Impact of newly constructed primary healthcare centres on antenatal care attendance, facility delivery and all-cause mortality: Quasi-experimental evidence from Taabo health and demographic surveillance system, Côte d’Ivoire

BMJ Open, Volume 12, No. 1, Year 2022

Interpretation

Objectives Access to quality care remains limited, particularly in low-income and middle-income countries. Although better health outcomes for families living in close proximity to healthcare facilities have been documented in cross-sectional studies, evidence on the extent to which additional health facilities can contribute to improved population health remains scanty. We aimed to estimate the causal impact of newly constructed primary healthcare facilities within a health and demographic surveillance (HDSS) site in Côte d’Ivoire. Design We conducted a quasi-experimental study. Logistic and Cox proportional hazards regression models were used to estimate the impact of new healthcare facilities on healthcare-seeking behaviour and all-cause mortality. Setting Data were collected prospectively through the Taabo HDSS located in south-central Côte d’Ivoire between 2010 and 2018. Participants We analysed 2957 deaths across 440 973 person-year observations as well as 14 132 live births. Primary outcome measures The primary outcomes were antenatal care (ANC) attendance, facility delivery and mortality. Logistic and Cox proportional hazards models were employed to estimate the impact of the new health facilities on ANC attendance, facility delivery and child as well as adult mortality. Results Average distance to the nearest healthcare facility declined from 5.5 km before to 2.8 km after opening of four new healthcare facilities in targeted villages. No improvement was observed for ANC attendance, institutional deliveries and adult mortality. New facilities reduced the risk of post-neonatal infant mortality by 46% (HR 0.54, 95% CI 0.31 to 0.94, p<0.05), suggesting a mortality gradient of 2 deaths per 1000 for each additional km (Coef=0.002, 95% CI 0.000 to 0.004, p<0.05). Conclusions Our results suggest that new facilities do not necessarily improve healthcare utilisation and health outcomes. Further research is needed to identify the best ways to ensure access to quality care in resource-constrained settings. We followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) cross-sectional reporting guidelines23 throughout the manuscript. A quasi-experimental study was conducted to assess the impact of new healthcare facilities on treatment seeking and mortality outcomes. At the beginning of the study 7 out of 13 villages had their own health centre. In 2010, a local committee decided to build four additional health centres. To assess the causal impact of these new facilities, we compared village-level changes in child mortality before and after opening of new facilities to the changes observed in communities with constant health facility access over the same period. All empirical models included village and year fixed effects (intercepts) to rule out confounding by time-invariant unobserved characteristics. This study was conducted in the Taabo HDSS. The Taabo HDSS is located in the south-central part of Côte d’Ivoire and covers a surface area of approximately 980 km2. The area is mainly rural and comprises 13 villages as well as an urban settlement (Taabo-Cité) (figure 1). The primary economic activity of the region is agriculture, dominated by cocoa and rubber but also featuring subsistence crops such as cassavas, plantains, vegetables and yams. Map of the Taabo health and demographic surveillance system in south-central Côte d’Ivoire. Under-5 mortality was 94 per 1000 children born alive in 2010.24 The primary causes of death in the area are malaria (18.0%), acute respiratory infections (15.4%), HIV/AIDS (11.2%) and pulmonary tuberculosis (6.5%). Non-communicable diseases (NCDs) represented 18.9% of deaths, mainly due to acute abdomen (5.3%), while unspecified cardiac diseases, digestive neoplasm and severe malnutrition accounted for less than 3% each. Maternal and neonatal conditions accounted for 8.3% of all deaths.25 All women of reproductive age whose pregnancy started and ended between January 2010 and December 2018 and all deaths registered during this 9-year period were included in the analysis. Each household of the Taabo HDSS was visited three times per year for detailed registration of births, deaths, in-migrations, out-migrations and pregnancies. New pregnancies were followed-up longitudinally and all women with a new pregnancy were interviewed using a specific pregnancy questionnaire. This questionnaire includes the date of last menstrual period and pregnancy outcome; hence, facilitating enumerators to be aware of neonatal deaths. Key informants in communities continuously observed and reported any death occurring in the surveillance zone. More detailed information on routine monitoring activities have been described elsewhere.24 All individuals registered and living in the Taabo HDSS between 2010 and 2018 were included in the study. As mentioned above, only 7 of the 13 villages had their own health facilities in 2010. These PHC centres were supported by a 12-bed hospital in Taabo-Cité. In 2010, Fairmed, a non-governmental