(Determinants of Accurate Control in Diabetic Patients: Application of the Multilevel Analysis for Costa Rica)
Aim: To establish an initial approach to identify individual and group variables that determine adequate interventions on diabetic patients by the Basic Integral Healthcare Units of the Costa Rican social security system. Methods: The study design is non-experimental, cross-sectional and applies multilevel logistic regression. The data were obtained from a sample chosen from the Health Services Purchasing Direction, and includes diabetic patients cared for at local levels from January to December 2004. The information was used at 2 levels of analysis: level 1 (individual) and level 2 (group), and glycosylated hemoglobin was used as a dependent variable. Results: Forty-nine percent of patients were controlled, with a median age above 60 years, 66% were women, and 76,6% had a body mass index reflecting overweight or obesity. On average, the Basic Integral Healthcare Units in the study had 7 years since initiating the reform process, and their average score on the “Commitment of Management” for the last 5 years was 87%. Moreover, the average population covered was 40 thousand inhabitants, and 22% of them had high school education. Multilevel logistic regression revealed that as diabetic patients age the probability of achieving control of the disease also increases. Women had a lower probability of being under control as compared to men. Diabetic patients belonging to the Basic Integral Healthcare Units that initiated their reform earlier, and those belonging to health services achieving higher scores on the “Commitment of Management” had a higher probability of being under control, even though this finding was not statistically significant, with respect to the other variables in the model. Discussion: Approximately between 6% and 10% of the variance in the control of diabetic patients is explained by differences within local health services, after controlling for other intervening variables.