Abstract

rural, suburban, and urban areas that have varying access to physicians and hospitals. For example, Losina et al found that policies restricting total hip replacements to highvolume centers would differentially affect poor, lesseducated, and rural patients. Stratifying the analysis by population density, socioeconomic indicators, types of insurance carriers, and health care professional and facility density may be very valuable. The authors concede that there are limitations in using straight-line travel distances instead of travel time, but cite the 0.987 correlation found by Grumbach et al between travel distance and travel time in New York state. However, this correlative study excluded New York City and Long Island, which represent more than 8 million people, and may not be applicable to all of New York, New Jersey, and Florida. Technologies such as MapQuest can estimate travel time when origin and destination addresses are known. These travel times reflect the actual routes used, traffic flow patterns, and geography. Additionally, measuring the effects of excluding PO boxes and older patients who may reside in nursing homes rather than their listed home addresses may provide further insight.

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