Using a logistic regression model, this dissertation employed a macro level Gateway Provider Model to explore eight factors that may influence community health center HIV testing approach. The logistic regression model indicated that three variables related to community health center HIV testing approach. First, all else equal, the odds of offering routine HIV testing for community health centers that perceived their patients and community to be at average risk for HIV were 3.676 times the odds for those centers that perceived their patients and community to be at low or no risk for HIV. Further, the odds of offering routine HIV testing for community health centers that perceived their patients and community to be at high risk for HIV were 4.693 times the odds for those centers that perceived the community to be at low or no HIV risk. Second, all else equal, the odds of offering routine HIV testing for community health centers in which an HIV testing policy exists were 2.202 times the odds for those centers in which an HIV testing policy does not exist. Third, all else equal, the odds of offering routine HIV testing for community health centers that received funding specifically for HIV testing were 2.938 times the odds for those centers that did not receive such funding. No other individual predictor variables in the model were related to community health center HIV testing approach.