A course introducing the principles of pharmaceutical care.

OBJECTIVES: To develop, implement, and assess a course that introduces students to the process and application of pharmaceutical care. DESIGN: The course was offered to students in the third semester of the PharmD curriculum. The course's ability outcomes were to integrate and apply scientific and therapeutic knowledge in the delivery of evidence-based pharmaceutical care, and to develop the skills of a professional, lifelong learner. ASSESSMENT: The students successfully applied the information learned in this course to the practice of pharmaceutical care. The 3 components of the course that appeared to be the most challenging were identifying drug-therapy problems, creating compound goals, and creating a care plan. CONCLUSION: This course was effective in meeting ability-based outcomes. The assessment data helped the instructors determine what changes should be made to increase the course's success when it is offered again.

Assessment of glycated hemoglobin using A1CNow+ point-of-care device as compared to central laboratory testing.

BACKGROUND: Hemoglobin A1c monitoring is routine care for patients with diabetes and may be obtained as often as every 3 months. Most family practice clinics are not equipped to evaluate a hemoglobin A1c result in the office. Obtaining a hemoglobin A1c result from a central laboratory can result in a delay, added expense, and inconvenience for the patient. To date, there are no published studies on the accuracy of the A1CNow+, a point-of-care hemoglobin A1c monitoring device. METHODS: Seventy patients having type 1 or type 2 diabetes were enrolled from three pharmacy-managed diabetes clinics. Subjects were required to have a venous blood draw within 1 week of the point-of-care test. The study then evaluated the statistical and clinical significance between both tests. RESULTS: A good correlation was seen between the A1CNow+ and laboratory values with a correlation coefficient of r = 0.893. The best correlation between the A1CNow+ and the laboratory was seen among hemoglobin A1c values in the range of 7-8.5%. CONCLUSION: The access of the A1CNow+ device at point of care makes a hemoglobin A1c evaluation economically and therapeutically beneficial after proving its accuracy in a primary care setting. Advantages of this device may go beyond convenience and economic benefit by allowing patients to acknowledge their level of glucose control at the point of care and to be counseled appropriately.

Influence of coagulation factor, vitamin K epoxide reductase complex subunit 1, and cytochrome P450 2C9 gene polymorphisms on warfarin dose requirements.

INTRODUCTION: The primary objective of this study was to determine whether variability in warfarin dose requirements is determined by common polymorphisms in genes whose products are involved in the pharmacodynamics and pharmacokinetics of warfarin, namely, the coagulation factors, vitamin K epoxide reductase complex subunit 1 (VKORC1), and cytochrome P450 (CYP) 2C9. METHODS: Patients (N = 350) receiving stable doses of warfarin at 3 consecutive visits were enrolled, and a deoxyribonucleic acid sample was collected. Samples were genotyped for polymorphisms in the factor II, factor VII, factor X, VKORC1, and CYP2C9 genes. A stepwise linear regression analysis was used to determine the independent effects of genetic and nongenetic factors on mean warfarin dose requirements. RESULTS: Variables associated with lower warfarin dose requirements were VKORC1 3673 AA genotype (P < .0001), VKORC1 3673 GA genotype (P < .0001), 1 variant CYP2C9 allele (P < .0001), 2 variant CYP2C9 alleles (P = .0004), increasing age (P = .0005), concomitant CYP2C9 inhibitors (P = .0005), and goal international normalized ratio (P = .01). Variables associated with higher warfarin dose requirements were weight (P < .0001), current smoker status (P = .0009), mean international normalized ratio (P = .001), concomitant CYP2C9 inducers (P = .006), factor X insertion/deletion genotype (P = .01), factor X insertion/insertion genotype (P = .04), factor VII deletion/deletion genotype (P = .04), and calculated vitamin K intake (P = .05). The linear regression model explained 51.4% of the variability in warfarin dose requirements. CONCLUSION: Polymorphisms in warfarin drug target and metabolizing enzyme genes, in addition to nongenetic factors, were important determinants of warfarin dose requirements.