organisation, launched activities to reduce mortality and morbidity due to malaria and neglected tropical diseases. During the initial engagement of stakeholders, distance to facilities was highlighted by community members as the primary health system constraint, and construction of new health centres in the area was requested. Based on population size and access to facilities in 2010, four out of the six villages without health centres in 2010 were selected for new primary care health facilities. These facilities were designed to run by a nurse or midwife and included a dispensary, a small maternity ward and a pharmacy. Primary care facilities were supposed to offer the local population a minimum package of essential health services including routine immunisation of children, curative care for common ailments, prenatal and postnatal consultations, and family planning, deliveries assistance, prevention of mother-to-child transmission of HIV, as well as the promotion of essential family practices with the support of community relays. The first new health centre was opened in Tokohiri in May 2013. In January 2015, a new health centre started its operations in Taabo-Village. Finally, in January and February 2017, new health centres were opened in Ahouaty and N’Denou. Figure 1 illustrates the location of these new health facilities, while figure 2 illustrates the timeline of the project. Health facility coverage in the Taabo HDSS from 2010 to 2018. HDSS, health and demographic surveillance. The primary outcome variables were ANC attendance, facility delivery and all-cause mortality. ANC attendance was a binary variable taking value 0 if the woman had not made any prenatal consultation and value 1 if she made at least one prenatal consultation. Facility delivery was a binary value with 0 for all deliveries outside a health facility and value 1 for all deliveries at a health facility (health centre or hospital). We defined four age-specific mortality variables for children: (1) neonatal mortality (ie, the probability of dying within the first 30 days of life); (2) postneonatal infant mortality (ie, the probability of dying between days 30 and 364 of life); (3) infant mortality (ie, the probability of dying before the first birthday) and (4) child mortality (ie, the probability of dying between the first and fifth birthdays).26 For adults, we analysed mortality by age groups: 18–39, 40–59, 60–79 and ≥80 years. To minimise the risk of confounding through other factors that may have changed over time, we controlled for age and sex of child, twin status, child year of birth and mother and household characteristics (maternal age, religion, education, marital status, number of previous pregnancies and household socioeconomic status) in all child mortality models. Health facility delivery and ANC attendance were adjusted only for mother and household characteristics (maternal age, religion, education, marital status, number of previous pregnancies and household socioeconomic status). We used principal component analysis of household assets to divide households into wealth quintile (ie, poorest, poor, medium, rich and richest).27 The primary exposure variable of interest was the availability of a health facility in the village of residence during the exposure period. For the four period-specific mortality variables (ie, neonatal, postneonatal, infant and child mortality), local facility availability was coded as 1 if the facility was operational in the month of birth. For ANC attendance and facility delivery, local facility availability was coded as 1 if the facility was operational when the pregnancy started. Data collected during this study were cross-checked and managed using a household registration system implemented in Windev V.12.0 (PC Soft; Montpellier, France). We also computed distance to the nearest facility for all households using the Statageodist package.28 We then displayed minimum, average and maximum for distance before and after the health centre was operational in each village. Descriptive statistics of the study sample included means, minimum and maximum of quantitative variables and frequencies (%) of categorical variables. We used Cox proportional hazards model to estimate impacts on mortality. We also used instrumental variable regression models to estimate the impact of distance on child survival, using the local facility availability as predictors of household distance. In a sensitivity analysis, we employed linear probability models to ensure the robustness of the postneonatal mortality outcomes with respect to the empirical model. We used multivariate logistic regression with clustering at village and year level to investigate the relationship between ANC attendance, health facility delivery and local health centre availability. All models included child and mother characteristics as well as village and year fixed effects (intercepts) to rule out confounding by time-invariant unobserved characteristics. Standard errors were corrected to allow for residual correlation both at the household and community level using Huber’s cluster-robust variance estimator.29 All statistical analyses were performed in Stata V.15.0 (StataCorp). Patients were not involved in the design and implementation of this study.

