Distribution of maternity waiting homes and their correlation with perinatal mortality and direct obstetric complication rates in Ethiopia

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Study Justification:
– The study aims to address gaps in the distribution, service availability, and readiness of maternity waiting homes in Ethiopia.
– It also investigates the correlation between the presence of waiting homes and perinatal mortality and direct obstetric complication rates.
– The findings of the study can inform regional maternal and newborn improvement strategies and highlight areas for improvement in the distribution and conditions of waiting homes.
Study Highlights:
– Approximately half of the health facilities in Ethiopia have a waiting home.
– Regions such as Amhara, SNNP, and Oromia have a higher proportion of facilities with waiting homes, while Gambella has none.
– Highly urbanized regions have fewer waiting homes.
– Waiting homes at hospitals generally have better conditions compared to those at health centers.
– Facilities with waiting homes have similar or lower rates of perinatal death and direct obstetric complication rates compared to facilities without a waiting home.
– Hospitals with a waiting home have a 47% lower perinatal mortality rate and a 49% lower direct obstetric complication rate compared to hospitals without a waiting home.
Recommendations:
– Efforts should be made to improve the distribution and conditions of waiting homes, especially in pastoralist regions.
– Regular monitoring, refinement, and documentation of the impact of waiting homes should be prioritized as they continue to expand.
Key Role Players:
– Ministry of Health
– Regional health authorities
– Health facility administrators
– Health care workers
– Maternal and newborn health program managers
Cost Items for Planning Recommendations:
– Infrastructure improvement of waiting homes (e.g., construction, renovation)
– Provision of essential amenities (e.g., electricity, water, toilets, beds with mattresses)
– Training and capacity building for health care workers
– Monitoring and evaluation activities
– Data collection and analysis
– Communication and dissemination of findings
Please note that the above information is a summary of the study and its findings. For more detailed information, please refer to the publication “Distribution of maternity waiting homes and their correlation with perinatal mortality and direct obstetric complication rates in Ethiopia” in BMC Pregnancy and Childbirth, Volume 19, No. 1, Year 2019.

Background: Ethiopia has been expanding maternity waiting homes to bridge geographical gaps between health facilities and communities in order to improve access to skilled care. In 2015, the Ministry of Health revised its national guidelines to standardize the rapid expansion of waiting homes. Little has been done to document their distribution, service availability and readiness. This paper addresses these gaps as well as their association with perinatal mortality and obstetric complication rates. Methods: We utilized data from the 2016 national Emergency Obstetric and Newborn Care assessment, a census of 3804 public and private health facilities. Data were collected between May and December 2016 through interviews with health care workers, record reviews, and observation of infrastructure. Descriptive statistics describe the distribution and characteristics of waiting homes and linear regression models examined the correlation between independent variables and institutional perinatal and peripartum outcomes. Results: Nationally, about half of facilities had a waiting home. More than two-thirds of facilities in Amhara and half of the facilities in SNNP and Oromia had a home while the region of Gambella had none. Highly urbanized regions had few homes. Conditions were better among homes at hospitals than at health centers. Finished floors, electricity, water, toilets, and beds with mattresses were available at three (or more) out of four hospital homes. Waiting homes in pastoralist regions were often at a disadvantage. Health facilities with waiting homes had similar or lower rates of perinatal death and direct obstetric complication rates than facilities without a home. The perinatal mortality was 47% lower in hospitals with a home than those without. Similarly, the direct obstetric complication rate was 49% lower at hospitals with a home compared to hospitals without. Conclusions: The findings should inform regional maternal and newborn improvement strategies, indicating gaps in the distribution and conditions, especially in the pastoralist regions. The impact of waiting homes on maternal and perinatal outcomes appear promising and as homes continue to expand, so should efforts to regularly monitor, refine and document their impact.

