A quality assessment of Health Management Information System (HMIS) data for maternal and child health in Jimma Zone, Ethiopia

Quality of routine health facility data for monitoring maternal, newborn and child health indicators: A desk review of DHIS2 data in Lumbini Province, Nepal

INTRODUCTION

Health-facility data serves as a primary source for monitoring service provision and guiding the attainment of health targets. District Health Information Software (DHIS2) is a free open software predominantly used in low and middle-income countries to manage the facility-based data and monitor program wise service delivery. Evidence suggests the lack of quality in the routine maternal and child health information, however there is no robust analysis to evaluate the extent of its inaccuracy. We aim to bridge this gap by accessing the quality of DHIS2 data reported by health facilities to monitor priority maternal, newborn and child health indicators in Lumbini Province, Nepal.

METHODS

A facility-based descriptive study design involving desk review of Maternal, Neonatal and Child Health (MNCH) data was used. In 2021/22, DHIS2 contained a total of 12873 reports in safe motherhood, 12182 reports in immunization, 12673 reports in nutrition and 12568 reports in IMNCI program in Lumbini Province. Of those, monthly aggregated DHIS2 data were downloaded at one time and included 23 priority maternal and child health related data items. Of these 23 items, nine were chosen to assess consistency over time and identify outliers in reference years. Twelve items were selected to examine consistency between related data, while five items were chosen to assess the external consistency of coverage rates. We reviewed the completeness, timeliness and consistency of these data items and considered the prospects for improvement.

RESULTS

The overall completeness of facility reporting was found within 98% to 100% while timeliness of facility reporting ranged from 94% to 96% in each Maternal, Newborn and Child Health (MNCH) datasets. DHIS2 reported data for all 9 MNCH data items are consistent over time in 4 of 12 districts as all the selected data items are within ±33% difference from the provincial ratio. Of the eight MNCH data items assessed, four districts reported ≥5% monthly values that were moderate outliers in a reference year with no extreme outliers in any districts. Consistency between six-pairs of data items that are expected to show similar patterns are compared and found that three pairs are within ±10% of each other in all 12 districts. Comparison between the coverage rates of selected tracer indicators fall within ±33% of the DHS survey result.

CONCLUSION

Given the WHO data quality guidance and national benchmark, facilities in the Lumbini province well maintained the completeness and timeliness of MNCH datasets. Nevertheless, there is room for improvement in maintaining consistency over time, plausibility and predicted relationship of reported data. Encouraging the promotion of data review through the data management committee, strengthening the system inbuilt data validation mechanism in DHIS2, and promoting routine data quality assessment systems should be greatly encouraged.

Health system barriers to the first dose of measles immunization in Ethiopia: a qualitative study

BACKGROUND

Ethiopia has made considerable progress toward measles elimination. Despite ongoing efforts, the country remains among those with the highest number of children missing their initial dose of measles vaccine, and the disease continues to be a public health emergency. The barriers within the health system that hinder the first dose of measles immunization have not been thoroughly investigated. This study aims to identify these barriers within the Ethiopian context.

METHODS

Qualitative research, using purposive expert sampling to select key informants from health organizations in Addis Ababa, Ethiopia was employed. We conducted in-depth face-to-face interviews using a semi-structured interview guide. A thematic analysis based on the World Health Organization's health systems building blocks framework was conducted.

RESULTS

The study uncovered substantial health system barriers to the uptake of the first dose of the measles vaccine in Ethiopia. These barriers include; restricted availability of immunization services, vaccine stockouts, shortage of cold chain technologies, data inaccuracy resulting from deliberate data falsification or accidental manipulation of data, as well as data incompleteness.

CONCLUSION

Our research highlighted significant health system barriers to MCV1 immunization, contributing to unmet EPI targets in Ethiopia. Our results suggest that to accelerate the country towards measles elimination, there is an urgent need to improve the health systems components such as service delivery, information systems, as well as access to vaccine and cold chain technologies.

District health management and stillbirth recording and reporting: a qualitative study in the Ashanti Region of Ghana

BACKGROUND

Despite global efforts to reduce maternal and neonatal mortality, stillbirths remain a significant public health challenge in many low- and middle-income countries. District health systems, largely seen as the backbone of health systems, are pivotal in addressing the data gaps reported for stillbirths. Available, accurate and complete data is essential for District Health Management Teams (DHMTs) to understand the burden of stillbirths, evaluate interventions and tailor health facility support to address the complex challenges that contribute to stillbirths. This study aims to understand stillbirth recording and reporting in the Ashanti Region of Ghana from the perspective of DHMTs.

METHODS

The study was conducted in the Ashanti Region of Ghana. 15 members of the regional and district health directorates (RHD/DHD) participated in semi-structured interviews. Sampling was purposive, focusing on RHD/DHD members who interact with maternity services or stillbirth data. Thematic analyses were informed by an a priori framework, including theme 1) experiences, perceptions and attitudes; theme 2) stillbirth data use; and theme 3) leadership and support mechanisms, for stillbirth recording and reporting.

RESULTS

Under theme 1, stillbirth definitions varied among respondents, with 20 and 28 weeks commonly used. Fresh and macerated skin appearance was used to classify timing with limited knowledge of antepartum and intrapartum stillbirths. For theme 2, data quality checks, audits, and the district health information management system (DHIMS-2) data entry and review are functions played by the DHD. Midwives were blamed for data quality issues on omissions and misclassifications. Manual entry of data, data transfer from the facility to the DHD, limited knowledge of stillbirth terminology and periodic closure of the DHIMS-2 were seen to proliferate gaps in stillbirth recording and reporting. Under theme 3, perinatal audits were acknowledged as an enabler for stillbirth recording and reporting by the DHD, though audits are mandated for only late-gestational stillbirths (> 28 weeks). Engagement of other sectors, e.g., civil/vital registration and private health facilities, was seen as key in understanding the true population-level burden of stillbirths.

CONCLUSION

Effective district health management ensures that every stillbirth is accurately recorded, reported, and acted upon to drive improvements. A large need exists for capacity building on stillbirth definitions and data use. Recommendations are made, for example, terminology standardization and private sector engagement, aimed at reducing stillbirth rates in high-mortality settings such as Ghana.

District health information system (DHIS2) as integrated antimicrobial resistance surveillance platform: An exploratory qualitative investigation of the one health stakeholders' viewpoints in Ethiopia

INTRODUCTION

There is an unmet need for One Health (OH) surveillance and reporting systems for antimicrobial resistance (AMR) in resource poor settings. District health information system, version 2 (DHIS2), is a globally recognized digital surveillance platform which has not been widely utilized for AMR data yet. Our study aimed to understand the local stakeholders' viewpoints on DHIS2 as OH-AMR surveillance platform in Jimma, Ethiopia which will aid its further context specific establishment.

