Quality of maternal and newborn health care in Ethiopia: a cross-sectional study

BMC Health Services Research, Volume 21, No. 1, Year 2021

Interpretation

Background: Despite reports of universal access to and modest utilization of maternal and newborn health services in Ethiopia, mothers and newborns continue to die from preventable causes. Studies indicate this could be due to poor quality of care provided in health systems. Evidences show that high quality health care prevents more than half of all maternal deaths. In Ethiopia, there is limited knowledge surrounding the status of the quality of maternal and newborn health care in health facilities. This study aims to assess the quality of maternal and neonatal health care provision at the health facility level in four regions in Ethiopia. Methodology: This study employed a facility-based cross-sectional study design. It included 32 health facilities which were part of the facilities for prototyping maternal and neonatal health quality improvement interventions. Data was collected using a structured questionnaire, key informant interviews and record reviews. Data was entered in Microsoft Excel and exported to STATA for analysis. Descriptive analysis results are presented in texts, tables and graphs. Quality of maternal and neonatal health care was measured by input, process and outputs components. The components were developed by computing scores using standards used to measure the three components of the quality of maternal and neonatal health care. Result: The study was done in a total of 32 health facilities: 5 hospitals and 27 health centers in four regions. The study revealed that the average value of the quality of the maternal and neonatal health care input component among health facilities was 62%, while the quality of the process component was 43%. The quality of the maternal and neonatal health output component was 48%. According to the standard cut-off point for MNH quality of care, only 5 (15.6%), 3 (9.3%) and 3 (10.7%) of health facilities met the expected input, process and output maternal and neonatal health care quality standards, respectively. Conclusion: This study revealed that the majority of health facilities did not meet the national MNH quality of care standards. Focus should be directed towards improving the input, process and output standards of the maternal and neonatal health care quality, with the strongest focus on process improvement. Ethiopia has very diversified culture and more than 86 indigenous languages. Administratively, it has ten regions and two city administrations. Among those 10 regions and two city administration, the four regions which the four prototype districts selected house 81% of the country’s population. Each region subdivided into districts and there are over 850 districts in nationwide. Health service delivery is provided through a three-tier system as primary, secondary, and tertiary level health care. Four districts were chosen for the prototype phase of the QI project that began in 2016: Limu bilbilu, Tanqua Abergele, Duguna Fango and Fogera in the Oromia, Tigray, Southern Nations, Nationalities and Peoples’ (SNNP) and Amhara regions, respectively. A total of 121 health posts, 27 health centers and 5 hospitals that were providing MNH care for the population in the four districts were included in prototype and clustered into four QI collaborative sites, one for each district. The catchment populations of the collaborative sites were 213,032 in Limu Bilbilu, 115,841 in Tanqua Abergele, 122,316 in Duguna Fango, and 296,842 in Fogera districts. The prototype collaborative sites were purposefully selected in consultation with Ministry of Health of Ethiopia and regional health bureaus (RHBs) based on pre-set criteria. The criteria included high maternal and perinatal deaths, high level of leadership commitment to improve the service, reliability of MNH service data, and no other partner organizations working on quality improvement project in the sites to minimize duplication of efforts. All health facilities under the selected districts were included in the collaborative including health posts, health centers and hospitals. All districts had maternal mortality, still births and neonatal deaths; they are agrarian; the staff were interested to improve the system and no organization working on quality issues. A facility based cross-sectional study was deployed to determine the quality of MNH care in the QI collaborative sites. Quality of MNH care was measured using input, process and outcome components. The components were developed using input, process and output MNH quality standards of the WHO and HSTQ for health facilities of Ethiopia MoH. Data were collected in 2016 using face to face interviews and data extraction. Data were organized to be collected as elements of the input, process, and outcome variable. Input quality standards was developed using 28 items related to the infrastructure, supplies and equipment standards. Process quality standards was developed using 13 items of the labour, delivery and postnatal care provision and complication management standards. Outcome quality standards was measured using four items related to the health seeking behavior standards (Table (Table1).1). The three quality standard elements were selected and withdrawn from the