Healthcare professionals' satisfaction toward the use of district health information system and its associated factors in southwest Ethiopia: using the information system success model

BackgroundEthiopia has the potential to use the district health information system, which is a building block of the health system. Thus, it needs to assess the performance level of the system by identifying the satisfaction of end users. There is little evidence about users' satisfaction with using this system. As a result, this study was conducted to fill this gap by evaluating user satisfaction and associated factors of district health information system among healthcare providers in Ethiopia, using the information system success model.MethodsAn institutional-based cross-sectional study was conducted from November to December 2022 in the Oromia region of southwest Ethiopia. A total of 391 health professionals participated in the study. The study participants were selected using a census. Using a self-administered questionnaire, data were collected. Measurement and structural equation modeling analyses were used to evaluate reliability, the validity of model fit, and to test the relationship between the constructs, respectively, using analysis of moment structure (AMOS) V 26.ResultsSystem quality had a positive direct effect on the respondent's system use (β = 0.18, P-value < 0.001), and satisfaction (β = 0.44, P-value < 0.001). Service quality had also a direct effect on the respondent's system use (β = 0.37, P-value < 0.01), and satisfaction with using the district health information system (β = 0.36, P-value < 0.01). Similarly, system use had also a direct effect on the respondent's satisfaction (β = 0.53, P-value < 0.05). Moreover, computer literacy had a direct effect on the respondent's system use (β = 0.63, P-value < 0.05), and satisfaction (β = 0.51, P-value < 0.01).ConcussionsThe overall user satisfaction with using the district health information system in Ethiopia was low. System quality, service quality, and computer literacy had a direct positive effect on system use and user satisfaction. In addition, system use and information quality had a direct positive effect on healthcare professionals' satisfaction with using the district health information system. The most important factor for enhancing system use and user satisfaction was computer literacy. Accordingly, for the specific user training required for the success of the district health information system in Ethiopia, the manager should offer additional basic computer courses for better use of the system

Microbiome dataset of spontaneously fermented Ethiopian honey wine, Tej.

This dataset contains raw and analyzed microbial data for the samples of spontaneously fermented Ethiopian honey wine, Tej, collected from three locations of Ethiopia. It was generated using culture independent amplicon sequencing technique. To gain a better understanding of microbial community variance and similarity across Tej samples from the same and different locations, the raw sequenced data obtained from the Illumina Miseq sequencer was subjected to a bioinformatics analysis. Lower diversity and richness of both bacterial and fungal communities were observed for all of the Tej samples. Besides, samples collected from Debre Markos area showed a significant discriminating tax for both bacterial and fungal communities. In nutshell, this amplicon sequencing dataset provides a useful collection of data for modernizing this spontaneous fermentation into a directed inoculated fermentation. Detail discussion on microbiome of Tej samples is given in [1]

Investigation on Reinforcement Effects of Nanocellulose on the Mechanical Properties, Water Absorption Capacity, Biodegradability, Optical Properties, and Thermal Stability of a Polyvinyl Alcohol Nanocomposite Film

This paper presents the reinforcement of nanocellulose (NC) in polyvinyl alcohol (PVA) to examine the effect of the amount of reinforcement on the properties of PVA. The nanocellulose was successfully extracted by sulfuric acid hydrolysis method and ultrasonication, and successively reinforced with polyvinyl alcohol by the solvent-casting method. After incorporating nanocellulose into the PVA matrix, the effect of nanocellulose on the tensile strength, elongation at break, water absorption capacity, transmittance, thermal stability, and biodegradability of PVA was investigated. The tensile strength increased from 24:5±0:53 MPa to 35:5±0:55 MPa and 40:6±0:73 MPa with the addition of 2%NC and 5%NC, respectively. The elongation at break increased from 40 ± 0:53% to 45:7±0:53% with 2%NC, and after the reinforcement of 7%NC, it decreased to 32:2 ± 0:75%. The water absorption capacity result reveals that neat PVA absorbs the highest amount of water which is 84:6±0:56% and is reduced to 73 ± 0:78% by adding 2%NC. By increasing the nanocellulose loading to 7%, the water intake capacity was reduced to 61 ± 0:59% which illustrates the water intake was reduced linearly with the increment of NC. The ultraviolet-visible (UV-Vis) result implies that the transmittance of neat PVA and PVA-2%NC composite film was 85.4% and 78.2% at 600 nm, respectively, which indicates the decrement in transmittance. The thermogravimetry analysis (TGA) reveals that the thermal stability of polyvinyl alcohol after incorporating nanocellulose particles was reduced. The weight loss of neat PVA is 70:7±1:7 % after 90 days while the weight loss of the PVA composite films reinforced with 1%, 3%, 5%, 7%, and 9% was 65 ± 1:85%, 57 ± 1:57%, 55:6±0:64%, 52 ± 1:73%, and 53:1±1:72%, respectively. The scanning electron microscopy micrograph for the PVA-6%NC nanocomposite film reveals a dispersion of nanocellulose in a matri

