Health facility readiness and facility-based birth in Haiti: a maximum likelihood approach to linking household and facility data

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 (bandwidth (h)=12.28, standard error (SE)=0.16) spread their readiness over larger areas than urban facilities (h=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*\