METHODS

We performed an exploratory qualitative study using semi-structured key informant interviews (KIIs) in Jimma Zone at Southwest Ethiopia. We interviewed 42 OH professionals between November 2020 and February 2021. Following verbatim transcription of the audio recordings of KIIs, we conducted thematic analysis.

RESULTS

We identified five major themes which are important for understanding the trajectory of OH-AMR surveillance in DHIS2 platform. The themes were: (1) Stakeholders' current knowledge on digital surveillance platforms including DHIS2. (2) Stakeholders' perception on digital surveillance platform including DHIS2. (3) Features suggested by stakeholders to be included in the surveillance platform. (4) Comments from stakeholders on system implementation challenges. (5) Stakeholders' perceived role in the process of implementation. Despite several barriers and challenges, most of the participants perceived and suggested DHIS2 as a suitable OH-AMR surveillance platform and were willing to contribute at their current professional roles.

CONCLUSIONS

Our study demonstrates the potential of the DHIS2 as a user friendly and acceptable interoperable platform for OH-AMR surveillance if the technology designers accommodate the stakeholders' concerns. Piloting at local level and using performance appraisal tool in all OH disciplines should be the next step before proceeding to workable format.

Data completeness and consistency in individual medical records of institutional births: retrospective crossectional study from Northwest Ethiopia, 2022

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.

Quality of routine health data at the onset of the COVID-19 pandemic in Ethiopia, Haiti, Laos, Nepal, and South Africa

BACKGROUND

During the COVID-19 pandemic, governments and researchers have used routine health data to estimate potential declines in the delivery and uptake of essential health services. This research relies on the data being high quality and, crucially, on the data quality not changing because of the pandemic. In this paper, we investigated those assumptions and assessed data quality before and during COVID-19.

METHODS

We obtained routine health data from the DHIS2 platforms in Ethiopia, Haiti, Lao People's Democratic Republic, Nepal, and South Africa (KwaZulu-Natal province) for a range of 40 indicators on essential health services and institutional deaths. We extracted data over 24 months (January 2019-December 2020) including pre-pandemic data and the first 9 months of the pandemic. We assessed four dimensions of data quality: reporting completeness, presence of outliers, internal consistency, and external consistency.

RESULTS

We found high reporting completeness across countries and services and few declines in reporting at the onset of the pandemic. Positive outliers represented fewer than 1% of facility-month observations across services. Assessment of internal consistency across vaccine indicators found similar reporting of vaccines in all countries. Comparing cesarean section rates in the HMIS to those from population-representative surveys, we found high external consistency in all countries analyzed.

CONCLUSIONS

While efforts remain to improve the quality of these data, our results show that several indicators in the HMIS can be reliably used to monitor service provision over time in these five countries.

Data quality and associated factors of routine health information system among health centers of West Gojjam Zone, northwest Ethiopia, 2021

Background

Data quality is a multidimensional term that includes accuracy, precision, completeness, timeliness, integrity, and confidentiality. The quality of data generated by a routine health information system (RHIS) is still very poor in low- and middle-income countries. There is a paucity of studies as to what determines data quality in health facilities in the study area. Therefore, the aim of the present study was to assess the magnitude of the quality of routine health information system data and its determinants among health centers.

Methods

A facility-based quantitative study design triangulated by the qualitative method was conducted. A total of 314 health professionals from 32 health centers were selected using a simple random sampling procedure. Data were gathered using a standardized checklist, interviewer-administered questionnaires, and key informant interview guidelines. Descriptive statistics were used to describe variables and binary logistic regression was used to identify factors associated with data quality using STATA version 14. Variables with p-value <0.25 in the bivariate analysis were entered to a multivariable logistic regression analysis. P-values <0.05 at 95% confidence intervals (CI) were taken to be statistically significant. A manual analysis was conducted for the qualitative data collected from purposively selected key informants.

Results

The study found that the overall data quality at the health centers of West Gojjam Zone was 74% (95% CI 68-78). The complexity of the routine health information system format [adjusted odds ratio (AOR) 3.8; 95% CI 1.7-8.5], problem-solving skills for RHIS tasks (AOR 2.8; 95% CI 1.2-6.4), and knowing duties, roles, and responsibilities were significantly associated with data quality (AOR 12; 95% CI 5.6-25.8), and lack of human resources, poor feedback mechanisms, delay in completing data records, lack of data use, and inadequate training on health information systems were barriers affecting data quality.

Conclusions

The level of data quality among public health centers in the Amhara region was lower than expected at the national level.

Measures to assess quality of postnatal care: A scoping review

High quality postnatal care is key for the health and wellbeing of women after childbirth and their newborns. In 2022, the World Health Organization (WHO) published global recommendations on maternal and newborn care for a positive postnatal care experience in a new WHO PNC guideline. Evidence regarding appropriate measures to monitor implementation of postnatal care (PNC) according to the WHO PNC guideline is lacking. This scoping review aims to document the measures used to assess the quality of postnatal care and their validity. The review was conducted according to the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR). Five electronic bibliographic databases were searched together with a grey literature search. Two reviewers independently screened and appraised identified articles. All data on PNC measures were extracted and mapped to the 2022 WHO PNC recommendations according to three categories: i) maternal care, ii) newborn care, iii) health system and health promotion interventions. We identified 62 studies providing measures aligning with the WHO PNC recommendations. For most PNC recommendations there were measures available and the highest number of recommendations were found for breastfeeding and the assessment of the newborn. No measures were found for recommendations related to sedentary behavior, criteria to be assessed before discharge, retention of staff in rural areas and use of digital communication. Measure validity assessment was described in 24 studies (39%), but methods were not standardized. Our review highlights a gap in existing PNC measures for several recommendations in the WHO PNC guideline. Assessment of the validity of PNC measures was limited. Consensus on how the quality of PNC should be measured is needed, involving a selection of priority measures and the development of new measures as appropriate.

Individual- and community-level determinants of maternal health service utilization in southern Ethiopia: A multilevel analysis

BACKGROUND

Maternal health service utilization decreases maternal morbidity and mortality. However, the existing evidence is inadequate to design effective intervention strategies in Ethiopia.

OBJECTIVES

This study aimed to examine the utilization of maternal health service and identify its determinants among women of reproductive age in southern Ethiopia.

DESIGN

A community-based cross-sectional study was conducted from October 21 to November 11, 2022 on a sample of 1140 women selected randomly from the Northern Zone of the Sidama region.

METHODS

Data were collected using the Open Data Kit mobile application and exported to Stata version 15 for analysis. We used a multilevel mixed-effects modified Poisson regression with robust standard error to identify determinants of maternal health service utilization.

