Reproductive health voucher program and facility based delivery in informal settlements in Nairobi: A longitudinal analysis

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Study Justification:
– The study aimed to investigate the impact of a reproductive health voucher program on women’s access to facility-based delivery in informal settlements in Nairobi.
– The justification for the study was the high maternal mortality rate in Kenya and the need to reduce these rates by improving access to quality healthcare services for pregnant women.
Study Highlights:
– The study used population-based cohort data from two Nairobi slums where the voucher program was piloted.
– Mothers were divided into two groups: those who bought the voucher for their index child and had a facility-based delivery (Index-OBA mothers) and those who did not buy the voucher (non-OBA mothers).
– The study found that women who bought the voucher for their index child and had a facility-based delivery were more likely to deliver a subsequent child in a facility compared to those who did not buy vouchers.
– The study also found that the facility-based delivery of an index child had a persistent effect, as subsequent children of the same mother were more likely to be born in a facility as well.
Recommendations for Lay Reader and Policy Maker:
– The study recommends the need to improve access to facility-based delivery for all near poor women, not just those who purchased the voucher.
– The study highlights the importance of facility-based deliveries in improving maternal and child health outcomes.
– The study suggests that the reproductive health voucher program has improved access to facility-based delivery for poor women, but there is still room for improvement.
Key Role Players:
– Government agencies responsible for implementing and monitoring reproductive health programs.
– Healthcare facilities and providers involved in delivering maternal and child health services.
– Non-governmental organizations (NGOs) working in the field of reproductive health and women’s rights.
– Community leaders and organizations in informal settlements who can help raise awareness and advocate for improved access to facility-based delivery.
Cost Items for Planning Recommendations:
– Funding for the reproductive health voucher program, including the cost of vouchers and administrative expenses.
– Investment in healthcare infrastructure and facilities in informal settlements to ensure adequate capacity for facility-based deliveries.
– Training and capacity building for healthcare providers to deliver quality maternal and child health services.
– Community outreach and education programs to raise awareness about the importance of facility-based delivery and the availability of the voucher program.

The strength of evidence for this abstract is 7 out of 10.
The evidence in the abstract is moderately strong. The study used population-based cohort data from two Nairobi slums and analyzed the impact of a reproductive health voucher program on facility-based delivery. The adjusted odds-ratio of facility-based delivery for subsequent children was found to be higher for women who bought the voucher for their index child. However, the odds were smaller compared to women who did not buy the voucher. The study acknowledges the need to improve access to facility-based delivery for all women. To improve the strength of the evidence, the study could have included a larger sample size and conducted a randomized controlled trial to compare the outcomes between voucher recipients and non-recipients. Additionally, the study could have provided more details on the methodology and statistical analysis used.

Introduction: In Kenya, the maternal mortality rate had ranged from 328 to 501 deaths per 100,000 live births over the last three decades. To reduce these rates, the government launched in 2006 a means-tested reproductive health output-based approach (OBA) voucher program that covers costs of antenatal care, a facility-based delivery (FBD) and a postnatal visit in prequalified healthcare facilities. This paper investigated whether women who bought the voucher for their index child and had a FBD were more likely to deliver a subsequent child in a facility compared to those who did not buy vouchers. Methods and Findings: We used population-based cohort data from two Nairobi slums where the voucher program was piloted. We selected mothers of at least two children born between 2006 and 2012 and divided the mothers into two groups: Index-OBA mothers bought the voucher for the index child (N=352), and non-OBA mothers did not buy the voucher during the study period (N=514). The most complete model indicated that the adjusted odds-ratio of FBD of subsequent child when the index child was born in a facility was 3.89 (p<0.05) and 4.73 (p<0.01) in Group 2. Discussion and Conclusion: The study indicated that the voucher program improved poor women access to FBD. Furthermore, the FBD of an index child appeared to have a persistent effect, as a subsequent child of the same mother was more likely to be born in a facility as well. While women who purchased the voucher have higher odds of delivering their subsequent child in a facility, those odds were smaller than those of the women who did not buy the voucher. However, women who did not buy the voucher were less likely to deliver in a good healthcare facility, negating their possible benefit of facility-based deliveries. Pathways to improve access to FBD to all near poor women are needed. © 2013 Amendah et al.

