcare providers' readiness for electronic health record adoption: a cross-sectional study during pre-implementation phase.

BACKGROUND: The adoption of an electronic health record (EHR) in the healthcare system has the potential to make healthcare service delivery effective and efficient by providing accurate, up-to-date, and complete information. Despite its great importance, the adoptions of EHR in low-income country settings, like Ethiopia, were lagging and increasingly failed. Assessing the readiness of stakeholders before the actual adoption of EHR is considered the prominent solution to tackle the problem. However, little is known about healthcare providers' EHR readiness in this study setting. Accordingly, this research was conducted aiming at examining healthcare providers' readiness for EHR adoption and associated factors in southwestern Ethiopia. METHODS: An institutional-based cross-sectional study was conducted from September 1 to October 30, 2021. A total of 423 healthcare providers working in public hospitals were selected using a simple random sampling technique. Multivariable logistic regression was fitted to identify determinant factors of overall healthcare providers' readiness after the other covariates were controlled. RESULT: In this study, the overall good readiness level of EHR adoption was 52.8% (n = 204) [95% CI of 47.9% to 56.6%]. Age, computer literacy, computer access at health facilities, attitude towards EHRs, awareness about EHRs, perceived benefit, and perceived technology self-efficacy were significantly associated with the overall health care providers' readiness for the adoption of EHR using a cut point of P-value less than 0.05. CONCLUSION: Around half of the respondents had a good level of overall healthcare providers' readiness for the adoption of EHR which was considered inadequate. This finding implied that a huge effort is required to improve readiness before the actual implementation of EHRs. The finding implied that younger-aged groups were more ready for such technology which in turn implied; the older one needs more concern. Enhancing computer literacy, confidence building to raise self-efficacy of such technology, addressing the issue of computer availability at health facilities, building a positive attitude, awareness campaign of EHR, and recognizing the usefulness of such systems were the necessary measures to improve EHR readiness in this setting. Additionally, further studies are recommended to encompass all types of EHR readiness such as organizational readiness, technology readiness, societal readiness, and so on. Additionally, exploring the healthcare provider opinion with qualitative study and extending the proposed study to other implementation settings are recommended to be addressed by future works.