RESULTS

Utilization of antenatal care, health facility delivery, and postnatal care was 52.0% (95% confidence interval: 49.0%, 55.0%), 48.5% (95% confidence interval: 45.6%, 51.4%), and 26.0% (95% confidence interval: 23.0%, 29.0%), respectively. Antenatal care use was associated with receiving model family training (adjusted prevalence ratio: 1.19; 95% confidence interval: 1.06, 1.35), knowledge of antenatal care (adjusted prevalence ratio: 1.54; 95% confidence interval: 1.31, 1.81), perceived quality of antenatal care (adjusted prevalence ratio: 1.02; 95% confidence interval: 1.01, 1.03), and having birth preparedness plan (adjusted prevalence ratio: 1.13; 95% confidence interval: 1.02, 1.25). The identified determinants of health facility delivery use were middle wealth rank (adjusted prevalence ratio: 1.35; 95% confidence interval: 1.03, 1.77), perceived quality of health facility delivery (adjusted prevalence ratio: 1.02; 95% confidence interval: 1.01, 1.03), antenatal care (adjusted prevalence ratio: 1.76; 95% confidence interval: 1.36, 2.26), and high community-level women literacy (adjusted prevalence ratio: 1.55; 95% confidence interval: 1.10, 2.19). Postnatal care use was associated with facing health problems during postpartum period (adjusted prevalence ratio: 1.79; 95% confidence interval: 1.18, 2.72), urban residence (adjusted prevalence ratio: 3.52; 95% confidence interval: 2.15, 5.78), knowledge of postnatal care (adjusted prevalence ratio: 1.11; 95% confidence interval: 1.04, 1.19), and low community-level poverty (adjusted prevalence ratio: 0.43; 95% confidence interval: 0.25, 0.73).

CONCLUSION

Maternal health service use was low in the study area and was influenced by individual- and community-level determinants. Any intervention strategies must consider multi-sectorial collaboration to address determinants at different levels. The programs should focus on the provision of model family training, the needs of women who have a poor perception, and knowledge of maternal health service at the individual level.

Development and Testing Requirements for an Integrated Maternal and Child Health Information System in Iran: A Design Thinking Case Study

BACKGROUND

 Management of child health care can be negatively affected by incomplete recording, low data quality, and lack of data integration of health management information systems to support decision making and public health program needs. Given the importance of identifying key determinants of child health via capturing and integrating accurate and high-quality information, we aim to address this gap through the development and testing requirements for an integrated child health information system.

SUBJECTS AND METHODS

 A five-phase design thinking approach including empathizing, defining, ideation, prototyping, and testing was applied. We employed observations and interviews with the health workers at the primary health care network to identify end-users' challenges and needs using tools in human-centered design and focus group discussion. Then, a potential solution to the identified problems was developed as an integrated maternal and child health information system (IMCHIS) prototype and tested using Software Quality Requirements and Evaluation Model (SQuaRE) ISO/IEC 25000.

RESULTS

 IMCHIS was developed as a web-based system with 74 data elements and seven maternal and child health care requirements. The requirements of "child disease" with weight (0.26), "child nutrition" with weight (0.20), and "prenatal care" with weight (0.16) acquired the maximum weight coefficient. In the testing phase, the highest score with the weight coefficient of 0.48 and 0.73 was attributed to efficiency and functionality characteristics, focusing on software capability to fulfill the tasks that meet users' needs.

CONCLUSION

 Implementing a successful child health care system integrates both maternal and child health care information systems to track the effect of maternal conditions on child health and support managing performance and optimizing service delivery. The highest quality score of IMCHIS in efficiency and functionality characteristics confirms that it owns the capability to identify key determinants of child health.

Maternal and child health data quality in health care facilities at the Cape Coast Metropolis, Ghana

Background

The demand for quality maternal and child health (MCH) data is critical for tracking progress towards attainment of the Sustainable Development Goal 3. However, MCH cannot be adequately monitored where health data are inaccurate, incomplete, untimely, or inconsistent. Thus, this study assessed the level of MCH data quality.

Method

A facility-based cross-sectional study design was adopted, including a review of MCH service records. It was a stand-alone study involving 13 healthcare facilities of different levels that provided MCH services in the Cape Coast Metropolis. Data quality was assessed using the dimensions of accuracy, timeliness, completeness, and consistency. Health facilities registers were counted, collated, and compared with data on aggregate monthly forms, and a web-based data collation and reporting system, District Health Information System (DHIS2). The aggregate monthly forms were also compared with data in the DHIS2. Eight MCH variables were selected to assess data accuracy and consistency and two monthly reports were used to assess completeness and timeliness. Percentages and verification factor were estimated in the SPSS version 22 package.

Results

Data accuracy were recorded between the data sources: Registers and Forms, 102.1% (95% CI = 97.5%—106.7%); Registers and DHIS2, 102.4% (95% CI = 94.4%—110.4%); and Forms and DHIS2, 100.1% (95% CI = 96.4%—103.9%). Across the eight MCH variables, data were 93.2% (95% CI = 82.9%—103.5%) complete in Registers, 91.0% (95% CI = 79.5%—102.5%) in the Forms, and 94.9% (95% CI = 89.9%—99.9%) in DHIS2 database. On the average, 87.2% (95% CI = 80.5%—93.9%) of the facilities submitted their Monthly Midwife’s Returns reports on time, and Monthly Vaccination Report was 94% (95% CI = 89.3%—97.3%). The overall average data consistency was 93% (95% CI = 84%—102%).

Conclusion

Given the WHO standard for data quality, the level of MCH data quality in the health care facilities at the Cape Coast Metropolis, available through the DHIS2 is complete, reported on timely manner, consistent, and reflect accurately what exist in facility’s source document. Although there is evidence that data quality is good, there is still room for improvement in the quality of the data.

Data quality and associated factors in the health management information system at health centers in Shashogo district, Hadiya zone, southern Ethiopia, 2021

BACKGROUND

Poor quality routine data contributes to poor decision-making, inefficient resource allocation, loss of confidence in the health system, and may threaten the validity of impact evaluations. For several reasons in most developing countries, the routine health information systems in those countries are described as ineffective. Hence, the aim of this study is to determine the quality of data and associated factors in the routine health management information system in health centers of Shashogo district, Hadiya Zone.

METHODS

A facility-based cross-sectional study was conducted from June 1, 2021, to July 1, 2021, and 300 participants were involved in the study through simple random sampling. The data was collected with a self-administered questionnaire by trained data collectors. After checking its completeness, the data was entered into EPI data version 3.1 and exported to SPSS version 25 for statistical analysis. Finally, variables with p < 0.05 during multivariable analysis were considered significant variables.

