Use of a spatial scan statistic to identify clusters of births occurring outside Ghanaian health facilities for targeted intervention

Objective To identify and evaluate clusters of births that occurred outside health facilities in Ghana for targeted intervention. Methods A retrospective study was conducted using a convenience sample of live births registered in Ghanaian health facilities from January 1 to December 31, 2014. Data were extracted from the district health information system. A spatial scan statistic was used to investigate clusters of home births through a discrete Poisson probability model. Scanning with a circular spatial window was conducted only for clusters with high rates of such deliveries. The district was used as the geographic unit of analysis. The likelihood P value was estimated using Monte Carlo simulations. Results Ten statistically significant clusters with a high rate of home birth were identified. The relative risks ranged from 1.43 (“least likely” cluster; P = 0.001) to 1.95 (“most likely” cluster; P = 0.001). The relative risks of the top five “most likely” clusters ranged from 1.68 to 1.95; these clusters were located in Ashanti, Brong Ahafo, and the Western, Eastern, and Greater regions of Accra. Conclusion Health facility records, geospatial techniques, and geographic information systems provided locally relevant information to assist policy makers in delivering targeted interventions to small geographic areas.