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Background: Maintaining good quality of healthcare data at various levels is a critical challenge in developing countries. The barriers to healthcare data quality remain largely unexplored in eastern Ethiopia., Objective: This study aimed to assess the barriers to quality of healthcare data in urban public health facilities in the Dire Dawa city administration from 7 April to 7 May 2019., Methods: An institutional-based qualitative exploratory approach was used among 17 purposefully selected key informants. In-depth interviews were inductively coded using the ATLAS.ti 7.5.4 version software. Inductive analysis was used by semantically analyzing the explicit content of the data to determine our themes., Results: Several key themes and subthemes with different barriers, some of which are mutually non-exclusive, were identified. These include: Organizational Barriers: Lack of an adequate health management information system and data clerk staff, poor management commitment, lack of post-training follow-up, work overload, frequent duty rotation, lack of incentives for good performers, lack of targeted feedback, and poor culture of information use. Behavioral/Individual Barriers: Gaps in the skill of managers and health professionals, lack of adequate awareness of each indicator and its definitions, inadequate educational competence, lack of feeling of ownership , poor commitment, lack of daily tallying, and lack of value for data. Technical Barriers: Lack of a standard form, diverse and too many data entry formats, manual data collection, shortage of supplies, failure to repair system break down in a timely manner, interruption in electricity and network, delay in digitizing health information systems, lack of post-training follow-up, and inadequate supervision. External Barriers: Poor collaboration between stakeholders, dependence on the software program of non-governmental organizations, and very hot weather conditions., Conclusion: Diverse and complex barriers to maintenance of data quality were identified. Developing standardized health management information system implementation plans, providing advanced supervisory-level training, supportive supervision, and site-level mentorship may be very effective in identifying and resolving bottleneck data quality issues. Healthcare managers should understand the imperative of data quality and accept responsibility for its improvement and maintenance. Interventions targeted only at supplies will not fully overcome limitations to data quality. Motivation of staff and recognition of best performance can motivate others and can create cooperation among staff., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (© 2024 Tolera, Firdisa, Roba, Motuma, Kitesa and Abaerei.)

Introduction: Tuberculosis treatment interruption increases the risk of poor treatment outcomes and the occurrence of drug resistant Tuberculosis. However, data on the incidence and predictors of tuberculosis treatment interruption are still scarce in Ethiopia, as well as in the study area. Therefore, this study aimed to assess the incidence and predictors of treatment interruption among patients on tuberculosis treatment in Nekemte public healthcare facilities, Oromia region, Western Ethiopia, from July 1, 2017, to June 30, 2021., Methods: A retrospective cohort study design was conducted among 800 patients enrolled in anti-tuberculosis treatment during the study period. Data were collected from patient cards who were enrolled in treatment from July 1, 2017 to June 30, 2021. Epidata version 3.2 was used for data entry, and STATA version 14 was used for analysis. A multivariable Cox regression model with a 95% confidence interval (CI) and adjusted hazard ratio (AHR) was used to identify the significant predictors at a p value < 0.05. Finally, the log likelihood ratio, and a Cox-Snell residual graph was used to check the adequacy of the model., Results: A total of 800 patients were followed for a median time of 2.3 (95% CI: 2.20-2.36) months, and with a maximum follow-up time of 11.7 months. The overall incidence rate of treatment interruption was 27.4 per 1000 (95% CI: 22.8-32.8) person-month observations. Age 18-34 years (AHR = 1.8, 95% CI: 1.02-3.18), male (AHR = 1.63, 95% CI: 1.1-2.42), rural residence (AHR = 3, 95% CI: 1.98-4.64), presence of comorbidity (AHR = 10, 95% CI: 5.47-18.27) and lack of treatment supporters on the treatment follow-up (AHR = 2.82, 95% CI: 1.9-4.41) were found to be significant predictors of treatment interruption., Conclusion: A high incidence rate of interruption was observed among TB patients in public health facilities in Nekemte town. Health facilities should provide supportive care for patients with co-morbidities and consider interventions that target middle-aged patients from rural areas that reduce treatment interruptions., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (© 2023 Getachew, Tolossa, Teklemariam, Ayele and Roba.)

Background: Despite the significant benefits of digital health technologies (ITs), developing countries are lagging behind their developed counterparts in the adoption of electronic medical records (EMRs) in a healthcare setting. EMRs have long been considered essential elements in improving the quality of healthcare. However, the rate of utilization of EMRs among healthcare providers still remains low, particularly in developing countries., Objective: This study aimed at exploring EMR use and its determinants among healthcare providers at public health facilities in Dire Dawa, eastern Ethiopia., Methods: A quantitative cross-sectional study was conducted among 402 health professionals working at public health facilities supplemented with an exploratory qualitative study in Dire Dawa, Ethiopia. Descriptive summary statistics and binary and multivariable logistic regression analysis were used to explore the determinant factors of EMR use, while qualitative data were thematically analyzed., Results: Overall, about a quarter (26.6%) of health professionals were using electronic medical records. A work experience of 6 years or less [adjusted odds ratio (AOR) = 2.23; 95% confidence interval (CI): [1.15-4.31]], a discussion on EMR (AOR = 14.47; 95% CI: [5.58-7.57]), the presence of an EMR manual (AOR = 3.10; 95% CI: [1.28-7.38]), and a positive attitude toward the EMR system (AOR = 11.15; 95% CI: [4.90-25.36]) and service quality (AOR = 8.02; 95% CI: [4.09-15.72]) were independent determinants of EMR use. Poor collaboration among stakeholders and dependence on the software programs of NGOs were the main challenges cited by key informants., Conclusion: The findings of this study indicate that EMR use by health professionals in the study area is very low. Several organizational, technical, and behavioral factors were identified for this low utilization. Therefore, there is a need to leverage EMRs through continuous technical support and commitment to enhance its use, which has the potential to improve health service performance. Developing locally applicable EMR software should be considered., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (© 2022 Tolera, Oljira, Dingeta, Abera and Shore Roba.)