The investigators will control for potential covariates which may not be evenly distributed between the intervention and control groups (e.g. age, socioeconomic status, etc.). Since observations within each participating clinic will be assumed more likely to be similar than observations between clinics, a logistic model using a conditional (for paired data) generalized estimating equation (GEE) method will be performed to account for this clustering effect within clinics, incorporating both within-clinic and between-clinic variations. An intracluster correlation coefficient (ICC) and variance inflation factor (VIF) will also be calculated to assess the impact of the clustering effect.