RESULT

A total of 300(100%) participant were included in the interview and HMIS data quality was 83% in Shashogo district health centers. The data quality in terms of accuracy, completeness, and timeliness was 79%, 86%, and 84%, respectively. Conducting supportive supervision [AOR 3.5 (1.4, 8.9)], checking accuracy [AOR 1.3 (1.5, 3.5)], filling registrations [AOR 2.7 (1.44, 7.7)], and confidence level [AOR 1.9 (1.55, 3.35)] were all rated positively found to be factors associated with data quality.

CONCLUSION

The overall level of data quality in Shashogo district health centers was found to be below the national expectation level. All dimensions of data quality in the district were below 90% in data accuracy, content completeness, and timeliness of data. Conducting supportive supervision, checking accuracy, filling registrations and confidence level were found to be factors associated with data quality. Hence, all stakeholders should give all necessary support to improve data quality in routine health information systems to truly attain the goal of providing good quality data for the decision-making process by considering the identified factors.

'The false reporter will get a praise and the one who reported truth will be discouraged': a qualitative study on intentional data falsification by frontline maternal and newborn healthcare workers in two regions in Ethiopia

INTRODUCTION

Health Management Information Systems (HMIS) are vital to ensure accountability and for making decisions including for tracking the Sustainable Development Goals. The Ethiopia Health Sector Transformation Plan II includes preventing data falsification as a major strategic initiative and our study aimed to explore the reasons why healthcare providers intentionally falsify maternal and newborn health (MNH) data in two regions of Ethiopia.

METHODS

We conducted a qualitative study in two hospitals, four health centres and their associated health posts in Oromia and Amhara regions. We conducted 45 in-depth interviews with health facility managers, quality improvement (QI) focal persons, health information technicians, MNH care providers, Health Extension Workers and QI mentors. Data were collected in local languages and transcribed in English. During analysis we repeatedly read the transcripts, coded them inductively using NVivo V.12, and categorised the codes into themes.

RESULTS

Participants were hesitant to report personal data falsification but many reported that falsification is common and that they had experienced it in other facilities or had been told about it by other health workers. Falsification was mostly inflating the number of services provided (such as deliveries). Decreasing the number of deaths or reclassifying neonatal death into stillbirths was also reported. An overarching theme was that the health system focuses on, and rewards, the number of services provided over any other metric. This focus led to both system and individual level incentives for falsification and disincentives for accurate reporting.

CONCLUSION

Our finding suggests that to reduce facility level data falsification policy makers might consider disentangling reward and punishments from the performance reports based on the routine HMIS data. Further studies examining the high-level drivers of falsification at regional, national and global levels and effective interventions to address the drivers of data falsification are needed.

Direct financial assistance for improved maternal and child health data: a pilot study supporting the health management information system in Malawi

Background

The health management information system (HMIS) is an integral component of a strong health care system. Despite its importance for decision-making, the quality of HMIS data remains of concern in low- and middle-income countries. To address challenges with the quality of maternal and child health (MCH) data gathered within Malawi’s HMIS, we conducted a pilot study evaluating different support modalities to district-level HMIS offices. We hypothesized that providing regular, direct financial assistance to HMIS offices would enable staff to establish strategies and priorities based on local context, resulting in more accurate, timely, and complete MCH data.

Methods

The pilot intervention was implemented in Mwanza district, while Chikwawa, Neno, and Ntchisi districts served as control sites given support received from other institutions. The intervention consisted of providing direct financial assistance to Mwanza’s HMIS office following the submission of detailed budgets and lists of planned activities. In the control districts, we performed interviews with the HMIS officers to track the HMIS-related activities. We evaluated the intervention by comparing data quality between the post- and pre-intervention periods in the intervention and control districts. Additionally, we conducted interviews with Mwanza’s HMIS office staff to determine the acceptability and appropriateness of the intervention.

Results

Following the 10-month intervention period, we observed improvements in MCH data quality in Mwanza. The availability and completeness of MCH data collected in the registers increased by 22 and 18 percentage points, respectively. The consistency of MCH data between summary reports and electronic HMIS also improved. In contrast, 2/3 control districts noted minimal changes or reductions in data quality after 10 months. The qualitative interviews confirmed that, despite some challenges, the intervention was well received by the participating HMIS office. HMIS staff preferred our strategy to other conventional strategies that fail to give them the independence to make decisions.

Conclusions

This pilot intervention demonstrated an alternative approach to support HMIS offices in their daily efforts to improve data quality. Given the Ministry of Health’s (MoH) interest in strengthening its HMIS, our intervention provides a strategy that the MoH and local and international partners could consider to rapidly improve HMIS data with minimal oversight.

Assessing routine health information system performance during the tenth outbreak of Ebola virus disease (2018-2020) in the Democratic Republic of the Congo: A qualitative study in North Kivu

The Democratic Republic of Congo has implemented reforms to its national routine health information system (RHIS) to improve timeliness, completeness, and use of quality data. However, outbreaks can undermine efforts to strengthen it. We assessed the functioning of the RHIS during the 2018-2020 outbreak of Ebola Virus Disease (EVD) to identify opportunities for future development. We conducted a qualitative study in North Kivu, from March to May 2020. Semi-structured interviews were conducted with 34 key informants purposively selected from among the personnel involved in the production of RHIS data. The topics discussed included RHIS functioning, tools, compilation, validation, quality, sharing, and the use of data. Audio recordings were transcribed verbatim and thematic analysis was used to study the interviewees' lived experience. The RHIS retained its structure, tools, and flow during the outbreak. The need for other types of data to inform the EVD response created other parallel systems to the RHIS. This included data from Ebola treatment centers, vaccination against Ebola, points of entry surveillance, and safe and dignified burial. The informants indicated that the availability of weekly surveillance data had improved, while timeliness and quality of monthly RHIS reporting declined. The compilation of data was late and validation meetings were irregular. The upsurge of patients following the implementation of the free care policy, the departure of healthcare workers for better-paid jobs, and the high prioritization of the outbreak response over routine activities led to RHIS disruptions. Delays in decision-making were one of the consequences of the decline in data timeliness. Adequate allocation of human resources, equitable salary policy, coordination, and integration of the response with local structures are necessary to ensure optimal functioning of the RHIS during an outbreak. Future research should assess the scale of data quality changes during outbreaks.

Exploring data quality and use of the routine health information system in Ethiopia: a mixed-methods study

OBJECTIVE

A routine health information system (RHIS) enables decision making in the healthcare system. We aimed to analyse data quality at the district and regional level and explore factors and perceptions affecting the quality and use of routine data.

DESIGN

This was a mixed-methods study. We used the WHO toolkit for analysing data quality and interviewed staff at the point of data generation and along with the flow of data. Data were analysed using the Performance of Routine Information System Management framework.

SETTING

This study was performed in eight districts in four regions of Ethiopia. The study was nested within a 2-year programme of the Operational Research and Coaching for government Analysts.