Cervical cancer screening utilization among healthcare professionals in Ethiopia: systematic review and meta-analysis

BackgroundCancer of the cervix is the second most common cancer among women worldwide, with about over 660 000 new cases and approximately ninety-four percent of the 350 000 cervical cancer-related death happened in low- and middle-income countries. Effective screening initiatives are particularly crucial in preventing cervical cancer in women. Therefore, the purpose of this systematic literature review was to investigate the pooled prevalence of Ethiopian female healthcare professionals' cervical cancer screening utilization.MethodsPublished articles were searched from different major international databases (PubMed, Cochrane Library, Scopus, Web of Science, Since Direct, Google Scholar). Direct Google searches were used for additional sources mainly for gray and preprint studies. This review included studies that reported either the use of cervical cancer screening or cervical cancer screening predictors in Ethiopia. All published and unpublished studies through May/2024 and reported in the English language were retrieved to assess eligibility for inclusion in this review. The Newcastle-Ottawa Scale quality assessment tool was used to assess the quality of the included studies and Egger's test was used to assess the publication bias.ResultsIn order to calculate the pooled prevalence of cervical cancer screening, 2,919 female healthcare professionals participated in the review. Articles were published from 2015 to 2024. The pooled Utilization of cervical cancer screening in Ethiopia, as determined by a meta-analysis of ten articles was 13.59% (95% CI: 7.53, 19.65).Conclusion and recommendationThe estimated/pooled cervical cancer screening utilization was found to be lower than the World Health Organization recommendations as the estimator revealed in the meta-analysis. The low utilization of Cervical Cancer (CCa)screening practice despite they are healthcare professionals is a significant concern that can impact the broader efforts to combat cervical cancer. Based on the this reviews the authors recommend regular monitoring and evaluation of the CCa screening habits of healthcare professionals and the effectiveness of implemented interventions. It is necessary to explore the factors that enable or hinder CCa screening and address the issue through qualitative or mixed-method studies

Framework to Adopt Cloud Computing for Medical Image Archiving and Sharing

Today’s best practices in medicine rely heavily on the use of diagnostic images and reports, throughout the hospital and in nearly every part of the healthcare enterprise. Since patients are nomadic in today’s healthcare environment there is a need to distribute and retrieve images across different healthcare providers. This often requires the interaction of multiple heterogeneous platforms. Multi-site implementations therefore require advanced integration capabilities and excellent IT skills. In this context, outsourcing of computation and storage resources using cloud infrastructure has become a potential alternative. Recently there has been an increase in the number of organizations adopting and implementing Picture Archiving and Communication Systems using cloud computing model. The research paper discusses the advantages of cloud computing for healthcare and specifically to medical imaging, the limitations of current IT utilization in healthcare organizations. It also discusses standard, legal and compliance issues for healthcare data. By doing so, this research set out to determine how a PACS can be implemented using cloud computing architectures and implementation tools, and developing a framework that helps to provide a complete and timely access to critical imaging/diagnostic information at the point of care, regardless of the source, age or location of the information in an cloud environment. In addition to the general framework to adopt cloud services, a design framework is developed in order to provide medical image archiving and sharing solution as a service. A rigorous analysis of the latest research on Cloud Computing as an alternative to IT provision, management and security for medical image archive and sharing is done. It also took into account the best practices for Cloud Computing usage within different hospitals and imaging centers, by interviewing with selected radiologists, physicians and healthcare IT professionals. The research finding shows that Cloud Computing is a potential alternative the framework is useful to healthcare organizations for medical image archiving and sharing. The paper finally recommends further research directions

Using best performance machine learning algorithm to predict child death before celebrating their fifth birthday

