Christopher G Kemp1, Reed Sorensen1, Nancy Puttkammer1, Reynold Grand'Pierre2, Jean Guy Honoré3, Lauren Lipira4, Christopher Adolph5,6. 1. Department of Global Health, University of Washington, Ninth and Jefferson Building, 13th Floor, Box 359932, 908 Jefferson Street, Seattle, WA 98104, USA. 2. Family Health Unit, Ministère de la Santé Publique et de la Population, Port-au-Prince, Haiti. 3. I-TECH Haiti, Delmas 95, Route de Jacquet #14, Pétion Ville, Haïti. 4. Department of Health Services, University of Washington, 1959 NE Pacific St, Box 357660 Seattle, WA 98195, USA. 5. Department of Political Science, University of Washington, 101 Gowen Hall, Box 353530. Seattle, WA 98195, USA. 6. Center for Statistics and the Social Sciences, University of Washington, Padelford Hall, Box 354320, Seattle, WA 98195, USA.
Abstract
BACKGROUND: Haiti has one of the world's highest maternal mortality ratios. Comprehensive obstetric services could prevent many of these deaths, though most births in Haiti occur outside health facilities. Demand-side factors like a mother's socioeconomic status are understood to affect her access or choice to deliver in a health facility. However, analyses of the role of supply-side factors like health facility readiness have been constrained by limited data and methodological challenges. We sought to address these challenges and determine whether Haiti could increase rates of facility-based birth by improving facility readiness to provide delivery services. METHODS: Our task was to characterize facility delivery readiness and link it to nearby births. We used birth data from the 2012 Haiti DHS and facility data from the 2013 Haiti SPA. Our outcome of interest was facility-based birth. Our predictor of interest was delivery readiness at the DHS sampling cluster level. We derived a novel likelihood function that used Kernel Density Estimation to estimate cluster-level readiness alongside the coefficients of a logistic regression. RESULTS: We analyzed data from 389 facilities and 1,991 births. Rural facilities were less ready than urban facilities to provide delivery services. Women delivering in health facilities were younger, more educated, wealthier, less likely to live in rural areas, and had fewer previous children. Our model estimated that rural facilities (σ = 12.28, standard error [SE] = 0.16) spread their readiness over larger areas than urban facilities (σ = 7.14, SE = 0.016). Cluster-level readiness was strongly associated with facility-based birth (adjusted log-odds = 0.031; p = 0.005), as was socioeconomic status (adjusted log-odds = 0.78; p < 0.001). CONCLUSIONS: Health system policymakers in Haiti could increase rates of facility-based birth by supporting targeted interventions to improve facility readiness to provide delivery-related services, alongside efforts to reduce poverty and increase educational attainment among women.
BACKGROUND: Haiti has one of the world's highest maternal mortality ratios. Comprehensive obstetric services could prevent many of these deaths, though most births in Haiti occur outside health facilities. Demand-side factors like a mother's socioeconomic status are understood to affect her access or choice to deliver in a health facility. However, analyses of the role of supply-side factors like health facility readiness have been constrained by limited data and methodological challenges. We sought to address these challenges and determine whether Haiti could increase rates of facility-based birth by improving facility readiness to provide delivery services. METHODS: Our task was to characterize facility delivery readiness and link it to nearby births. We used birth data from the 2012 Haiti DHS and facility data from the 2013 Haiti SPA. Our outcome of interest was facility-based birth. Our predictor of interest was delivery readiness at the DHS sampling cluster level. We derived a novel likelihood function that used Kernel Density Estimation to estimate cluster-level readiness alongside the coefficients of a logistic regression. RESULTS: We analyzed data from 389 facilities and 1,991 births. Rural facilities were less ready than urban facilities to provide delivery services. Women delivering in health facilities were younger, more educated, wealthier, less likely to live in rural areas, and had fewer previous children. Our model estimated that rural facilities (σ = 12.28, standard error [SE] = 0.16) spread their readiness over larger areas than urban facilities (σ = 7.14, SE = 0.016). Cluster-level readiness was strongly associated with facility-based birth (adjusted log-odds = 0.031; p = 0.005), as was socioeconomic status (adjusted log-odds = 0.78; p < 0.001). CONCLUSIONS: Health system policymakers in Haiti could increase rates of facility-based birth by supporting targeted interventions to improve facility readiness to provide delivery-related services, alongside efforts to reduce poverty and increase educational attainment among women.
Entities:
Keywords:
Haiti; kernel density estimation; maternal and child health; maximum likelihood; obstetric services; spatial analysis