If we build it, will they come? Results of a quasi-experimental study assessing the impact of maternity waiting homes on facility-based childbirth and maternity care in Zambia

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Study Justification:
The study aimed to assess the impact of maternity waiting homes (MWHs) on facility-based childbirth and maternity care in Zambia. MWHs are designed to increase access to maternity and emergency obstetric care by allowing women to stay near a health center before delivery. The study aimed to determine if an improved MWH model would increase health facility delivery among remote-living women in Zambia.
Highlights:
– The study used a quasi-experimental design and included 40 rural health centers in Zambia.
– Intervention clusters (n=20) received an improved MWH model, while control clusters (n=20) implemented standard of care.
– The study found that the improved MWH model was associated with increased odds of facility delivery, MWH utilization, postnatal attendance, counseling for family planning, breastfeeding, kangaroo care, and caesarean section.
– No differences were observed in household expenditures for delivery.
Recommendations:
Based on the study findings, the following recommendations can be made:
1. Expand the implementation of improved MWH models in rural areas to increase access to facility delivery and improve maternity care utilization.
2. Strengthen linkages between MWHs and health centers to ensure regular check-ins and provision of maternal and child health education.
3. Promote the use of MWHs through community outreach activities and engagement of key stakeholders, including men, community elders, and traditional leadership.
4. Continue monitoring and evaluation efforts to assess the long-term impact of MWHs on maternal and neonatal health outcomes.
Key Role Players:
1. Ministry of Health: Provide guidance and support in the implementation of improved MWH models.
2. Health Center Staff: Check-in on waiting women, provide maternal and child health education, and ensure the smooth operation of MWHs.
3. Community Leaders: Promote the use of MWHs through community engagement and outreach activities.
4. Traditional Leadership: Advocate for the importance of MWHs and encourage community participation.
5. Researchers and Evaluators: Conduct further studies and evaluations to assess the impact of MWHs on maternal and neonatal health outcomes.
Cost Items for Planning Recommendations:
1. Infrastructure: Construction or improvement of MWHs, including concrete floors, latrines, bathing areas, roofing, storage space, cooking facilities, and sleeping accommodations.
2. Equipment and Supplies: Provision of necessary items such as beds, bedding, mattresses, mosquito nets, cooking utensils, lighting, and water supply.
3. Staffing: Allocation of health center staff or volunteers to check-in on waiting women and provide maternal and child health education.
4. Training and Capacity Building: Training programs for health center staff on MWH management and maternal and child health education.
5. Community Engagement: Development and implementation of community outreach activities, communication campaigns, and engagement of key stakeholders.
6. Monitoring and Evaluation: Allocation of resources for ongoing monitoring and evaluation efforts to assess the impact of MWHs on maternal and neonatal health outcomes.
Please note that the cost items provided are for planning purposes and do not represent actual costs.

The strength of evidence for this abstract is 8 out of 10.
The evidence in the abstract is strong because it is based on a quasi-experimental study conducted at 40 rural health centers in Zambia. The study used a cluster design and included a large sample size of 2381 women at baseline and 2330 women at endline. The study measured various outcomes including facility delivery, postnatal care utilization, counseling, services received, and expenditures. The results showed that the improved maternity waiting home model was associated with increased odds of facility delivery, MWH utilization, postnatal attendance, counseling for family planning, breastfeeding, kangaroo care, and caesarean section. The study also found no differences in household expenditures for delivery. To improve the evidence, future studies could consider using a randomized controlled trial design and include a control group that receives no intervention.

Introduction Maternity waiting homes (MWHs) aim to increase access to maternity and emergency obstetric care by allowing women to stay near a health centre before delivery. An improved MWH model was developed with community input and included infrastructure, policies and linkages to health centres. We hypothesised this MWH model would increase health facility delivery among remote-living women in Zambia. Methods We conducted a quasi-experimental study at 40 rural health centres (RHC) that offer basic emergency obstetric care and had no recent stockouts of oxytocin or magnesium sulfate, located within 2 hours of a referral hospital. Intervention clusters (n=20) received an improved MWH model. Control clusters (n=20) implemented standard of care. Clusters were assigned to study arm using a matched-pair randomisation procedure (n=20) or non-randomly with matching criteria (n=20). We interviewed repeated cross-sectional random samples of women in villages 10+ kilometres from their RHC. The primary outcome was facility delivery; secondary outcomes included postnatal care utilisation, counselling, services received and expenditures. Intention-to-treat analysis was conducted. Generalised estimating equations were used to estimate ORs. Results We interviewed 2381 women at baseline (March 2016) and 2330 at endline (October 2018). The improved MWH model was associated with increased odds of facility delivery (OR 1.60 (95% CI: 1.13 to 2.27); p<0.001) and MWH utilisation (OR 2.44 (1.62 to 3.67); p<0.001). The intervention was also associated with increased odds of postnatal attendance (OR 1.55 (1.10 to 2.19); p<0.001); counselling for family planning (OR 1.48 (1.15 to 1.91); p=0.002), breast feeding (OR 1.51 (1.20 to 1.90); p0. For this model, we specified a Gaussian distribution for the dependent variable, an identity link function, and an exchangeable correlation structure. For all GEE models, matched-pair was specified as the group variable and robust SEs were estimated using a degrees-of-freedom corrected sandwich estimator. Except for referral from MWH (which had no baseline value prior to intervention), each model included the cluster-level average of the outcomes measured at baseline. Each model also controlled for the variables used in the matching procedure, average monthly volume of deliveries at nearest RHC and transfer time to nearest CEmONC hospital. No additional covariates were included in the main models. Because half of study clusters were non-randomly assigned, we present adjusted estimates of impact on the primary outcome in online supplemental table A3 using models that included the following covariates: woman’s age (years), education (years), marital status, and primigravida, along with household wealth quintile and distance of the village centre to the nearest government assigned RHC (km). These covariates were selected based on a review of the literature and previous work on where women deliver in Zambia. bmjgh-2021-006385supp003.pdf As a robustness check, we also present estimates of impact on the primary outcomes using a set of mixed-effects models that include random effects for matched-pair, health facility catchment area, and village in online supplemental table A4.33 Finally, we present estimates of impact on the primary outcomes from a set of generalised linear probability models (ie, GEE specified as having a Gaussian distribution for the dependent variable and an identity link function) in online supplemental table A5. All analyses were conducted using Stata statistical software (StataCorp. 2015. Release V.14). All data for this analysis are publicly available.(dataset)34 bmjgh-2021-006385supp004.pdf bmjgh-2021-006385supp005.pdf End-users of the MWHs and other key community-level stakeholders including men, community elders and traditional leadership were involved in conceptualising and designing the intervention during a formative research phase.28 29 The intervention design was refined with input from the Ministry of Health. We continued to engage a variety of key stakeholders, including members of the target population, through a rigorous process evaluation that routinely assessed intervention acceptability, and implementation feasibility and fidelity.19 35 36 We were guided by the Consolidated Standards of Reporting Trials checklist extension for cluster randomised trials in preparing this article.