Introduction: Child morbidity and mortality in resource-limited settings is a major public health problem. The previous studies were mainly concerned with determining the prevalence of child deaths and identifying associated factors. Extracting knowledge and discovering insights from hidden patterns in child data through supervised machine learning algorithms is limited. Therefore, this study aimed to predict the under-five death of children using a best performance-supervised machine learning algorithm. Methods: A total of 1813 samples were used from the 2019 Ethiopian Demographic and Health Survey dataset. 70% and 30% of total instances were used for training the model and measuring the performance of each algorithm with 10-fold cross-validation techniques respectively. Five supervised machine learning algorithms were considered for model building and comparison. All the included algorithms were evaluated using confusion matrix elements. Information gain value was used to select important attributes to predict child deaths. The If/then logical association was used to generate rules based on relationships among attributes using Weka version 3.8.6 software. Results: J48 is the second-best performance algorithm next to the random forest to predict child death, with 77.8% and 93.9% accuracy, respectively. Late initiation of breastfeeding, mothers with no formal education, short birth intervals, poor wealth status of the mother, and unexposed to media were the top five important attributes to predict child deaths. A total of six associated rules were generated that could determine the magnitude of child deaths. Of these, if children were rural residents, had a short birth interval, and if born as multiples (twins), then the probability of child death was 83.6%. Conclusions: Five machine learning algorithms were included to predict child deaths and generate rules. Hence, the random forest algorithm was the best algorithm to predict child deaths. However, the study was limited since important attributes were not included in the data source, and irrelevant values were found. So, researchers are encouraged to use machine learning algorithms for future studies including important attributes that could predict child death. The current findings would be useful for stakeholders’ preparedness, and taking proactive childcare interventions. Encouraging women in education, media access, and economic development programs are essential interventions for child death reduction

Framework to Adopt Cloud Computing for Medical Image Archiving and Sharing

Today’s best practices in medicine rely heavily on the use of diagnostic images and reports, throughout the hospital and in nearly every part of the healthcare enterprise. Since patients are nomadic in today’s healthcare environment there is a need to distribute and retrieve images across different healthcare providers. This often requires the interaction of multiple heterogeneous platforms. Multi-site implementations therefore require advanced integration capabilities and excellent IT skills. In this context, outsourcing of computation and storage resources using cloud infrastructure has become a potential alternative. Recently there has been an increase in the number of organizations adopting and implementing Picture Archiving and Communication Systems using cloud computing model. The research paper discusses the advantages of cloud computing for healthcare and specifically to medical imaging, the limitations of current IT utilization in healthcare organizations. It also discusses standard, legal and compliance issues for healthcare data. By doing so, this research set out to determine how a PACS can be implemented using cloud computing architectures and implementation tools, and developing a framework that helps to provide a complete and timely access to critical imaging/diagnostic information at the point of care, regardless of the source, age or location of the information in an cloud environment. In addition to the general framework to adopt cloud services, a design framework is developed in order to provide medical image archiving and sharing solution as a service. A rigorous analysis of the latest research on Cloud Computing as an alternative to IT provision, management and security for medical image archive and sharing is done. It also took into account the best practices for Cloud Computing usage within different hospitals and imaging centers, by interviewing with selected radiologists, physicians and healthcare IT professionals. The research finding shows that Cloud Computing is a potential alternative the framework is useful to healthcare organizations for medical image archiving and sharing. The paper finally recommends further research directions

Women’s health service access and associated factors in Ethiopia: application of geographical information system and multilevel analysis

Objectives Women’s access to healthcare services is challenged by various factors. This study aimed to assess women’s health service access and identify associated factors.Methods A cross-sectional study design with a two-stage stratified sampling technique, and 12 945 women from the 2016 Ethiopia Demographic and Health Survey dataset were used. The spatial hotspot analysis and purely Bernoulli-based model scan statistics were used to highlight hot and cold spot areas, and to detect significant local clusters of women’s health service access. A multilevel logistic regression analysis was used to assess factors that affect women’s access to health services. A variable with a p<o.o5 was considered as a significant factor.Results Overall, 29.8%% of women had health services access. 70.2% of women had problems with health services access such as: not wanting to go alone (42%), distance to health facilities (51%), getting the money needed for treatment (55%) and getting permission to go for medical care (32.3%). The spatial distribution of health service access in Ethiopia was clustered, and low health service access was observed in most areas of the country. Women who lived in primary, secondary and tertiary clusters were 96%, 39% and 72% more likely to access health services. Educational status, rich wealth status, media exposure and rural residence were statistically significant factors.Conclusions In Ethiopia, women have problems with health services access. The spatial distribution of health services access was non-random, and hotspot areas of women’s health service access were visualised in parts of Benishangul Gumez, Amhara, Afar, DireDawa, Harari, and Somali regions. Creating job opportunities, public health promotion regarding maternal health service utilisation and constructing nearby health facilities are required for better healthcare service access for women