Charles D. Sintek

Clinical and Economic Impact of Ambulatory Care Clinical Pharmacists in Management of Dyslipidemia in Older Adults: The IMPROVE Study

We examined the impact of ambulatory care clinical pharmacist interventions on clinical and economic outcomes of 208 patients with dyslipidemia and 229 controls treated at nine Veterans Affairs medical centers. This was a randomized, controlled trial involving patients at high risk of drug‐related problems. Only those with dyslipidemia are reported here. In addition to usual medical care, clinical pharmacists were responsible for providing pharmaceutical care for patients in the intervention group. The control group did not receive pharmaceutical care. Seventy‐two percent of the intervention group and 70% of controls required secondary prevention according to the National Cholesterol Education Program guidelines. Significantly more patients in the intervention group had a fasting lipid profile compared with controls (p=0.021). The absolute change in total cholesterol (17.7 vs 7.4 mg/dl, p=0.028) and low‐density lipoprotein (23.4 vs 12.8 mg/dl, p=0.042) was greater in the intervention than in the control group. There were no differences in patients achieving goal lipid values or in overall costs despite increased visits to pharmacists. Ambulatory care clinical pharmacists can significantly improve dyslipidemia in a practice setting designed to manage many medical and drug‐related problems.

An economic analysis of a randomized, controlled, multicenter study of clinical pharmacist interventions for high-risk veterans: The IMPROVE study

Study Objective. To determine if clinical pharmacists could affect economic resource use and humanistic outcomes in an ambulatory, high‐risk population.

Can clinical pharmacists affect SF-36 scores in veterans at high risk for medication-related problems?

Background.An objective of pharmaceutical care is for pharmacists to improve patients’ health-related quality of life (HRQOL) by optimizing medication therapy. Objectives.The objective of this study was to determine whether ambulatory care clinical pharmacists could affect HRQOL in veterans who were likely to experience a drug-related problem. Research Design. This was a 9-site, randomized, controlled trial involving Veterans Affairs Medical Centers (VAMCs). Patients were eligible if they met ≥3 criteria for being at high risk for drug-related problems. Enrolled patients were randomized to either usual medical care or usual medical care plus clinical pharmacist interventions. HRQOL was measured with the SF-36 questionnaire administered at baseline and at 6 and 12 months. Results.In total, 1,054 patients were enrolled; 523 were randomized to intervention, and 531 to control. After patient age, site, and chronic disease score were controlled for, the only domain that was significantly different between groups over time was the bodily pain scale, which converged to similar values at the end of the study. Patients’ rating of the change in health status in the past 12 months was statistically different between groups, intervention patients declining less (−2.4 units) than control subjects (−6.3 units) (P <0.004). This difference was not considered clinically meaningful. However, a dose-response relationship was observed for general health perceptions (P = 0.004), vitality (P = 0.006), and change in health over the past year (P = 0.007). Conclusions.These results suggest that clinical pharmacists had no significant impact on HRQOL as measured by the SF-36 for veterans at high risk for medication-related problems.

Types of Interventions Made by Clinical Pharmacists in the IMPROVE Study

The purpose of this study was to describe and evaluate the activities and interventions provided by ambulatory care clinical pharmacists during the IMPROVE (Impact of Managed Pharmaceutical Care on Resource Utilization and Outcomes in Veterans Affairs Medical Centers) study. A total of 523 patients were randomized into the intervention arm at nine Veterans Affairs medical centers if they were considered to be at high risk for drug‐related problems. Patients randomized to the control group had no interventions and they are not reported. Using a standard form, pharmacists were asked to document the length of visit, method of contact, medical conditions addressed, and drug‐related problems addressed and resolved during each contact. Seventy‐eight ambulatory care clinical pharmacists documented 1855 contacts over 12 months, an average of 3.54 ± 2.31/patient. The length of visits was 15 minutes or more for 73% of contacts. In‐person contacts accounted for 1421 visits (76.6%), with the remainder being telephone contacts. During each contact the average number of drug‐related problems addressed and resolved were 1.64 ± 1.16 and 1.14 ± 0.98, respectively. More drug‐related problems were addressed and resolved when visits were 15 minutes or longer (p= 0.001) and when the contact was in person (p= 0.001). These data may provide information to clinical pharmacists developing pharmacy‐managed clinics for patients at high risk for drug‐related problems. The information may be a benchmark for types of interventions that can be made, as well as the time commitments required to make them.

Estimating Risk Factors for Patients with Potential Drug-Related Problems Using Electronic Pharmacy Data

OBJECTIVE: To validate a computer-based program to identify patients at high risk for drug-related problems. DESIGN: Computerized analysis of pharmacy dispensing records and manual review of medical records. SETTING: Ambulatory clinics at a Veterans Affairs Medical Center. PATIENTS: 246 randomly selected patients who were receiving at least one outpatient medication in the previous 24 months. MAIN OUTCOME MEASURES: Presence of six previously established criteria regarding medication use. These criteria are five or more medications, ≥12 doses per day, four or more changes to the medication regimen, three or more chronic diseases, history of noncompliance, and presence of a drug requiring therapeutic drug monitoring (TDM). RESULTS: Spearman rho rank order correlation coefficients ranged from 0.63 to 0.91 for criteria pertaining to the number of medications, daily doses, changes in the medication regimen, and number of chronic diseases (all significant, p = 0.0001). The computer program underestimated the number of chronic diseases and overestimated the number of daily doses. The level of agreement between the computer program and chart review for patient noncompliance was low (Kappa = 0.38), with the computer more likely to indicate a patient was noncompliant. A high level of agreement was seen between the computer program and chart review for the presence of a drug requiring TDM (Kappa = 0.83). For all six criteria, the computer program had a sensitivity of 65.7% and specificity of 88.2%. CONCLUSIONS: When compared with medical records, the use of this program to evaluate electronic pharmacy data can be efficient to screen large numbers of patients who may be at high risk for drug-related problems. This method may be useful for clinical pharmacists in providing pharmaceutical services to patients who are most likely to benefit.

Reduced Quality of Life in Veterans at Risk for Drug-Related Problems

The relationships between drug therapy and health‐related quality of life in 1054 patients who received care from Department of Veterans Affairs medical centers (VAMCs) were assessed. Patients at high risk for drug‐related problems were enrolled into a pharmaceutical care study at nine VAMCs. On enrollment, the short form (SF)‐36 was completed and medical records were examined for evidence of coexisting illness. Drug therapy in the year before enrollment was analyzed in relation to SF‐36 scores. Mean ± SD SF‐36 scores ranged from 37.99 ± 41.70 for role physical to 70.78 ± 18.97 for mental health domains, with all domain scores significantly below age‐adjusted national norms (p<0.05). Patients taking a drug that required therapeutic monitoring had significantly lower SF‐36 scores (p=0.0001 to p=0.0033) across all domains except for bodily pain and mental health, compared with patients not taking these agents.

A warfarin-piroxicam drug interaction.

A piroxicam-warfarin interaction is presented with a discussion of the possible mechanism of action. A 60-year-old white male on warfarin therapy for recurrent pulmonary embolism and deep venous thrombophlebitis showed a decrease in his previously therapeutic and stable prothrombin time when piroxicam was discontinued from his drug regimen. On two rechallenges over a ten-month period, his prothrombin times showed consistent and clinically significant fluctuations as piroxicam was added and deleted from his drug regimen.