broader HSTQ standard measures for the purpose of the study. Those all items of inputs, process and output standards were selected based on the national HSTQ MNH focus and their contribution to maternal and neonatal mortality. Quality standard items list The study included 32 health facilities which were part of the facilities for prototyping maternal and neonatal health quality improvement interventions. All health facility heads, and maternity care related department heads were included for the interviews. Data from individual patient records were extracted through selecting individual patient’s records by applying a systematic random sampling method using medical record numbers (MRN) as the sample frame. Previous 6 months delivery records in the MNH registration were included in the sample frame and it is sampled ten medical records for every month in each facility. There were 9602 medical records in total from all health facilities in the six-month period. The data was collected at the start of the implementation of IHI’s project from Sep 2016 to Nov 2016 at the health facilities. Structured interviews with health facility and department heads were conducted to assess availability of resources. Direct observation was also done to complement and verify interview results to cross check the available infrastructures, medical equipment’s, supplies, and available services. Before the data collection the data collectors discussed and agreed upon each question. The data collectors were IHI staff and zonal health departments (ZHD)/district health offices MNH and HMIS officers. The collected data were cross-checked for completeness immediately after completion. The data collection tool had two parts: 1) An interview guide which was used to collect the data from the health facility heads and maternity care related department heads. During the interview, there was cross-checking of records through direct looking on records to confirm the reliability of the data they provided. 2) A data abstraction form which was used to collect the data from the MNH registers and clients’ individual patient medical records. The output data was extracted from the MNH registers, and the process data of clinical care elements and complication management were extracted from the individual patient records to measure the required care elements are given and complications are managed according to the national complication protocol. During the data extraction data elements were cross-checked among the registers and individual patient records; if there is a discrepancy, that element was dropped. In general, input elements were assessed through interviews in 32 health facility heads and department heads; process elements of the quality of MNH care were assessed by using data extracted from a total of 1920 individual patient records in 32 health facilities, and output elements were assessed from 32 health facility MNH registers. Data was entered in to an excel database and cleaning was done by running simple frequencies and looking for unusual (out of the coding value) and incomplete values. The selected variables for this study were extracted, coded, and exported to STATA version 13 for analysis. Elements of the input, process, and outcome variable were coded, analyzed and described using average scores. To look the difference of care provision among the facility type, average score was used to compare health centers and hospitals. Further analysis was done based on the operational definition of “satisfactory quality” and “unsatisfactory quality” using the cutoff point of meeting at least 75% of the standards using the previous study [12]. An analysis of the average score of MNH quality of care was done separately for input, process and outcome and then for the overall score. Each element contributes equally to the score for the respective variable. For the input variable, number of health facilities were used as denominator and number of sample patient records for MNH clinical care process variable and number of complicated cases for the complication management process variable. Estimated number of deliveries were used as denominator for calculating the output standards of antenatal care, skilled births and postnatal care. First antenatal care visit was used as the denominator for syphilis test variable. The data was collected primary for the improvement purpose in the health facilities, which is part of a broader IHI project evaluation study that was reviewed and approved by Ethiopian Public Health Association (EPHA) Scientific and Ethical Review Committee (Ref: EPHA/OG/5046/17). It was purely program evaluation and was waived by the aforementioned IRB in accordance with Ethiopia ethical guideline [13]. Then, a permission was obtained from IHI Ethiopia project office to analyze further the stored data for this manuscript. During the data collection process, informed consent was obtained from all interview subjects and from health facility heads on behalf of mothers for the medical record reviews since not possible to trace them. Confidentiality of the information and their privacy were respected throughout the data collection process and then after. All responses given by the participants have been kept anonymous and confidential using coding system whereby no one has access to the information.