PARTICIPANTS

We visited 45 health posts, 1 district hospital, 16 health centres and 8 district offices for analysis of routine RHIS data and interviewed 117 staff members for the qualitative assessment.

OUTCOME MEASURES

We assessed availability of source documents, completeness, timeliness and accuracy of reporting of routine data, and explored data quality and use perceptions.

RESULTS

There was variable quality of both indicator and data element. Data on maternal health and immunisation were of higher quality than data on child nutrition. Issues ranged from simple organisational factors, such as availability of register books, to intricate technical issues, like complexity of indicators and choice of denominators based on population estimates. Respondents showed knowledge of the reporting procedures, but also demonstrated limited skills, lack of supportive supervision and reporting to please the next level. We saw limited examples of the use of data by the staff who were responsible for data reporting.

CONCLUSION

We identified important organisational, technical, behavioural and process factors that need further attention to improve the quality and use of RHIS data in Ethiopia.

Assessment of quality of routine health information system data and associated factors among departments in public health facilities of Harari region, Ethiopia

Background

Despite the improvements in the knowledge and understanding of the role of health information in the global health system, the quality of data generated by a routine health information system is still very poor in low and middle-income countries. There is a paucity of studies as to what determines data quality in health facilities in the study area. Therefore, this study was aimed to assess the quality of routine health information system data and associated factors in public health facilities of Harari region, Ethiopia.

Methods

A cross-sectional study was conducted in all public health facilities in the Harari region of Ethiopia. The department-level data were collected from respective department heads through document reviews, interviews, and observation checklists. Descriptive statistics were used to data quality and multivariate logistic regression was run to identify factors influencing data quality. The level of significance was declared at P value < 0.05.

Result

The study found good quality data in 51.35% (95% CI 44.6–58.1) of the departments in public health facilities in the Harari Region. Departments found in the health centers were 2.5 times more likely to have good quality data as compared to those found in the health posts. The presence of trained staffs able to fill reporting formats (AOR = 2.474; 95% CI 1.124–5.445) and provisions of feedbacks (AOR = 3.083; 95% CI 1.549–6.135) were also significantly associated with data quality.

Conclusion

The level of good data quality in the public health facilities was less than the expected national level. Lack of trained personnel able to fill the reporting format and feedback were the factors that are found to be affecting data quality. Therefore, training should be provided to increase the knowledge and skills of the health workers. Regular supportive supervision and feedback should also be maintained.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12911-021-01651-2.

Outcome evaluation of capacity building and mentorship partnership (CBMP) program on data quality in the public health facilities of Amhara National Regional State, Ethiopia: a quasi-experimental evaluation

Background

Capacity Building and Mentorship Partnership (CBMP) is a flagship program designed by the Ethiopian Ministry of Health in collaboration with six local universities to strengthen the national health information system and facilitate evidence-informed decision making through various initiatives. The program was initiated in 2018. This evaluation was aimed to assess the outcome of CBMP on health data quality in the public health facilities of Amhara National Regional State, Ethiopia.

Methods

A matched comparison group evaluation design with a sequential explanatory mixed-method was used to evaluate the outcome of CBMP on data quality. A total of 23 health facilities from the intervention group and 17 comparison health facilities from a randomly selected district were used for this evaluation. The Organization for Economic Cooperation and Development (OECD) evaluation framework with relevance, effectiveness, and impact dimensions was used to measure the program’s outcome using the judgment parameter. The program’s average treatment effect on data quality was estimated using propensity score matching (PSM).

Results

The overall outcome of CBMP was found to be 90.75 %. The mean data quality in the intervention health facility was 89.06 % [95 %CI: 84.23, 93.88], which has a significant mean difference with the comparison health facilities (66.5 % [95 % CI: 57.9–75]). In addition, the CBMP increases the data quality of pilot facilities by 27.75 % points [95 %CI: 17.94, 37.58] on the nearest neighboring matching. The qualitative data also noted that there was a data quality problem in the health facility and CBMP improved the data quality gap among the intervention health facilities.

Conclusions

The outcome of the CBMP was highly satisfactory. The program effectively increased the data quality in the health facilities. Therefore, the finding of this evaluation can be used by policymakers, program implementers, and funding organizations to scale the program at large to improve the overall health data quality for health outcome improvement.

Using health management information system data: case study and verification of institutional deliveries in Ethiopia

Health management information systems (HMIS) are a crucial source of timely health statistics and have the potential to improve reporting in low-income countries. However, concerns about data quality have hampered their widespread adoption in research and policy decisions. This article presents results from a data verification study undertaken to gain insights into the quality of HMIS data in Ethiopia. We also provide recommendations for working with HMIS data for research and policy translation. We linked the HMIS to the 2016 Emergency Obstetric and Newborn Care Assessment, a national census of all health facilities that provided maternal and newborn health services in Ethiopia. We compared the number of visits for deliveries and caesarean sections (C-sections) reported in the HMIS in 2015 (January–December) to those found in source documents (paper-based labour and delivery and operating theatre registers) in 2425 facilities across Ethiopia. We found that two-thirds of facilities had ‘good’ HMIS reporting for deliveries (defined as reporting within 10% of source documents) and half had ‘very good’ reporting (within 5% of source documents). Results were similar for reporting on C-section deliveries. We found that good reporting was more common in urban areas (OR: 1.30, 95% CI 1.06 to 1.59), public facilities (OR: 2.95, 95% CI 1.38 to 6.29) and in hospitals compared with health centres (OR: 1.71, 95% CI 1.13 to 2.61). Facilities in the Somali and Afar regions had the lowest odds of good reporting compared with Addis Ababa and were more likely to over-report deliveries in the HMIS. Further work remains to address remaining discrepancies in the Ethiopian HMIS. Nonetheless, our findings corroborate previous data verification exercises in Ethiopia and support greater use and uptake of HMIS data for research and policy decisions (particularly, greater use of HMIS data elements (eg, absolute number of services provided each month) rather than coverage indicators). Increased use of these data, combined with feedback mechanisms, is necessary to maintain data quality.

