Influence of hometown on family physicians' choice to practice in rural settings.

OBJECTIVE: This study examines the influence of a physician's hometown location on the choice of practice location, adjusting for confounding variables. METHODS: Medical school records for 2,487 Indiana University graduates (classes of 1988--1997) were matched to the American Medical Association's Masterfile data to identify the graduates' current practice locations and specialties. Urban influence codes were assigned to each county in Indiana for the purposes of defining metro or nonmetro locations. Physician practice locations were mapped using ArcGIS software. Chi-square tests, logistic regression, and analysis of variance were used to examine the influence of hometown on choice of practice location. RESULTS: Chi-square tests revealed significant associations between physician hometown and current practice location. Logistic regression, controlling for age and gender, predicted physicians (all specialties) from nonmetro hometowns were 4.7 times as likely to locate their practice in a nonmetro location as compared to their peers from metro hometowns. Similarly, family physicians from nonmetro hometowns were 4.4 times as likely to choose a nonmetro practice location. There was not a significant difference in the mean distance between hometown and practice location for physicians from nonmetro hometowns compared to those from metro hometowns. CONCLUSIONS: This study underscores the influence of physicians' hometown on their choice of practice location.

Estimating the economic impact of secondhand smoke on the health of a community.

PURPOSE: This study provides a model to estimate the health-related costs of secondhand smoke exposure at a community level. MODEL DEVELOPMENT: Costs of secondhand smoke-related mortality and morbidity were estimated using national attributable risk values for diseases that are causally related to secondhand smoke exposure for adults and children. Estimated costs included ambulatory care costs, hospital inpatient costs, and loss of life costs based on vital statistics, hospital discharge data, and census data. APPLICATION OF THE MODEL: The model was used to estimate health-related costs estimates of secondhand smoke exposure for Marion County, Indiana. Attributable risk values were applied to the number of deaths and hospital discharges to determine the number of individuals impacted by secondhand smoke exposure. RESULTS: The overall cost of health care and premature loss of life attributed to secondhand smoke for the study county was estimated to be $53.9 million in 2000-$10.5 million in health care costs and $20.3 million in loss of life for children compared with $6.2 million in health care costs and $16.9 million in loss of life for adults. This amounted to $62.68 per capita. CONCLUSIONS: This method may be replicated in other counties to provide data needed to educate the public and community leaders about the health effects and costs of secondhand smoke exposure.