The country has a decentralized health system with three tiers where the first level provides primary health care and acts as the major platform for health service delivery. It consists of one primary hospital with four or five primary health care units (PHCUs). A PHCU is composed of a health center and five satellite health posts to serve approximately 25 thousand people. Health centers are staffed with health officers, nurses, midwives, and laboratory technicians to provide primarily preventive care including ANC, delivery and post-natal care, curative, inpatient and ambulatory services, including maternal and child health (MCH) services. It serves as a referral center and administrative and technical linkage to health posts. A primary hospital provides inpatient and ambulatory services to an average population of 100,000. It also provides emergency surgical services, including cesarean sections and access to blood transfusion services, and serves as a referral center for the health centers in its catchment area while serving as a practical training center for nurses and other paramedical health professionals. General hospitals provide care at the secondary level to a catchment population of approximately one million people. They serve as referral and training centers for primary hospitals and mid-level professionals. The third level is a specialized hospital that serves a catchment population of about five general hospitals or 5 million people. All public health centers and hospitals, as well as private hospitals and MCH specialty clinics, are expected to provide delivery services. Ethiopia is committed to improving maternal and newborn health outcomes and its targets are aligned with those of the Sustainable Development Goals. To improve outcomes, Ethiopia aims to strengthen health systems to provide universal access to high quality promotive, preventive, curative, and rehabilitative services. This strategy is laid out in the Health Sector Transformation Plan (HSTP 2015–2020). During the HSTP period, the Federal Ministry of Health has developed different strategies and initiatives including the establishment of effective clinical mentorship and quality improvement initiatives. Moreover, the government seeks to improve access to and utilization of EmONC services by promoting facility delivery, expanding MWHs at health centers [17], strengthening referral linkages through the procurement and distribution of ambulances, expanding the number of health facilities, and the number of midwives, emergency surgical officers, and specialty professionals to ensure EmONC services [22]. Maternity waiting homes are expected to be available in most rural health centers which are closer to the rural population than other health facilities. This is a secondary analysis of the 2016 national EmONC assessment [18], a national cross-sectional census of 3804 public and private health facilities that provided maternal and newborn health services. All public hospitals (referral, general, primary) and health centers, and all private (for-profit and not-for-profit) facilities (hospitals, MCH specialty centers, MCH specialty clinics, and higher clinics) that reported having attended births in the 12 months prior to the survey were included in the study. Facilities classified as medium clinics or below were excluded per the guidance of the Food, Medicine and Health Care Administration and Control Authority of Ethiopia, who sets out which facilities are expected to provide childbirth services. The 2008 Ethiopia EmONC assessment modules (questionnaires) and a set of survey tools revised by Columbia University’s Averting Maternal Death and Disability Program (AMDD) in 2014 were adapted to the national context. The Ethiopian Public Health Institute (EPHI) designed an electronic data collection template using CSPro 6.1. Data were collected between May and December 2016 through interviews with health care workers, record reviews, and observation of infrastructure. The overall assessment utilized 14 facility-based modules. Ethiopia was the first country to test the MWH module. It included data related to the infrastructure, support, and features of the MWH as reported by the facility medical director or designee. For this secondary analysis, we used the facility case summary and maternity waiting home modules. Data were managed using CSPro 6.1 programming and exported to Stata 15.1 for statistical analysis [23]. Distribution, infrastructure, and characteristics of MWHs were described and the association between independent and dependent variables were analyzed using univariate and multivariate linear regression models where the unit of analysis was the facility. The outcome variables considered in this analysis were the institutional perinatal death rate (PDR) and direct obstetric complication rate (DOCR) in the 12-month period preceding the assessment. We defined perinatal deaths as all stillbirths (macerated and fresh) and all live births who died within 24 h or before discharge, whichever came first. The perinatal deaths were divided by the number of deliveries that took place in the facility over the same period and multiplied by 100. The DOCR was defined as the proportion of admitted women who had a major obstetric complication (antepartum or postpartum hemorrhage, retained placenta, severe pre-eclampsia or eclampsia, severe abortion complications, uterine rupture, ectopic pregnancy and prolonged/obstructed labor) as well as any other direct obstetric complication (multiple gestation, premature rupture of membranes, etc.). It was calculated as the number of women with obstetric complications treated divided by the number of deliveries recorded in the same facility, multiplied by 100. We performed logarithmic transformations on each outcome variable prior to running the models to achieve a more normal distribution; thus, regression coefficients should be interpreted as percent change. The independent variable of primary interest was the availability of a MWH. Moreover, we included region, managing authority of the facility, location of facility (urban/rural), availability of motor transport, density of skilled birth attendants (SBAs) per annual deliveries, and volume of annual deliveries. Other variables and their operational definitions used in this study are presented below. EmONC facility: EmONC is defined as a set of life-saving interventions used to treat the major obstetric causes of morbidity and mortality. To assess the level of care, the performance of these signal functions in the last 3 months defines whether a facility is classified as providing basic EmONC (BEmONC) or comprehensive EmONC (CEmONC). BEmONC services comprise: 1) administration of parenteral antibiotics to prevent puerperal infection or treat abortion complications; 2) administration of parenteral anticonvulsants for treatment of eclampsia and preeclampsia; 3) administration of parenteral uterotonic drugs for postpartum hemorrhage; 4) manual removal of the placenta; 5) assisted vaginal delivery (vacuum extractions); 6) removal of retained products of conception; and 7) neonatal resuscitation with bag and mask. CEmONC services comprise cesarean sections and blood transfusions, in addition to all BEmONC functions [13]. Index of MWH infrastructure and amenities: an index score was calculated for each MWH, measured by 10 infrastructure and amenity indicators listed in Table 1. Each item was given a score of 0–2 points: 2 for each item available that met the standard, 1 for partial availability and 0 for not available or below the standard. Three items had a maximum of 1 point. Items were given equal weights and a total score was generated; maximum score being 17. Waiting homes that scored 13 or more were categorized as optimal, scores in the range of 9–12 points were ranked as basic, and scores less than 9 were considered substandard. Items used to measure MHW index score

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The recommendation to improve access to maternal health in Ethiopia is the distribution of maternity waiting homes. These facilities bridge the geographical gaps between health facilities and communities, allowing pregnant women to stay closer to a health facility as they approach their due date. A study conducted in Ethiopia found that facilities with waiting homes had similar or lower rates of perinatal death and direct obstetric complication rates compared to facilities without a waiting home.