Neglected tropical zoonotic diseases in Tigray region, northern Ethiopia: Spatial distribution and trend analysis of rabies, tuberculosis, schistosomiasis, and visceral leishmaniasis in humans

Neglected tropical zoonotic diseases (NTZDs) continue to affect the health and livelihoods of humans particularly the poor and marginalized populations in developing countries. Mapping the distribution and burden of these diseases will support making an informed decision. A retrospective study was conducted to map the spatial distribution and analyse trend of NTZDs in Tigray region, Northern Ethiopia. A health management information system (HMIS) data between 2012/13 and 2016/17 was obtained from Tigray National Regional State Health Bureau. The Quantum-GIS software was used to map the spatial distribution and burden of selected NTZDs at zonal level. Only four of the NTZDs namely rabies, tuberculosis (TB), schistosomiasis and visceral leishmaniasis (VL) from the records of HMIS data were considered. A high incidence rate (IR) at least for one of the NTZDs was reported in males above 15 years old. In the 5-year period, of the 60,099 reported NTZD cases, 30.3% (18,220), 26.6% (16,005), 23.3% (14,001), 14.4% (8,661), and 5.3% (3,212) were, respectively, schistosomiasis, extra-pulmonary TB, rabies, pulmonary TB, and visceral leishmaniasis. The year-wise analysis showed an irregular trend for the NTZDs where both the decreasing and increasing trends didn't show statistically significant variation. However, the overall regional number of TB cases showed a decreasing trend, where the decrease for extra-pulmonary TB (1.8 cases per 100,000 population) was higher than pulmonary TB (0.5 cases per 100,000 population). Similarly, the annual number of rabies and VL cases showed a decreasing trend. On the other hand, the number of schistosomiasis cases showed an increasing trend (8.2 cases per 100,000 population). The annual average number of TB (171 cases per 100,000 population), schistosomiasis (354 cases per 100,000 population), and VL (63 cases per 100,000 population) cases were much higher in Western zone compared to the rest of the zones. The incidence rate of rabies was higher in Mekelle and Southeastern (100 cases per 100,000 population) and Northwestern (97 cases per 100,000 population) zones. Intervention strategies applied in the region should take into account the zonal distribution and burden of NTZDs.

Uterotonics for prevention of postpartum haemorrhage: EN-BIRTH multi-country validation study

BACKGROUND

Postpartum haemorrhage (PPH) is a leading cause of preventable maternal mortality worldwide. The World Health Organization (WHO) recommends uterotonic administration for every woman after birth to prevent PPH. There are no standardised data collected in large-scale measurement platforms. The Every Newborn Birth Indicators Research Tracking in Hospitals (EN-BIRTH) is an observational study to assess the validity of measurement of maternal and newborn indicators, and this paper reports findings regarding measurement of coverage and quality for uterotonics.

METHODS

The EN-BIRTH study took place in five hospitals in Bangladesh, Nepal and Tanzania, from July 2017 to July 2018. Clinical observers collected tablet-based, time-stamped data. We compared observation data for uterotonics to routine hospital register-records and women's report at exit-interview survey. We analysed the coverage and quality gap for timing and dose of administration. The register design was evaluated against gap analyses and qualitative interview data assessing the barriers and enablers to data recording and use.

RESULTS

Observed uterotonic coverage was high in all five hospitals (> 99%, 95% CI 98.7-99.8%). Survey-report underestimated coverage (79.5 to 91.7%). "Don't know" replies varied (2.1 to 14.4%) and were higher after caesarean (3.7 to 59.3%). Overall, there was low accuracy in survey data for details of uterotonic administration (type and timing). Register-recorded coverage varied in four hospitals capturing uterotonics in a specific column (21.6, 64.5, 97.6, 99.4%). The average coverage measurement gap was 18.1% for register-recorded and 6.0% for survey-reported coverage. Uterotonics were given to 15.9% of women within the "right time" (1 min) and 69.8% within 3 min. Women's report of knowing the purpose of uterotonics after birth ranged from 0.4 to 64.9% between hospitals. Enabling register design and adequate staffing were reported to improve routine recording.

CONCLUSIONS

Routine registers have potential to track uterotonic coverage - register data were highly accurate in two EN-BIRTH hospitals, compared to consistently underestimated coverage by survey-report. Although uterotonic coverage was high, there were gaps in observed quality for timing and dose. Standardisation of register design and implementation could improve data quality and data flow from registers into health management information reporting systems, and requires further assessment.

The use of data in resource limited settings to improve quality of care

Quality improvement is driven by benchmarking between and within institutions over time and the collaborative improvement efforts that stem from these comparisons. Benchmarking requires systematic collection and use of standardized data. Low- and middle-income countries (LMIC) have great potential for improvements in newborn outcomes but serious obstacles to data collection, analysis, and implementation of robust improvement methodologies exist. We review the importance of data collection, internationally recommended neonatal metrics, selected methods of data collection, and reporting. The transformation from data collection to data use is illustrated by several select data system examples from LMIC. Key features include aims and measures important to neonatal team members, co-development with local providers, immediate access to data for review, and multidisciplinary team involvement. The future of neonatal care, use of data, and the trajectory to reach global neonatal improvement targets in resource-limited settings will be dependent on initiatives led by LMIC clinicians and experts.

Data quality of the routine health management information system at the primary healthcare facility and district levels in Tanzania

BACKGROUND

Effective planning for disease prevention and control requires accurate, adequately-analysed, interpreted and communicated data. In recent years, efforts have been put in strengthening health management information systems (HMIS) in Sub-Saharan Africa to improve data accessibility to decision-makers. This study assessed the quality of routine HMIS data at primary healthcare facility (HF) and district levels in Tanzania.

METHODS

This cross-sectional study involved reviews of documents, information systems and databases, and collection of primary data from facility-level registers, tally sheets and monthly summary reports. Thirty-four indicators from Outpatient, Inpatient, Antenatal care, Family Planning, Post-natal care, Labour and Delivery, and Provider-Initiated Testing and Counselling service areas were assessed. Indicator records were tracked and compared across the process of data collection, compilation and submission to the district office. Copies of monthly report forms submitted by facilities to the district were also reviewed. The availability and utilization of HMIS tools were assessed, while completeness and data accuracy levels were quantified for each phase of the reporting system.

RESULTS

A total of 115 HFs (including hospitals, health centres, dispensaries) in 11 districts were involved. Registers (availability rate = 91.1%; interquartile range (IQR) 66.7-100%) and report forms (86.9%; IQR 62.2-100%) were the most utilized tools. There was a limited use of tally-sheets (77.8%; IQR 35.6-100%). Tools availability at the dispensary was 91.1%, health centre 82.2% and hospital 77.8%, and was low in urban districts. The availability rate at the district level was 65% (IQR 48-75%). Wrongly filled or empty cells in registers and poor adherence to the coding procedures were observed. Reports were highly over-represented in comparison to registers' records, with large differences observed at the HF phase of the reporting system. The OPD and IPD areas indicated the highest levels of mismatch between data source and district office. Indicators with large number of clients, multiple variables, disease categorization, or those linked with dispensing medicine performed poorly.

CONCLUSION

There are high variations in the tool utilisation and data accuracy at facility and district levels. The routine HMIS is weak and data at district level inaccurately reflects what is available at the source. These results highlight the need to design tailored and inter-service strategies for improving data quality.

