Date of Award


Degree Type


Degree Name

Master of Science in Pharmaceutical Sciences


Biomedical and Pharmaceutical Sciences

First Advisor

Stephen J. Kogut


The aim of the study is to determine whether the recommended lab monitoring for metformin is preformed appropriately in the ambulatory care setting and if the patient characteristics are associated with monitoring rate. A cross-sectional study was performed using a healthcare claims database. An univariate analysis frequency and percentage assessed the characteristics of patients in our study. Also it measure the frequency of lab monitoring: HGBA1C, CBC, OR B12, SCR and optimal, defined as receiving all three tests. Bivariate analyses determined the significance of differences between those receiving and not receiving lab testing according to patience characteristics. In a prediction model multivariate logistic modeling with backward elimination was performed to identify significant patient characteristics predicting lab monitoring, and to obtain adjusted odd ratios. Optimal lab monitoring rate during 18 months rate during the 18 months was 32.88 percent. A predictive model included age category, cardiovascular, renal, respiratory disease, mental health disorder, number of clinic visit, and medication possession rate (MPR). Elderly patients with comorbidities were more likely to receive optimal care; more frequent clinic visits and greater rates of medication adherence were associated with receiving optimal lab monitoring for metformin.