Understanding the Clustering Patterns in Physician Distribution Through Affinity Propagation

The spatial distribution of physicians has a significant impact in public health research. It is critical to clarify whether the addresses provided by the physicians are the home addresses or the practice addresses, since the practice address is the key to understand relevant issues of maldistribution, accessibility and disparity. Through a pilot study as partial effort of the research project "Reducing Physician Distribution Uncertainty in Spatial Accessibility Research" sponsored by the National Institutes of Health (NIH award number 1R21CA182874-01), appropriate solutions were developed to differentiate the home addresses from practice addresses. This paper introduces how to understand the clustering patterns in physician distribution through Affinity Propagation, a relatively new clustering algorithm, to derive the potential extent of the practice locations for those physicians who provided home addresses. The physician data is derived from the 2014 American Medical Association (AMA) Physician Masterfile, while two counties (Fulton and DeKalb) in the metropolitan area of Atlanta, Georgia were selected as the study area. Both Euclidian distance and driving distance were applied in the AP algorithm, while gravity models based AP calculation were applied in comparison to the clustering of individual physicians. By justifying preference and similarity parameters in the AP calculation, hierarchical clustering patterns can be derived and perceived. Future research challenges in AP clustering are identified, while this pilot study can be extended with broader impact in public health research.