The study revealed that about half of the health facilities in Ethiopia had a waiting home, with higher proportions in certain regions. However, there were gaps in the distribution and conditions of waiting homes, particularly in pastoralist regions. Waiting homes at hospitals generally had better conditions compared to those at health centers.

To improve access to skilled care during childbirth, the distribution of maternity waiting homes can be further expanded and improved. Efforts should be made to regularly monitor, refine, and document the impact of waiting homes on maternal and perinatal outcomes. This recommendation aligns with Ethiopia’s commitment to improving maternal and newborn health outcomes and its targets under the Sustainable Development Goals.

By implementing this recommendation, pregnant women in Ethiopia, especially those in rural areas, will have better access to skilled care during childbirth, leading to improved maternal and perinatal health outcomes.
AI Innovations Description
The recommendation to improve access to maternal health is the distribution of maternity waiting homes. Maternity waiting homes are facilities that bridge the geographical gaps between health facilities and communities, allowing pregnant women to stay closer to a health facility as they approach their due date. This recommendation is based on a study conducted in Ethiopia, which found that facilities with waiting homes had similar or lower rates of perinatal death and direct obstetric complication rates compared to facilities without a waiting home.

The study revealed that about half of the health facilities in Ethiopia had a waiting home, with higher proportions in certain regions. However, there were gaps in the distribution and conditions of waiting homes, particularly in pastoralist regions. The study also found that waiting homes at hospitals generally had better conditions compared to those at health centers.

The distribution of maternity waiting homes can be further expanded and improved to ensure that more pregnant women have access to skilled care during childbirth. Efforts should be made to regularly monitor, refine, and document the impact of waiting homes on maternal and perinatal outcomes. This recommendation aligns with Ethiopia’s commitment to improving maternal and newborn health outcomes and its targets under the Sustainable Development Goals.

By implementing this recommendation, pregnant women in Ethiopia, especially those in rural areas, will have better access to skilled care during childbirth, leading to improved maternal and perinatal health outcomes.
AI Innovations Methodology
The methodology used to simulate the impact of the main recommendations on improving access to maternal health in Ethiopia includes the following steps:

1. Data Collection: The study utilized data from the 2016 national Emergency Obstetric and Newborn Care assessment, which conducted a census of 3804 public and private health facilities in Ethiopia. Data were collected through interviews with healthcare workers, record reviews, and observation of infrastructure.

2. Descriptive Statistics: Descriptive statistics were used to describe the distribution and characteristics of maternity waiting homes (MWHs) in Ethiopia. This included analyzing the proportion of facilities with MWHs at the national level and in different regions, as well as comparing the conditions of MWHs at hospitals versus health centers.

3. Linear Regression Analysis: Linear regression models were used to examine the correlation between independent variables (such as the availability of MWHs) and institutional perinatal mortality rates and direct obstetric complication rates. The unit of analysis was the facility, and the outcome variables were the perinatal death rate and direct obstetric complication rate in the 12-month period preceding the assessment.

4. Transformation of Outcome Variables: Logarithmic transformations were performed on the outcome variables (perinatal death rate and direct obstetric complication rate) to achieve a more normal distribution.

5. Calculation of Outcome Measures: The perinatal death rate was calculated as the number of perinatal deaths divided by the number of deliveries in the facility, multiplied by 100. The direct obstetric complication rate was calculated as the number of women with obstetric complications treated divided by the number of deliveries in the facility, multiplied by 100.

6. Analysis of Independent Variables: The availability of MWHs was the primary independent variable of interest. Other independent variables included region, managing authority of the facility, location of the facility (urban/rural), availability of motor transport, density of skilled birth attendants per annual deliveries, and volume of annual deliveries.

7. Index of MWH Infrastructure and Amenities: An index score was calculated for each MWH based on 10 infrastructure and amenity indicators. Each item was given a score of 0-2 points, and a total score was generated. MWHs were categorized as optimal, basic, or substandard based on their index scores.

8. Statistical Analysis: Statistical analysis was performed using Stata 15.1 software. Univariate and multivariate linear regression models were used to analyze the association between independent and dependent variables.

By following this methodology, the study was able to assess the distribution and conditions of MWHs in Ethiopia and determine their correlation with perinatal mortality and direct obstetric complication rates. The findings of the study can inform regional maternal and newborn improvement strategies and guide efforts to expand and improve the distribution of MWHs in order to improve access to skilled care during childbirth and ultimately improve maternal and perinatal health outcomes.

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