AI Digest

Study Justification:

– Access to quality healthcare is limited, especially in low-income and middle-income countries.
– Previous studies have shown that proximity to healthcare facilities improves health outcomes for families.
– However, there is limited evidence on how the construction of new healthcare facilities can contribute to improved population health.
– This study aims to estimate the impact of newly constructed primary healthcare facilities on healthcare-seeking behavior and all-cause mortality in Côte d’Ivoire.

Highlights:

– The study used a quasi-experimental design to assess the causal impact of new healthcare facilities.
– Data was collected prospectively through the Taabo health and demographic surveillance system between 2010 and 2018.
– The study analyzed 2957 deaths and 14,132 live births.
– The primary outcomes measured were antenatal care attendance, facility delivery, and mortality.
– The average distance to the nearest healthcare facility decreased from 5.5 km to 2.8 km after the opening of four new facilities.
– No improvement was observed in antenatal care attendance, institutional deliveries, and adult mortality.
– However, the new facilities reduced the risk of post-neonatal infant mortality by 46%.

Recommendations:

– The study suggests that the construction of new healthcare facilities does not necessarily improve healthcare utilization and health outcomes.
– Further research is needed to identify effective ways to ensure access to quality care in resource-constrained settings.

Key Role Players:

– Local committee: Responsible for decision-making and overseeing the construction of new healthcare facilities.
– Non-governmental organization (Fairmed): Involved in reducing mortality and morbidity due to malaria and neglected tropical diseases.
– Nurses and midwives: Responsible for running the new primary care health facilities.
– Community relays: Provide support in promoting essential family practices and disseminating health information.

Cost Items for Planning Recommendations:

– Construction costs: Budget for building new healthcare facilities, including the dispensary, maternity ward, and pharmacy.
– Staffing costs: Budget for hiring and training nurses and midwives to run the facilities.
– Equipment and supplies: Budget for purchasing medical equipment and supplies needed for providing essential health services.
– Operational costs: Budget for ongoing operational expenses, such as utilities, maintenance, and administrative costs.
– Training and capacity building: Budget for training healthcare staff and community relays to ensure effective service delivery and health promotion.
Please note that the above cost items are estimates and not actual costs. The actual budget will depend on various factors such as local context, facility size, and specific requirements.

Strength of Evidence

The strength of evidence for this abstract is 7 out of 10.
The evidence in the abstract is based on a quasi-experimental study design, which provides moderate strength of evidence. The study used regression models to estimate the impact of new healthcare facilities on healthcare-seeking behavior and mortality outcomes. The study included a large sample size and controlled for confounding variables. However, the study did not find improvements in antenatal care attendance, facility delivery, and adult mortality. To improve the strength of evidence, future studies could consider using a randomized controlled trial design and include a control group to compare the outcomes more rigorously.