Experiences of managerial accountability in Ethiopia's primary healthcare system: a qualitative study

Background

Despite calls for improved accountability in global health systems, and a set of clear and consistent theoretical accountability frameworks, empirical descriptions of how accountability is experienced and enacted in low- and middle- income country (LMIC) settings is limited. Therefore, we sought to characterize how managers at all levels of Ethiopia’s primary healthcare system experience accountability in their daily practice.

Methods

We conducted in-depth key informant interviews with 41 key stakeholders across 4 regions (Amhara, Oromia, Southern Nations Nationalities and Peoples, and Tigray) in the context of the Primary Healthcare Transformation Initiative (PTI). Consistent with the principles of grounded theory, our team used the constant comparative method to identify emergent themes related to concrete areas that could be targeted to allow an overall culture of accountability to flourish.

Results

Emergent themes were: development of a shared understanding of system-wide accountability, streamlining of managerial reporting lines, strengthening of medico-legal knowledge and systems, and development of mechanisms for bottom-up accountability.

Conclusions

Findings may be valuable to policymakers seeking to create more effective national accountability frameworks; practitioners and development partners seeking to strengthen implementation of evidence-based accountability systems and practices; and researchers aiming to develop meaningful, practical measures of accountability in public health.

Predictors of electronic health management information system for improving the quality of care for women and people with disabilities

The electronic Hospital management Information System (eHMIS) can improve care for vulnerable patients, help collect important disability and maternal health data, and improve the hospital’s overall data management. This study assessed the use of HMIS and factors influencing the usage and behavioral intentions to use the eHMIS at the Comprehensive Community Based Rehabilitation in Tanzania (CCBRT). We investigated both clinical and non-clinical staff (n=69) using tablets and online surveys, with a rate of return of 71.9%. The ICT staff were also interviewed to supplement data from the survey. The survey questionnaire was guided by the updated Information System Success (ISS) model. Most health workers (81.2%) used the eHMIS several times a day to support different decision-making activities. The better educated personnel were more likely to enter data more effectively into eHMIS as compared to their counterparts. Among six predictors, self-efficacy positively influenced self-reported use and user satisfaction of HMIS, while service quality negatively affected self-reported use of eHMIS. The system quality positively influenced health workers to be satisfied with the eHMIS, and user satisfaction positively influenced continued usage intention of the eHMIS. Both user satisfaction and continued usage intention were positively related to individual impact of eHMIS. Individual impact had positive effects on organizational impact of eHMIS. This is a comprehensive study conducted in Tanzania regarding the implementation of eHMIS, and factors influencing post-adoptive use of HMIS to improve quality of care of women and people with disabilities.

Promoting equity in maternal, newborn and child health - how does gender factor in? Perceptions of public servants in the Ethiopian health sector

Background: Advancing gender equality and health equity are concurrent priorities of the Ethiopian health sector. While gender is regarded as an important determinant of health, there is a paucity of literature that considers the interface between how these two priorities are pursued.

Objective: This article explores how government stakeholders understand gender issues (gender barriers and roles) in the promotion of maternal, newborn and child health equity in Ethiopia.

Methods: Adopting an exploratory qualitative case study design, we conducted semi-structured interviews with 17 purposively-selected stakeholders working in leadership positions with the Federal Ministry of Health and Federal Ministry of Women and Children Affairs as part of a larger study regarding the promotion of health equity in maternal, newborn and child health. A post hoc content and thematic sub-analysis was done to explore how participants raised gender issues in conversations about health equity.

Results: Efforts to address gender inequalities were synonymous with the promotion of a women’s health agenda, which was largely oriented towards promoting health service use. Men were predominant decision makers with regards to women’s health and health care seeking in both public and private spheres. Participants reported persisting gender-related barriers to health stemming from traditional gender roles, and noted the increased inclusion of women in the health workforce since the introduction of the Health Extension Program.

Conclusions: The framing of gender as a women’s health issue, advanced through patriarchal structures, does little to elevate the status of women, or promote power differentials that contribute to health inequity. Encouraging leadership roles for women as health decision makers and redressing certain gender-based norms, attitudes, practices and discrimination are possible ways forward in re-orienting gender equality efforts to align with the promotion of health equity.

Effect of data quality improvement intervention on health management information system data accuracy: An interrupted time series analysis

Background

As part of a partnership between the Institute for Healthcare Improvement and the Ethiopian Federal Ministry of Health, woreda-based quality improvement collaboratives took place between November 2016 and December 2017 aiming to accelerate reduction of maternal and neonatal mortality in Lemu Bilbilu, Tanqua Abergele and Duguna Fango woredas. Before starting the collaboratives, assessments found inaccuracies in core measures obtained from Health Management Information System reports.

Methods and results

Building on the quality improvement collaborative design, data quality improvement activities were added and we used the World Health Organization review methodology to drive a verification factor for the core measures of number of pregnant women that received their first antenatal care visit, number of pregnant women that received antenatal care on at least four visits, number of pregnant women tested for syphilis and number of births attended by skilled health personnel. Impact of the data quality improvement was assessed using interrupted time series analysis. We found accurate data across all time periods for Tanqua Abergele. In Lemu Bilbilu and Duguna Fango, data quality improved for all core metrics over time. In Duguna Fango, the verification factor for number of pregnant women that received their first antenatal care visit improved from 0.794 (95%CI 0.753, 0.836; p<0.001) pre-intervention by 0.173 (95%CI 0.128, 0.219; p<0.001) during the collaborative; and the verification factor for number of pregnant women tested for syphilis improved from 0.472 (95%CI 0.390, 0.554; p<0.001) pre-intervention by 0.460 (95%CI 0.369, 0.552; p<0.001) during the collaborative. In Lemu Bilbilu, the verification factor for number of pregnant women receiving a fourth antenatal visit rose from 0.589 (95%CI 0.513, 0.664; p<0.001) at baseline by 0.358 (95%CI 0.258, 0.458; p<0.001) post-intervention; and skilled birth attendance rose from 0.917 (95%CI 0.869, 0.965) at baseline by 0.083 (95%CI 0.030, 0.136; p<0.001) during the collaborative.

Conclusions

A Data quality improvement initiative embedded within woreda clinical improvement collaborative improved accuracy of data used to monitor maternal and newborn health services in Ethiopia.

Health management information system (HMIS) data verification: A case study in four districts in Rwanda

INTRODUCTION

Reliable Health Management and Information System (HMIS) data can be used with minimal cost to identify areas for improvement and to measure impact of healthcare delivery. However, variable HMIS data quality in low- and middle-income countries limits its value in monitoring, evaluation and research. We aimed to review the quality of Rwandan HMIS data for maternal and newborn health (MNH) based on consistency of HMIS reports with facility source documents.