AI Digest

Study Justification:

– Despite reports of universal access to maternal and newborn health services in Ethiopia, preventable deaths still occur due to poor quality of care.
– High-quality health care can prevent more than half of all maternal deaths.
– Limited knowledge exists regarding the quality of maternal and newborn health care in Ethiopian health facilities.

Study Highlights:

– The study assessed the quality of maternal and neonatal health care in 32 health facilities in four regions of Ethiopia.
– The study used input, process, and output components to measure the quality of care.
– The average quality scores were 62% for input, 43% for process, and 48% for output.
– Only a small percentage of health facilities met the expected quality standards for input, process, and output.

Study Recommendations:

– Focus should be directed towards improving the input, process, and output standards of maternal and neonatal health care.
– Strong emphasis should be placed on process improvement.

Key Role Players:

– Ministry of Health of Ethiopia
– Regional health bureaus
– Health facility heads
– Maternity care department heads

Cost Items for Planning Recommendations:

– Training and capacity building for health facility staff
– Infrastructure improvement
– Procurement of necessary supplies and equipment
– Monitoring and evaluation activities
– Quality improvement interventions and initiatives

Strength of Evidence

The strength of evidence for this abstract is 7 out of 10.
The evidence in the abstract is based on a cross-sectional study design and includes data collected from 32 health facilities in four regions of Ethiopia. The study measures the quality of maternal and neonatal health care using input, process, and output components. The study provides descriptive analysis results and reveals that the majority of health facilities did not meet the national MNH quality of care standards. The abstract could be improved by providing more information on the methodology, such as the sampling strategy and data collection methods. Additionally, it would be helpful to include information on the limitations of the study and suggestions for future research.

Abstract

Ethiopia has very diversified culture and more than 86 indigenous languages. Administratively, it has ten regions and two city administrations. Among those 10 regions and two city administration, the four regions which the four prototype districts selected house 81% of the country’s population. Each region subdivided into districts and there are over 850 districts in nationwide. Health service delivery is provided through a three-tier system as primary, secondary, and tertiary level health care. Four districts were chosen for the prototype phase of the QI project that began in 2016: Limu bilbilu, Tanqua Abergele, Duguna Fango and Fogera in the Oromia, Tigray, Southern Nations, Nationalities and Peoples’ (SNNP) and Amhara regions, respectively. A total of 121 health posts, 27 health centers and 5 hospitals that were providing MNH care for the population in the four districts were included in prototype and clustered into four QI collaborative sites, one for each district. The catchment populations of the collaborative sites were 213,032 in Limu Bilbilu, 115,841 in Tanqua Abergele, 122,316 in Duguna Fango, and 296,842 in Fogera districts. The prototype collaborative sites were purposefully selected in consultation with Ministry of Health of Ethiopia and regional health bureaus (RHBs) based on pre-set criteria. The criteria included high maternal and perinatal deaths, high level of leadership commitment to improve the service, reliability of MNH service data, and no other partner organizations working on quality improvement project in the sites to minimize duplication of efforts. All health facilities under the selected districts were included in the collaborative including health posts, health centers and hospitals. All districts had maternal mortality, still births and neonatal deaths; they are agrarian; the staff were interested to improve the system and no organization working on quality issues. A facility based cross-sectional study was deployed to determine the quality of MNH care in the QI collaborative sites. Quality of MNH care was measured using input, process and outcome components. The components were developed using input, process and output MNH quality standards of the WHO and HSTQ for health facilities of Ethiopia MoH. Data were collected in 2016 using face to face interviews and data extraction. Data were organized to be collected as elements of the input, process, and outcome variable. Input quality standards was developed using 28 items related to the infrastructure, supplies and equipment standards. Process quality standards was developed using 13 items of the labour, delivery and postnatal care provision and complication management standards. Outcome quality standards was measured using four items related to the health seeking behavior standards (Table (Table1).1). The three quality standard elements were selected and withdrawn from the broader HSTQ standard measures for the purpose of the study. Those all items of inputs, process and output standards were selected based on the national HSTQ MNH focus and their contribution to maternal and neonatal mortality. Quality standard items list The study included 32 health facilities which were part of the facilities for prototyping maternal and neonatal health quality improvement interventions. All health facility heads, and maternity care related department heads were included for the interviews. Data from individual patient records were extracted through selecting individual patient’s records by applying a systematic random sampling method using medical record numbers (MRN) as the sample frame. Previous 6 months delivery records in the MNH registration were included in the sample frame and it is sampled ten medical records for every month in each facility. There were 9602 medical records in total from all health facilities in the six-month period. The data was collected at the start of the implementation of IHI’s project from Sep 2016 to Nov 2016 at the health facilities. Structured interviews with health facility and department heads were conducted to assess availability of resources. Direct observation was also done to complement and verify interview results to cross check the available infrastructures, medical equipment’s, supplies, and available services. Before the data collection the data collectors discussed and agreed upon each question. The data collectors were IHI staff and zonal health departments (ZHD)/district health offices MNH and HMIS officers. The collected data were cross-checked for completeness immediately after completion. The data collection tool had two parts: 1) An interview guide which was used to collect the data from the health facility heads and maternity care related department heads. During the interview, there was cross-checking of records through direct looking on records to confirm the reliability of the data they provided. 2) A data abstraction form which was used to collect the data from the MNH registers and clients’ individual patient medical records. The output data was extracted from the MNH registers, and the process data of clinical care elements and complication management were extracted from the individual patient records to measure the required care elements are given and complications are managed according to the national complication protocol. During the data extraction data elements were cross-checked among the registers and individual patient records; if there is a discrepancy, that element was dropped. In general, input elements were assessed through interviews in 32 health facility heads and department heads; process elements of the quality of MNH care were assessed by using data extracted from a total of 1920 individual patient records in 32 health facilities, and output elements were assessed from 32 health facility MNH registers. Data was entered in to an excel database and cleaning was done by running simple frequencies and looking for unusual (out of the coding value) and incomplete values. The selected variables for this study were extracted, coded, and exported to STATA version 13 for analysis. Elements of the input, process, and outcome variable were coded, analyzed and described using average scores. To look the difference of care provision among the facility type, average score was used to compare health centers and hospitals. Further analysis was done based on the operational definition of “satisfactory quality” and “unsatisfactory quality” using the cutoff point of meeting at least 75% of the standards using the previous study [12]. An analysis of the average score of MNH quality of care was done separately for input, process and outcome and then for the overall score. Each element contributes equally to the score for the respective variable. For the input variable, number of health facilities were used as denominator and number of sample patient records for MNH clinical care process variable and number of complicated cases for the complication management process variable. Estimated number of deliveries were used as denominator for calculating the output standards of antenatal care, skilled births and postnatal care. First antenatal care visit was used as the denominator for syphilis test variable. The data was collected primary for the improvement purpose in the health facilities, which is part of a broader IHI project evaluation study that was reviewed and approved by Ethiopian Public Health Association (EPHA) Scientific and Ethical Review Committee (Ref: EPHA/OG/5046/17). It was purely program evaluation and was waived by the aforementioned IRB in accordance with Ethiopia ethical guideline [13]. Then, a permission was obtained from IHI Ethiopia project office to analyze further the stored data for this manuscript. During the data collection process, informed consent was obtained from all interview subjects and from health facility heads on behalf of mothers for the medical record reviews since not possible to trace them. Confidentiality of the information and their privacy were respected throughout the data collection process and then after. All responses given by the participants have been kept anonymous and confidential using coding system whereby no one has access to the information.

