Optimising the location of antenatal classes.

Objectives: To combine microsimulation and location-allocation techniques to determine antenatal class locations which minimise the distance travelled from home by potential users.

Design: Microsimulation modeling and location-allocation modeling.

Setting: City of Leeds, UK.

Participants: Potential users of antenatal classes.

Methods: An individual-level microsimulation model was built to estimate the number of births for small areas by combining data from the UK Census 2001 and the Health Survey for England 2006. Using this model as a proxy for service demand, we then used a location-allocation model to optimize locations.

Findings: Different scenarios show the advantage of combining these methods to optimize (re)locating antenatal classes and therefore reduce inequalities in accessing services for pregnant women.

Key Conclusions: Use of these techniques should lead to better use of resources by allowing planners to identify optimal locations of antenatal classes which minimise women's travel.

Implications For Practice: These results are especially important for health-care planners tasked with the difficult issue of targeting scarce resources in a cost-efficient, but also effective or accessible, manner. (169 words).