Abstract

We followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) cross-sectional reporting guidelines23 throughout the manuscript. A quasi-experimental study was conducted to assess the impact of new healthcare facilities on treatment seeking and mortality outcomes. At the beginning of the study 7 out of 13 villages had their own health centre. In 2010, a local committee decided to build four additional health centres. To assess the causal impact of these new facilities, we compared village-level changes in child mortality before and after opening of new facilities to the changes observed in communities with constant health facility access over the same period. All empirical models included village and year fixed effects (intercepts) to rule out confounding by time-invariant unobserved characteristics. This study was conducted in the Taabo HDSS. The Taabo HDSS is located in the south-central part of Côte d’Ivoire and covers a surface area of approximately 980 km2. The area is mainly rural and comprises 13 villages as well as an urban settlement (Taabo-Cité) (figure 1). The primary economic activity of the region is agriculture, dominated by cocoa and rubber but also featuring subsistence crops such as cassavas, plantains, vegetables and yams. Map of the Taabo health and demographic surveillance system in south-central Côte d’Ivoire. Under-5 mortality was 94 per 1000 children born alive in 2010.24 The primary causes of death in the area are malaria (18.0%), acute respiratory infections (15.4%), HIV/AIDS (11.2%) and pulmonary tuberculosis (6.5%). Non-communicable diseases (NCDs) represented 18.9% of deaths, mainly due to acute abdomen (5.3%), while unspecified cardiac diseases, digestive neoplasm and severe malnutrition accounted for less than 3% each. Maternal and neonatal conditions accounted for 8.3% of all deaths.25 All women of reproductive age whose pregnancy started and ended between January 2010 and December 2018 and all deaths registered during this 9-year period were included in the analysis. Each household of the Taabo HDSS was visited three times per year for detailed registration of births, deaths, in-migrations, out-migrations and pregnancies. New pregnancies were followed-up longitudinally and all women with a new pregnancy were interviewed using a specific pregnancy questionnaire. This questionnaire includes the date of last menstrual period and pregnancy outcome; hence, facilitating enumerators to be aware of neonatal deaths. Key informants in communities continuously observed and reported any death occurring in the surveillance zone. More detailed information on routine monitoring activities have been described elsewhere.24 All individuals registered and living in the Taabo HDSS between 2010 and 2018 were included in the study. As mentioned above, only 7 of the 13 villages had their own health facilities in 2010. These PHC centres were supported by a 12-bed hospital in Taabo-Cité. In 2010, Fairmed, a non-governmental organisation, launched activities to reduce mortality and morbidity due to malaria and neglected tropical diseases. During the initial engagement of stakeholders, distance to facilities was highlighted by community members as the primary health system constraint, and construction of new health centres in the area was requested. Based on population size and access to facilities in 2010, four out of the six villages without health centres in 2010 were selected for new primary care health facilities. These facilities were designed to run by a nurse or midwife and included a dispensary, a small maternity ward and a pharmacy. Primary care facilities were supposed to offer the local population a minimum package of essential health services including routine immunisation of children, curative care for common ailments, prenatal and postnatal consultations, and family planning, deliveries assistance, prevention of mother-to-child transmission of HIV, as well as the promotion of essential family practices with the support of community relays. The first new health centre was opened in Tokohiri in May 2013. In January 2015, a new health centre started its operations in Taabo-Village. Finally, in January and February 2017, new health centres were opened in Ahouaty and N’Denou. Figure 1 illustrates the location of these new health facilities, while figure 2 illustrates the timeline of the project. Health facility coverage in the Taabo HDSS from 2010 to 2018. HDSS, health and demographic surveillance. The primary outcome variables were ANC attendance, facility delivery and all-cause mortality. ANC attendance was a binary variable taking value 0 if the woman had not made any prenatal consultation and value 1 if she made at least one prenatal consultation. Facility delivery was a binary value with 0 for all deliveries outside a health facility and value 1 for all deliveries at a health facility (health centre or hospital). We defined four age-specific mortality variables for children: (1) neonatal mortality (ie, the probability of dying within the first 30 days of life); (2) postneonatal infant mortality (ie, the probability of dying between days 30 and 364 of life); (3) infant mortality (ie, the probability of dying before the first birthday) and (4) child mortality (ie, the probability of dying between the first and fifth birthdays).26 For adults, we analysed mortality by age groups: 18–39, 40–59, 60–79 and ≥80 years. To minimise the risk of confounding through other factors that may have changed over time, we controlled for age and sex of child, twin status, child year of birth and mother and household characteristics (maternal age, religion, education, marital status, number of previous pregnancies and household socioeconomic status) in all child mortality models. Health facility delivery and ANC attendance were adjusted only for mother and household characteristics (maternal age, religion, education, marital status, number of previous pregnancies and household socioeconomic status). We used principal component analysis of household assets to divide households into wealth quintile (ie, poorest, poor, medium, rich and richest).27 The primary exposure variable of interest was the availability of a health facility in the village of residence during the exposure period. For the four period-specific mortality variables (ie, neonatal, postneonatal, infant and child mortality), local facility availability was coded as 1 if the facility was operational in the month of birth. For ANC attendance and facility delivery, local facility availability was coded as 1 if the facility was operational when the pregnancy started. Data collected during this study were cross-checked and managed using a household registration system implemented in Windev V.12.0 (PC Soft; Montpellier, France). We also computed distance to the nearest facility for all households using the Statageodist package.28 We then displayed minimum, average and maximum for distance before and after the health centre was operational in each village. Descriptive statistics of the study sample included means, minimum and maximum of quantitative variables and frequencies (%) of categorical variables. We used Cox proportional hazards model to estimate impacts on mortality. We also used instrumental variable regression models to estimate the impact of distance on child survival, using the local facility availability as predictors of household distance. In a sensitivity analysis, we employed linear probability models to ensure the robustness of the postneonatal mortality outcomes with respect to the empirical model. We used multivariate logistic regression with clustering at village and year level to investigate the relationship between ANC attendance, health facility delivery and local health centre availability. All models included child and mother characteristics as well as village and year fixed effects (intercepts) to rule out confounding by time-invariant unobserved characteristics. Standard errors were corrected to allow for residual correlation both at the household and community level using Huber’s cluster-robust variance estimator.29 All statistical analyses were performed in Stata V.15.0 (StataCorp). Patients were not involved in the design and implementation of this study.