Materials

Innovations

Based on the provided information, here are some potential innovations that could be used to improve access to maternal health in Ethiopia:

1. Telemedicine: Implementing telemedicine technologies can help connect pregnant women in remote areas with healthcare providers, allowing them to receive prenatal care and consultations without having to travel long distances.

2. Mobile health (mHealth) applications: Developing mobile applications that provide information and resources on maternal health, such as prenatal care guidelines, nutrition advice, and appointment reminders, can help educate and empower pregnant women to take better care of themselves and their babies.

3. Community health workers: Training and deploying community health workers who can provide basic prenatal care, health education, and referrals to pregnant women in rural areas can help bridge the gap in access to maternal health services.

4. Transportation solutions: Improving transportation infrastructure and implementing transportation services specifically for pregnant women can help overcome geographical barriers and ensure timely access to healthcare facilities for prenatal care, delivery, and postnatal care.

5. Maternal health clinics: Establishing dedicated maternal health clinics in underserved areas can provide comprehensive prenatal, delivery, and postnatal care services, ensuring that pregnant women have access to quality care throughout their pregnancy journey.

6. Health information systems: Implementing robust health information systems that capture and analyze data on maternal health can help identify gaps in care, monitor progress, and inform evidence-based decision-making for improving access and quality of maternal health services.

7. Public-private partnerships: Collaborating with private healthcare providers and organizations can help expand access to maternal health services, leverage resources, and improve the overall quality of care.

8. Maternal health education programs: Developing and implementing educational programs that focus on maternal health, including prenatal care, nutrition, hygiene, and birth preparedness, can empower women with knowledge and skills to make informed decisions about their health and the health of their babies.

9. Maternal health financing mechanisms: Exploring innovative financing mechanisms, such as health insurance schemes or conditional cash transfer programs, can help reduce financial barriers to accessing maternal health services and ensure that all women, regardless of their socioeconomic status, can receive the care they need.

10. Quality improvement initiatives: Implementing quality improvement initiatives at health facilities, such as training healthcare providers on evidence-based practices, improving infection prevention and control measures, and strengthening referral systems, can enhance the overall quality of maternal health services and improve health outcomes for mothers and newborns.

