Knowledge, attitudes and associated factors to use district health information system among healthcare providers in Illu Aba Bora zone, South West of Ethiopia.

BACKGROUND: Sound and reliable health information is needed to promote culture of evidence based decision making. The aim of this study was to assess knowledge and attitudes of healthcare providers to use District health information system among public health facilities in South-West Ethiopia. METHOD: Cross sectional quantitative study was conducted. A total of 264 participants were approached. Descriptive and analytical statistics was done. RESULT: Overall 130 (49.2%) of respondents had good knowledge to use DHIS (95% CI: [43, 55.3]). 149 (56.4%) of respondents had favourable attitudes (95% CI: [53.2, 59.8]). Sufficient skills [AOR = 2.20, 95% CI: (1.16, 4.19)], older age [AOR = 1.92, 95% CI: (1.03, 3.59)] , resources [AOR = 2.56, 95% CI: (1.35, 4.86)], staffing [AOR = 2.85, 95% CI: (1.49, 5.48)] and high experiences [AOR = 4.66, 95% CI: (1.94, 5.78)] were variables associated with knowledge. Being trained [AOR = 3.59, 95% CI: (2.48, 5.42)], provision of feedback [AOR = 4.08, 95% CI: (1.87, 8.91)], motivation [AOR = 2.87, 95% CI: (1.36, 6.06)] and health need [AOR = 2.32, 95% CI: (1.10, 4.92)] were variables associated with attitudes. CONCLUSION: Thus, Knowledge and attitudes of healthcare providers to use DHIS working in public health facilities in this setting is relatively low. The results highlight the need to improve knowledge and attitudes to use DHIS among healthcare providers focusing on the identified gaps.

Current and Future Needs for Human Resources for Ethiopia's National Health Information System: Survey and Forecasting Study.

BACKGROUND: Strengthening the national health information system is one of Ethiopia's priority transformation agendas. A well-trained and competent workforce is the essential ingredient to a strong health information system. However, this workforce has neither been quantified nor characterized well, and there is no roadmap of required human resources to enhance the national health information system. OBJECTIVE: We aimed to determine the current state of the health information system workforce and to forecast the human resources needed for the health information system by 2030. METHODS: We conducted a survey to estimate the current number of individuals employed in the health information system unit and the turnover rate. Document review and key-informant interviews were used to collect current human resources and available health information system position data from 110 institutions, including the Ministry of Health, federal agencies, regional health bureaus, zonal health departments, district health offices, and health facilities. The Delphi technique was used to forecast human resources required for the health information system in the next ten years: 3 rounds of workshops with experts from the Ministry of Health, universities, agencies, and regional health bureaus were held. In the first expert meeting, we set criteria, which was followed by expert suggestions and feedback. RESULTS: As of April 2020, there were 10,344 health information system professionals working in the governmental health system. Nearly 95% (20/21) of district health offices and 86.7% (26/30) of health centers reported that the current number of health information system positions was inadequate. In the period from June 2015 to June 2019, health information technicians had high turnover (48/244, 19.7%) at all levels of the health system. In the next ten years, we estimate that 50,656 health information system professionals will be needed to effectively implement the Ethiopia's national health information system. CONCLUSIONS: Current health information system-related staffing levels were found to be inadequate. To meet the estimated need of 50,656 multidisciplinary health information system professionals by 2030, the Ministry of Health and regional health bureaus, in collaboration with partners and academic institutions, need to work on retaining existing and training additional health information system professionals.

Status of Compassionate, Respectful, and Caring Health Service Delivery: Scoping Review.