Materials

Innovations

Based on the provided description, the study conducted a quasi-experimental analysis to assess the impact of newly constructed primary healthcare facilities on healthcare-seeking behavior and mortality outcomes related to maternal health in Côte d’Ivoire. The study found that the construction of new healthcare facilities did not necessarily improve healthcare utilization and health outcomes. However, it did reduce the risk of post-neonatal infant mortality by 46%. Here are some potential recommendations for innovations to improve access to maternal health based on the findings:

1. Strengthening existing healthcare facilities: Instead of constructing new facilities, focus on improving the quality and capacity of existing healthcare facilities to provide comprehensive maternal health services.

2. Mobile healthcare units: Implement mobile healthcare units equipped with necessary medical equipment and staffed by healthcare professionals to reach remote areas and provide antenatal care, facility delivery, and postnatal care.

3. Telemedicine and teleconsultation: Utilize telemedicine and teleconsultation services to provide remote access to healthcare professionals for prenatal consultations, advice, and monitoring, especially in areas with limited healthcare facilities.

4. Community health workers: Train and deploy community health workers who can provide basic maternal health services, educate and raise awareness about maternal health, and facilitate referrals to healthcare facilities when necessary.

5. Transportation support: Improve transportation infrastructure and provide transportation support, such as ambulances or transportation vouchers, to ensure pregnant women can access healthcare facilities for antenatal care, delivery, and emergency obstetric care.

6. Maternal health education and awareness campaigns: Conduct targeted education and awareness campaigns to inform women and their families about the importance of antenatal care, facility delivery, and postnatal care, and address any misconceptions or cultural barriers.

7. Financial incentives: Implement financial incentives, such as conditional cash transfers or subsidies, to encourage pregnant women to seek antenatal care and deliver in healthcare facilities.

8. Public-private partnerships: Foster collaborations between the government, private sector, and non-governmental organizations to improve access to maternal health services, leverage resources, and address gaps in healthcare infrastructure and services.

9. Integration of maternal health services: Integrate maternal health services with other healthcare programs, such as family planning, immunization, and HIV prevention, to provide comprehensive care and improve overall health outcomes for women and children.

10. Continuous monitoring and evaluation: Establish a robust monitoring and evaluation system to track the impact of interventions, identify areas for improvement, and ensure the delivery of quality maternal health services.

It is important to note that these recommendations are based on the findings of the specific study mentioned and may need to be adapted to the local context and resources available in different settings.

AI Innovations Description

The study titled “Impact of newly constructed primary healthcare centres on antenatal care attendance, facility delivery and all-cause mortality: Quasi-experimental evidence from Taabo health and demographic surveillance system, Côte d’Ivoire” aimed to assess the causal impact of newly constructed primary healthcare facilities on healthcare-seeking behavior and health outcomes in Côte d’Ivoire.