These innovations, when tailored to the specific context and needs of Ethiopia, have the potential to improve access to maternal health services and contribute to reducing maternal and newborn mortality rates in the country.

AI Innovations Description

Based on the provided description, the recommendation to improve access to maternal health in Ethiopia is to focus on improving the quality of maternal and neonatal health care in health facilities. The study revealed that the majority of health facilities did not meet the national standards for quality of care. Therefore, the following steps can be taken to develop an innovation:

1. Strengthen input standards: Improve the infrastructure, supplies, and equipment in health facilities to ensure they meet the required standards for maternal and neonatal health care.

2. Enhance process standards: Focus on improving the labor, delivery, and postnatal care provision, as well as complication management in health facilities. This can be achieved through training and capacity building for healthcare providers.

3. Improve output standards: Enhance health-seeking behavior among mothers by providing education and awareness programs on the importance of antenatal care, skilled births, and postnatal care. This can help increase the utilization of maternal health services.

4. Implement quality improvement interventions: Develop and implement quality improvement interventions in health facilities to address the identified gaps in input, process, and output standards. This can involve regular monitoring and evaluation of the quality of care provided.

5. Strengthen leadership commitment: Ensure strong leadership commitment at all levels, from the Ministry of Health to regional health bureaus and health facility heads, to prioritize and support efforts to improve the quality of maternal and neonatal health care.

By focusing on these recommendations, Ethiopia can work towards improving access to high-quality maternal health care, ultimately reducing maternal and neonatal mortality rates.

AI Innovations Methodology

Based on the provided information, here are some potential recommendations to improve access to maternal health in Ethiopia:

1. Strengthening Health Infrastructure: Invest in improving the infrastructure of health facilities, including the availability of essential equipment, supplies, and medications. This will ensure that health facilities are adequately equipped to provide quality maternal and neonatal health care.

2. Enhancing Human Resources: Increase the number of skilled health care providers, particularly midwives and obstetricians, in order to improve the availability and quality of maternal health services. This can be achieved through training programs, recruitment, and retention strategies.

3. Community Engagement and Education: Implement community-based interventions to raise awareness about maternal health issues, promote early antenatal care, and encourage women to seek skilled care during pregnancy, childbirth, and postpartum. This can be done through community health workers, health education campaigns, and community mobilization.

4. Strengthening Referral Systems: Improve the coordination and effectiveness of referral systems between health facilities at different levels of care. This will ensure that women with complications during pregnancy and childbirth can access appropriate and timely care.

To simulate the impact of these recommendations on improving access to maternal health, a methodology could include the following steps:

1. Baseline Data Collection: Gather data on the current status of maternal health access indicators, such as antenatal care coverage, skilled birth attendance, and postnatal care utilization. This data can be obtained through surveys, health facility records, and existing health information systems.

2. Define Simulation Parameters: Determine the specific parameters to be simulated, such as the increase in health infrastructure, the number of additional health care providers, or the coverage of community-based interventions. These parameters should be based on evidence-based targets and expert recommendations.

3. Model Development: Develop a simulation model that incorporates the baseline data and the defined parameters. This model should simulate the impact of the recommendations on maternal health access indicators, taking into account factors such as population size, geographical distribution, and existing health system capacities.

4. Sensitivity Analysis: Conduct sensitivity analysis to assess the robustness of the simulation results. This involves testing the model with different scenarios and assumptions to understand the potential range of outcomes.

5. Impact Assessment: Analyze the simulation results to assess the potential impact of the recommendations on improving access to maternal health. This can include estimating changes in maternal health indicators, such as increased antenatal care coverage or reduced maternal mortality rates.

6. Policy Recommendations: Based on the simulation results, provide policy recommendations on the most effective strategies to improve access to maternal health. These recommendations should consider the feasibility, cost-effectiveness, and sustainability of the proposed interventions.

It is important to note that simulation models are simplifications of complex systems and are based on assumptions. Therefore, the results should be interpreted with caution and validated with real-world data and implementation experiences.

Author

Dima Health

Statistics:

Citations: 5

Identifiers:

DOI: 10.1186/s12913-021-06680-1

Research Areas:

Community Interventions, Health System and Policy, Maternal Access, Maternal and Child Health, Quality of Care, Social Determinants

Study Countries:

Ethiopia

Study Design:

Cross Sectional Study, Grounded Theory

Study Approach:

Mixed-methods, Quantitative, Systematic Review