Access to cardiac interventional services in Alabama and Mississippi: a geographical information system analysis.
OBJECTIVE
The objective of this study was to determine the contribution of distance to hospitals with cardiac interventional services (CIS) to county age-adjusted myocardial infarction (MI) mortality rates (CAMR) in Alabama and Mississippi counties.


METHODS
THE STUDY USED THREE DATA SOURCES: U.S. Census data, Centers for Disease Control and Prevention (CDC) mortality data, and American Hospital Association data. A geographical information system (GIS) was used to measure distance, providing an empirical measure of county access to CIS. Multiple regression analysis was conducted using measures of distance to CIS, county rural status, state, sex, poverty, education, race, and interaction as predictors of CAMR.


RESULTS
Regression results indicate that the model significantly predicts CAMR, R(2) = .378, adjusted R(2) = .319, F = 6.321, p < .001. The model accounts for 31.9 percent of the variability.


CONCLUSIONS
The results of this study do not lead to the conclusion that cardiac outcomes as measured by CAMR were sensitive to the geographic location of CIS. However, statistically significant interactions supported the sensitivity of CAMR to complex patterns and issues of rural status, poverty, education, and race.
Graves
Barbara Ann
BA
Capstone College of Nursing, The University of Alabama, Tuscaloosa, AL, USA.
D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000407:Alabama / Q000453:epidemiology; D005260:Female; D040362:Geographic Information Systems; D006297:Health Services Accessibility / Q000706:statistics & numerical data*; D006304:Health Status; D006333:Heart Failure / Q000401:mortality* / Q000628:therapy; D006801:Humans; D008297:Male; D008875:Middle Aged; D008922:Mississippi / Q000453:epidemiology; D009203:Myocardial Infarction / Q000401:mortality* / Q000628:therapy; D010342:Patient Acceptance of Health Care / Q000706:statistics & numerical data; D010351:Patient Discharge / Q000706:statistics & numerical data; D012044:Regression Analysis; D012111:Residence Characteristics; D018570:Risk Assessment; D012307:Risk Factors; D012424:Rural Population / Q000706:statistics & numerical data*; D012720:Severity of Illness Index; D012959:Socioeconomic Factors; D014505:Urban Population / Q000706:statistics & numerical data*; D055815:Young Adult