METHODS

We conducted a cross-sectional study in 76 health facilities (HFs) in four Rwandan districts. For 14 MNH data elements, we compared HMIS data to facility register data recounted by study staff for a three-month period in 2017. A HF was excluded from a specific comparison if the service was not offered, source documents were unavailable or at least one HMIS report was missing for the study period. World Health Organization guidelines on HMIS data verification were used: a verification factor (VF) was defined as the ratio of register over HMIS data. A VF<0.90 or VF>1.10 indicated over- and under-reporting in HMIS, respectively.

RESULTS

High proportions of HFs achieved acceptable VFs for data on the number of deliveries (98.7%;75/76), antenatal care (ANC1) new registrants (95.7%;66/69), live births (94.7%;72/76), and newborns who received first postnatal care within 24 hours (81.5%;53/65). This was slightly lower for the number of women who received iron/folic acid (78.3%;47/60) and tested for syphilis in ANC1 (67.6%;45/68) and was the lowest for the number of women with ANC1 standard visit (25.0%;17/68) and fourth standard visit (ANC4) (17.4%;12/69). The majority of HFs over-reported on ANC4 (76.8%;53/69) and ANC1 (64.7%;44/68) standard visits.

CONCLUSION

There was variable HMIS data quality by data element, with some indicators with high quality and also consistency in reporting trends across districts. Over-reporting was observed for ANC-related data requiring more complex calculations, i.e., knowledge of gestational age, scheduling to determine ANC standard visits, as well as quality indicators in ANC. Ongoing data quality assessments and training to address gaps could help improve HMIS data quality.

Utilization of key preventive measures for pregnancy complications and malaria among women in Jimma Zone, Ethiopia

Background

In Ethiopia, malaria infections and other complications during pregnancy contribute to the high burden of maternal morbidity and mortality. Preventive measures are available, however little is known about the factors influencing the uptake of maternal health services and interventions by pregnant women in Ethiopia.

Methods

We analyzed data from a community-based cross-sectional survey conducted in 2016 in three rural districts of Jimma Zone, Ethiopia, with 3784 women who had a pregnancy outcome in the year preceding the survey. We used multivariable logistic regression models accounting for clustering to identify the determinants of antenatal care (ANC) attendance and insecticide-treated net (ITN) ownership and use, and the prevalence and predictors of malaria infection among pregnant women.

Results

Eighty-four percent of interviewed women reported receiving at least one ANC visit during their last pregnancy, while 47% reported attending four or more ANC visits. Common reasons for not attending ANC included women’s lack of awareness of its importance (48%), distance to health facility (23%) and unavailability of transportation (14%). Important determinants of ANC attendance included higher education level and wealth status, woman’s ability to make healthcare decisions, and pregnancy intendedness. An estimated 48% of women reported owning an ITN during their last pregnancy. Of these, 55% reported to have always slept under it during their last pregnancy. Analysis revealed that the odds of owning and using ITNs were respectively 2.07 (95% CI: 1.62–2.63) and 1.73 (95% CI: 1.32–2.27) times higher among women who attended at least one ANC visit. The self-reported prevalence of malaria infection during pregnancy was low (1.4%) across the three districts. We found that young, uneducated, and unemployed women presented higher odds of malaria infection during their last pregnancy.

Conclusion

ANC and ITN uptake during pregnancy in Jimma Zone fall below the respective targets of 95 and 90% set in the Ethiopian Health Sector Transformation Plan for 2020, suggesting that more intensive programmatic efforts still need to be directed towards improving access to these health services. Reaching ANC non-users and ITN ownership and use as part of ANC services could be emphasized to address these gaps.

Measuring progress towards universal health coverage: national and subnational analysis in Ethiopia

Introduction

Aiming for universal health coverage (UHC) as a country-level goal requires that progress is measured and tracked over time. However, few national and subnational studies monitor UHC in low-income countries and there is none for Ethiopia. This study aimed to estimate the 2015 national and subnational UHC service coverage status for Ethiopia.

Methods

The UHC service coverage index was constructed from the geometric means of component indicators: first, within each of four major categories and then across all components to obtain the final summary index. Also, we estimated the subnational level UHC service coverage. We used a variety of surveys data and routinely collected administrative data.

Results

Nationally, the overall Ethiopian UHC service coverage for the year 2015 was 34.3%, ranging from 52.2% in the Addis Ababa city administration to 10% in the Afar region. The coverage for non-communicable diseases, reproductive, maternal, neonatal and child health and infectious diseases were 35%, 37.5% and 52.8%, respectively. The national UHC service capacity and access coverage was only 20% with large variations across regions, ranging from 3.7% in the Somali region to 41.1% in the Harari region.

Conclusion

The 2015 overall UHC service coverage for Ethiopia was low compared with most of the other countries in the region. Also, there was a substantial variation among regions. Therefore, Ethiopia should rapidly scale up promotive, preventive and curative health services through increasing investment in primary healthcare if Ethiopia aims to reach the UHC service coverage goals. Also, policymakers at the regional and federal levels should take corrective measures to narrow the gap across regions, such as redistribution of the health workforce, increase resources allocated to health and provide focused technical and financial support to low-performing regions.

Optimizing data quality of pharmaceutical information systems in public health care in resource limited settings

BACKGROUND

Robust pharmaceutical management information systems (PMIS) strengthen healthcare planning and delivery. Few nationwide studies in resource limited settings in Africa validate the data quality of PMIS in public healthcare.

OBJECTIVE

To determine predictors and quality of data in a nationwide PMIS database in Namibia.

METHODS

A population-level analysis of the quality of data i.e. completeness, accuracy and consistency in a nationwide PMIS database, 2007-2015. Data quality of the PMIS was determined by three domains, completeness, accuracy and consistency. Data completeness was determined by level of missing data in SPSSv25, with acceptable level set at <5%. Data accuracy was determined by proportion of PMIS indicators with extreme outliers. Data consistence was determined by patterns of missingness, i.e. random or systematic. Predictors of data quality were determined using logistic regression modelling.

RESULTS

A total of 544 entries and 12 indicators were registered in the PMIS at 38 public health facilities. All the PMIS indicators had missing data and 50% (n = 6) had inaccurate data i.e. extreme values. The data for most PMIS indicators (75%, n = 12) were consistent with the pattern of missing completely at random (MCAR, i.e. missingness <5%). Incompleteness of PMIS data was highest for average number of prescriptions 6%, annual expenditure per capita for pharmaceuticals 5% and population per pharmacist's assistant 5%. The main predictors of poor quality of PMIS data were year of reporting of PMIS data (p = 0.035), level of health facility (p < 0.001), vital reference materials available at the pharmacy (p = 0.002), and pharmacists' posts filled (p = 0.013).

CONCLUSIONS

The data quality of PMIS in public health care in Namibia is sub-optimal and widely varies by reporting period, level of health facility and region. The integration of data quality assurance systems is required to strengthen quality of PMIS data to optimize quality of PMIS data in public health care.