The innovation described in the study is the implementation of improved Maternity Waiting Homes (MWHs) near rural health centers in Zambia. The MWH model included infrastructure, policies, and linkages to health centers. The goal of this innovation was to increase access to maternity and emergency obstetric care by allowing women to stay near a health center before delivery.

The study found that the improved MWH model was associated with several positive outcomes, including increased odds of facility delivery, MWH utilization, postnatal attendance, counseling for family planning, breastfeeding, and kangaroo care, as well as increased odds of caesarean section. No differences were observed in household expenditures for delivery.

Based on these findings, implementing improved MWHs near well-equipped rural health centers can be considered an innovation to improve access to maternal health. This innovation provides a supportive environment for pregnant women to stay near a health center before delivery, increasing the likelihood of facility-based childbirth and access to emergency obstetric care.
AI Innovations Description
The recommendation based on the study is to develop and implement improved Maternity Waiting Homes (MWHs) near well-equipped rural health centers (RHCs) in areas where substantial numbers of women live remotely. The improved MWH model should include infrastructure, policies, and linkages to health centers. The study found that the improved MWH model increased access to facility delivery, encouraged the use of facilities with emergency care capacity, and improved exposure to counseling services for family planning, breastfeeding, and kangaroo care. The MWHs should be culturally acceptable and have a formalized management structure responsible for daily operations. The study also suggests that community input and engagement are crucial in the design and implementation of MWHs.
AI Innovations Methodology
The study described in the provided text aimed to assess the impact of maternity waiting homes (MWHs) on facility-based childbirth and maternity care in Zambia. MWHs are designed to improve access to maternity and emergency obstetric care by allowing women to stay near a health center before delivery. The improved MWH model included infrastructure, policies, and linkages to health centers.

The methodology used in the study was a quasi-experimental design. Here is a brief overview of the methodology:

1. Study Setting: The study was conducted in 40 primarily rural health centers in different districts of Zambia.

2. Study Design: A cluster design was used, with each cluster consisting of a rural health center and its catchment area households. The clusters were assigned to either the intervention group (received the improved MWH model) or the control group (implemented standard of care).

3. Randomization: Half of the clusters were randomly assigned to the study arms using a matched-pair randomization procedure. The other half were non-randomly assigned due to political considerations.

4. Data Collection: Cross-sectional random samples of women in villages located 10+ kilometers from their health centers were interviewed at baseline (March 2016) and endline (October 2018). The interviews collected information on facility delivery, postnatal care utilization, counseling, services received, expenditures, and other relevant factors.

5. Data Analysis: Intention-to-treat analysis was conducted, and generalized estimating equations (GEE) were used to estimate odds ratios (ORs) for the outcomes. The analysis compared the intervention group with the control group, taking into account baseline values and other covariates.

6. Sample Size: The target sample size for each round of data collection was 2400, providing 80% power to detect a 10-percentage point increase in facility delivery due to the intervention.

7. Ethical Considerations: Informed consent was obtained from participants, and data collection procedures were implemented consistently across the sites. Data privacy and confidentiality were ensured.

The results of the study showed that the improved MWH model was associated with increased odds of facility delivery, MWH utilization, postnatal attendance, counseling for family planning, breastfeeding, kangaroo care, and caesarean section. No differences were observed in household expenditures for delivery.

Overall, the study provides evidence that MWHs near well-equipped health centers can increase access to facility delivery, improve exposure to counseling, and encourage the use of facilities with emergency care capacity in areas where women live remotely.

Please note that this is a summary of the methodology described in the provided text. For a more detailed understanding, it is recommended to refer to the original study publication.

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