The study used a quasi-experimental design and collected data from the Taabo health and demographic surveillance system between 2010 and 2018. The primary outcomes measured were antenatal care (ANC) attendance, facility delivery, and mortality.

The results of the study showed that the average distance to the nearest healthcare facility decreased from 5.5 km to 2.8 km after the opening of four new healthcare facilities in targeted villages. However, there was no improvement observed in ANC attendance, institutional deliveries, and adult mortality. On the other hand, the new facilities reduced the risk of post-neonatal infant mortality by 46%.

Based on these findings, the study suggests that the construction of new healthcare facilities does not necessarily improve healthcare utilization and health outcomes. Further research is needed to identify the best ways to ensure access to quality care in resource-constrained settings.

In summary, the recommendation to improve access to maternal health based on this study would be to focus on strategies beyond the construction of new healthcare facilities. This could include interventions to address barriers to ANC attendance and facility delivery, such as improving transportation infrastructure, increasing awareness and education about the importance of maternal health services, and strengthening the quality of care provided at existing healthcare facilities.

AI Innovations Methodology

The study you provided focuses on the impact of newly constructed primary healthcare centers on access to maternal health in Côte d’Ivoire. The study used a quasi-experimental design to assess the causal impact of these new facilities on healthcare-seeking behavior and all-cause mortality.

To simulate the impact of recommendations on improving access to maternal health, a methodology similar to the one used in the study can be employed. Here is a brief description of the methodology:

1. Identify the recommendations: Start by identifying specific recommendations that can improve access to maternal health. These recommendations can include measures to reduce distance to healthcare facilities, enhance healthcare infrastructure, improve healthcare services, increase community awareness, and promote maternal health education.

2. Define the study population: Determine the target population for the simulation. This can include pregnant women, women of reproductive age, and healthcare providers involved in maternal health.

3. Select study sites: Choose specific locations or communities where the simulation will take place. Consider areas with limited access to maternal health services or areas with high maternal mortality rates.

4. Baseline data collection: Collect baseline data on the current status of access to maternal health in the selected study sites. This can include information on healthcare facilities, distance to facilities, utilization of antenatal care, facility delivery rates, and maternal mortality rates.

5. Implement the recommendations: Introduce the recommended interventions or innovations to improve access to maternal health in the study sites. This can involve constructing new healthcare facilities, improving existing facilities, training healthcare providers, implementing community awareness campaigns, and providing maternal health education.

6. Data collection after implementation: Collect data on the impact of the implemented recommendations. This can include information on changes in healthcare-seeking behavior, utilization of antenatal care, facility delivery rates, and maternal mortality rates.

7. Data analysis: Analyze the collected data using appropriate statistical methods. This can involve comparing pre- and post-intervention data to assess the impact of the recommendations on improving access to maternal health. Regression models, such as logistic and Cox proportional hazards regression models, can be used to estimate the causal impact of the recommendations.

8. Interpretation of results: Interpret the results of the analysis to understand the effectiveness of the recommendations in improving access to maternal health. Assess whether the implemented interventions have led to positive changes in healthcare-seeking behavior, utilization of antenatal care, facility delivery rates, and maternal mortality rates.

9. Further research and refinement: Based on the results, identify areas for further research and refinement of the recommendations. This can involve exploring additional interventions, adjusting existing interventions, or addressing any limitations identified during the simulation.

By following this methodology, it is possible to simulate the impact of recommendations on improving access to maternal health and assess their effectiveness in a specific context.

Author

Dima Health

Statistics:

Citations: 1

Identifiers:

DOI: 10.1136/bmjopen-2021-054355

Research Areas:

Cancer, Community Interventions, Food Security, Health System and Policy, Infectious Diseases, Maternal Access, Maternal and Child Health, Noncommunicable Diseases, Quality of Care, Sexual and Reproductive Health, Social Determinants

Study Countries:

Ivory Coast

Study Design:

Cross Sectional Study, Quasi Experimental Study

Study Approach:

Quantitative

Participants Gender:

Female