BACKGROUND: A compassionate, respectful, and caring (CRC) health professional is very important for human-centered care, serving clients ethically and with respect, adhering to the professional oath, and serving as a model for young professionals. As countries try to achieve universal health coverage (UHC), quality delivery of health services is crucial. CRC health care is an initiative around the need to provide quality care services to clients and patients. However, there is an evidence gap on the status of CRC health care service delivery. OBJECTIVE: This scoping review aimed to map global evidence on the status of CRC health service delivery practice. METHODS: An exhaustive literature review and Delphi technique were used to answer the 2 research questions: "What is the current status of CRC health care practices among health workers?" and "Is it possible for health professionals, health managers, administrators, and policy makers to incorporate it into their activity while designing strategies that could improve the humanistic and holistic approach to health care provision?" The studies were searched from the year 2014 to September 2020 using electronic databases such as MEDLINE (PubMed), Cochrane Library, Web of Science, Hinari, and the World Health Organization (WHO) library. Additionally, grey literature such as Google, Google Scholar, and WorldWideScience were scrutinized. Studies that applied any study design and data collection and analysis methods related to CRC care were included. Two authors extracted the data and compared the results. Discrepancies were resolved by discussion, or the third reviewer made the decision. Findings from the existing literature were presented using thematic analysis. RESULTS: A total of 1193 potentially relevant studies were generated from the initial search, and 20 studies were included in the final review. From this review, we identified 5 thematic areas: the status of CRC implementation, facilitators for CRC health care service delivery, barriers to CRC health care delivery, disrespectful and abusive care encountered by patients, and perspectives on CRC. The findings of this review indicated that improving the mechanisms for monitoring health facilities, improving accountability, and becoming aware of the consequences of maltreatment within facilities are critical steps to improving health care delivery practices. CONCLUSIONS: This scoping review identified that there is limited CRC service provision. Lack of training, patient flow volume, and bed shortages were found to be the main contributors of CRC health care delivery. Therefore, the health care system should consider the components of CRC in health care delivery during in-service training, pre-service training, monitoring and evaluation, community engagement, workload division, and performance appraisal.

Strengthening the national health information system through a capacity-building and mentorship partnership (CBMP) programme: a health system and university partnership initiative in Ethiopia.

BACKGROUND: A strong health information system (HIS) is one of the essential building blocks for a resilient health system. The Ministry of Health (MOH) of Ethiopia is working on different initiatives to strengthen the national HIS. Among these is the Capacity-Building and Mentorship Partnership (CBMP) Programme in collaboration with public universities in Ethiopia since November 2017. This study aims to evaluate the outcomes and share experiences of the country in working with universities to strengthen the national HIS. METHODS: The study employed a mixed-methods approach that included 247 health organizations (health offices and facilities) of CBMP-implementing woredas (districts) and 23 key informant interviews. The programme focused on capacity-building and mentoring facilities and woreda health offices. The status of HIS was measured using a connected woreda checklist before and after the intervention. The checklist consists of items related to HIS infrastructure, data quality and administrative use. The organizations were classified as emerging, candidate or model based on the score. The findings were triangulated with qualitative data collected through key informant interviews. RESULTS: The results showed that the overall score of the HIS implementation was 46.3 before and 74.2 after implementation of the programme. The proportion of model organizations increased from 1.2% before to 31.8% after the programme implementation. The health system-university partnership has provided an opportunity for higher education institutions to understand the health system and tune their curricula to address real-world challenges. The partnership brought opportunities to conduct and produce local- and national-level evidence to improve the HIS. Weak ownership, poor responsiveness and poor perceptions of the programme were mentioned as major challenges in programme implementation. CONCLUSION: The overall HIS has shown substantial progress in CBMP implementation woredas. A number of facilities became models in a short period of time after the implementation of the programme. The health system-university partnership was found to be a promising approach to improve the national HIS and to share the on-the-ground experiences with the university academicians. However, weak ownership and poor responsiveness to feedback were the major challenges identified as needing more attention in future programme implementation.

Improving data quality and information utilization at Metema Primary Hospital, Amhara national regional state, Northwest Ethiopia 2018: Capstone project.

Quality data for evidence-based decision making become a growing concern globally. Available information needs to be disseminated on time and used for decision making. Therefore, an effective Health Management Information System is essential to make evidence-based decision. This study aimed to measure the change in data quality and information utilization before and after intervention. Facility-based pre-post interventional study design was conducted at Metema hospital from September/2016 to December30/2018. A total of 384 individual medical-records, HMIS registration-books and reports were reviewed. Training, supportive supervision and feedback were intervention packages. About 309 (80.5%) of charts were from outpatient department. Data recording completeness increased from 69.0% to 96.0%, data consistency increased from 84.0% to 99.5% and report timeliness enhanced from 66.0% to 100%. There was a statistically significant difference for data recording completeness between pre and post-intervention results with mean difference of -0.246 (-0.412, -0.081). Also, after the intervention, gap-filling feedback and supportive supervision were given to all departments. In addition, four quality improvement projects were developed at post-intervention phase. The level of data quality and use was improved after the intervention. So, designing and implementing intervention strategies based on the root causes will help to improve data quality and use.