This study data came from Korogocho and Viwandani, two informal settlements where the African Population and Health Research Center (APHRC) has been running the Nairobi Urban Health and Demographic Surveillance System (NUHDSS) since 2003. Each settlement covers about one kilometer square and is located within five to 10 kilometers from the city center. The NUHDSS records demographic events (births, deaths and migration) every four months and detailed household expenditures data once a year. The Viwandani informal settlement neighbors the Industrial Area of Nairobi and was a magnet for young males and relatively educated migrants in search of work while Korogocho was home for more settled families[12], some of whom had been living there for multiple generations. As a corollary of the different demographics in both settlements, households sizes were bigger in Korogocho than Viwandani while household income per capita was higher in Viwandani [13]. As of end of 2011, the latest data available showed that 32,746 households with 83,484 individuals lived in the area covered by the NUHDSS. This surveillance system provided vital statistics and other information on a population for whom these data would otherwise be unavailable. Nested within NUHDSS was the Maternal and Child Health (MCH) project, which recruited cohorts of mother-child pairs and followed them up every four months. A mother-child pair was recruited if the mother resided in the slum when pregnant and the child was 6 months old or younger at the time of recruitment. The MCH study covered the years 2006 to 2010 with a couple of recruitment suspensions between June and September 2009 and February to June 2010. During recruitment suspensions, follow-up interviews of existing cohorts were conducted. The INDEPTH (International Network for the Demographic Evaluation of Populations and Their Health) vaccination project (IVP) succeeded the MCH project from 2011 and took over existing cohorts of children while recruiting all children born from 2010 when recruitment into the MCH project ended. That strategy allowed for continuity in the recruitment and follow-up of children born in the slums since 2006 in the ongoing cohort studies. Both MCH and IVP projects were run by the same institution and team using the similar procedures and questionnaires so that the data quality was similar across all the rounds of data collections. The MCH/IVP projects collected information on the child’s place of delivery during the recruitment interview but the information on RH-OBA knowledge and use was collected at the second interview. Hence, information on the RH-OBA voucher was unavailable for mothers who dropped out of the MCH/IVP projects after the first recruitment interview, 22% in the MCH project and 27% in the INDEPTH Vaccination Project. This study included mother-children pairs from the MCH and the IVP datasets from 2006 to 2012. We selected mothers of at least two children, and for whom no important information—like the date of birth of the child or the mother—was missing or implausible. For twin births, we kept only one record knowing the mother’s information was the same and assuming both children were born in the same place. Since this paper focused on longitudinal effect of the voucher, we excluded women who did not buy the voucher for the index child but for the subsequent child. The APHRC owns the datasets used in this analysis. APHRC has a data sharing policy that enables other researchers to access this dataset and others. APHRC data sharing policy is available at http://www.aphrc.org/insidepage/page.php?app=data

The study mentioned in the description focuses on the reproductive health voucher program and facility-based delivery in informal settlements in Nairobi. The program was launched in 2006 to reduce maternal mortality rates in Kenya. The study found that women who purchased the voucher for their index child and had a facility-based delivery were more likely to deliver subsequent children in a facility compared to those who did not buy vouchers.

The data for the study came from the Nairobi Urban Health and Demographic Surveillance System (NUHDSS), which records demographic events and household expenditures in informal settlements. The study used cohorts of mother-child pairs recruited from the slums and followed them up every four months. The Maternal and Child Health (MCH) project and the International Network for the Demographic Evaluation of Populations and Their Health (INDEPTH) vaccination project collected data on the child’s place of delivery and the knowledge and use of the reproductive health voucher.

The study included mothers of at least two children, and only those for whom no important information was missing or implausible. Twin births were represented by one record assuming both children were born in the same place. Women who did not buy the voucher for the index child but for subsequent children were excluded from the analysis.

The datasets used in the analysis are owned by the African Population and Health Research Center (APHRC), which has a data sharing policy that allows other researchers to access the dataset.
AI Innovations Description
The recommendation from the study to improve access to maternal health is the implementation of a reproductive health voucher program. This program would provide means-tested vouchers to cover the costs of antenatal care, facility-based delivery, and postnatal visits in prequalified healthcare facilities. The study found that women who purchased the voucher for their index child and had a facility-based delivery were more likely to deliver subsequent children in a facility compared to those who did not buy vouchers.

The study data was collected from two informal settlements in Nairobi, Kenya, where the African Population and Health Research Center (APHRC) has been running the Nairobi Urban Health and Demographic Surveillance System (NUHDSS) since 2003. The NUHDSS records demographic events and household expenditures data, providing vital statistics and information on a population for whom these data would otherwise be unavailable.

The reproductive health voucher program would aim to improve access to facility-based deliveries for all near-poor women, as the study found that women who did not buy the voucher were less likely to deliver in a good healthcare facility. The implementation of this program could help reduce maternal mortality rates in Kenya and improve overall maternal health outcomes.
AI Innovations Methodology
Based on the provided information, one potential innovation to improve access to maternal health is the implementation of a reproductive health voucher program. This program would provide means-tested vouchers to pregnant women, covering the costs of antenatal care, facility-based delivery, and postnatal visits in prequalified healthcare facilities. This approach aims to reduce financial barriers and increase access to essential maternal health services for women in low-income settings.

To simulate the impact of this recommendation on improving access to maternal health, a longitudinal analysis methodology can be used. Here is a brief description of the methodology:

1. Data Collection: Collect population-based cohort data from the target population, including information on maternal health outcomes, voucher program participation, and other relevant factors. This data can be obtained through existing surveillance systems or by conducting surveys and interviews.

2. Selection of Study Participants: Identify mothers who have had at least two children between a specified time period and divide them into two groups: those who bought the voucher for their index child (Index-OBA mothers) and those who did not buy the voucher (non-OBA mothers).

3. Data Analysis: Analyze the collected data using appropriate statistical methods. Compare the outcomes and access to facility-based delivery (FBD) between the two groups of mothers. Calculate adjusted odds ratios to determine the association between voucher program participation and FBD for subsequent children.

4. Interpretation of Findings: Interpret the results of the analysis to understand the impact of the voucher program on improving access to maternal health. Assess the effectiveness of the program in increasing the likelihood of delivering subsequent children in a healthcare facility.

5. Discussion and Conclusion: Discuss the implications of the findings and draw conclusions about the effectiveness of the voucher program in improving access to maternal health. Identify any limitations of the study and suggest potential pathways for further improvement in access to facility-based delivery for all women in need.

It is important to note that this methodology is based on the specific study described in the provided information. If you are looking to simulate the impact of a different recommendation or innovation, the methodology may need to be adjusted accordingly.

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