Using health data for decision-making at each level of the health system to achieve universal health coverage in Ethiopia: the case of an immunization programme in a low-resource setting.

BACKGROUND: For evidence-based decision-making, there is a need for quality, timely, relevant and accessible information at each level of the health system. Limited use of local data at each level of the health system is reported to be a main challenge for evidence-based decision-making in low- and middle-income countries. Although evidence is available on the timeliness and quality of local data, we know little about how it is used for decision-making at different levels of the health system. Therefore, this study aimed to assess the level of data use and its effect on data quality and shared accountability at different levels of the health system. METHODS: An implementation science study was conducted using key informants and document reviews between January and September 2017. A total of 21 key informants were selected from community representatives, data producers, data users and decision-makers from the community to the regional level. Reviewed documents include facility reports, district reports, zonal reports and feedback in supervision from the district. Thematic content analysis was performed for the qualitative data. RESULTS: Respondents reported that routine data use for routine decision-making was low. All health facilities and health offices have a performance monitoring team, but these were not always functional. Awareness gaps, lack of motivating incentives, irregularity of supportive supervision, lack of community engagement in health report verification as well as poor technical capacity of health professionals were found to be the major barriers to data use. The study also revealed that there are no institutional or national-level regulations or policies on the accountability mechanisms related to health data. The community-level Health Development Army programme was found to be a strong community engagement approach that can be leveraged for data verification at the source of community data. CONCLUSION: The culture of using routine data for decision-making at the local level was found to be low. Strengthening the capacity of health workers and performance monitoring teams, introducing incentive mechanisms for data use, engaging the community in data verification and introducing accountability mechanisms for health data are essential to improve data use and quality.

Commitment Levels of Health Care Providers in Using the District Health Information System and the Associated Factors for Decision Making in Resource-Limited Settings: Cross-sectional Survey Study.

BACKGROUND: Changing the culture of information use, which is one of the transformation agendas of the Ministry of Health of Ethiopia, cannot become real unless health care providers are committed to using locally collected data for evidence-based decision making. The commitment of health care providers has paramount influence on district health information system 2 (DHIS2) data utilization for decision making. Evidence is limited on health care providers' level of commitment to using DHIS2 data in Ethiopia. Therefore, this study aims to fill this evidence gap. OBJECTIVE: This study aimed to assess the levels of commitment of health care providers and the factors influencing their commitment levels in using DHIS2 data for decision making at public health care facilities in the Ilu Aba Bora zone of the Oromia national regional state, Ethiopia in 2020. METHODS: The cross-sectional quantitative study supplemented by qualitative methods was conducted from February 26, 2020 to April 17, 2020. A total of 264 participants were approached. SPSS version 20 software was used for data entry and analysis. Descriptive and analytical statistics, including bivariable and multivariable analyses, were performed. Thematic analysis was conducted for the qualitative data. RESULTS: Of the 264 respondents, 121 (45.8%, 95% CI 40.0%-52.8%) respondents showed high commitment levels to use DHIS2 data. The variables associated with the level of commitment to use DHIS2 data were found to be provision of feedback for DHIS2 data use (adjusted odds ratio [AOR] 1.85, 95% CI 1.02-3.33), regular supervision and managerial support (AOR 2.84, 95% CI 1.50-5.37), information use culture (AOR 1.92, 95% CI 1.03-3.59), motivation to use DHIS2 data (AOR 1.80, 95% CI 1.00-3.25), health needs (AOR 3.96, 95% CI 2.11-7.41), and competency in DHIS2 tasks (AOR 2.41, 95% CI 1.27-4.55). CONCLUSIONS: In general, less than half of the study participants showed high commitment levels to use DHIS2 data for decision making in health care. Providing regular supportive supervision and feedback and increasing the motivation and competency of the health care providers in performing DHIS2 data tasks will help in promoting their levels of commitment that can result in the cultural transformation of data use for evidence-based decision making in health care.