Pharmacist Recommendations to Improve the Quality of Diabetes Care: A Randomized Controlled Trial

Abstract

BACKGROUND: Diabetes mellitus continues to result in substantial morbidity and mortality despite receiving much attention from health care providers. Automated clinician reminder systems have been developed to improve adherence to diabetes care guidelines, but these reminder systems do not always provide actionable information and may be unable to detect relevant, subjective patient information that affects clinical decision making. Face-to-face visits with pharmacists, who have knowledge of care guidelines and medication management strategies, may assist in improving diabetes care. It is unknown if the combination of pharmacist chart review and clinician reminders could improve diabetes care without requiring face-to-face visits. OBJECTIVE: To assess the effects of a comprehensive, pharmacistdelivered, primary care, physician-focused intervention in a large hospitalbased primary care practice to improve the quality of care for patients with diabetes including rates of semiannual hemoglobin A1c testing and other biomarker and process measures. METHODS: This was a prospective, randomized, controlled study conducted in a hospital-based, primary care practice, composed of 37 faculty primary care physicians (PCPs) and 95 internal medicine residents. The initial sample included 346 patients with diabetes and 72 PCPs caring for them. PCPs were randomized to receive either a personalized letter from a practicing pharmacist containing treatment recommendations for patients with upcoming primary care visits (intervention, n = 33) or to usual care without the letters (control, n = 39). The letter included patient-specific recommendations regarding overdue testing as well as drug therapy to achieve diabetes-related treatment targets. The intervention included addition of the letter to the electronic medical record (EMR) and presentation of the letter to the PCP at the time of the index primary care visit that occurred between November 2003 and August 2004. Follow-up chart review was performed after the primary care visit to determine changes in 5 process and 3 biomarker outcome measures of diabetes care within 30 days of the index visit. The primary study outcome was a process measure, change in rates of semiannual A1c testing from baseline to 30-day follow-up. Baseline differences were tested for statistical significance using Pearson chisquare. The statistical significance of the intervention's effect was tested using logistic regression models predicting achievement of each study outcome, with randomization status (intervention vs. control) as the predictor variable of interest, controlling for baseline performance for each measure. RESULTS: 171 patients were in the 4 medical clinic suites with 33 PCPs who received the intervention, and 175 patients were in the 4 suites with 39 PCPs in usual care. 30-day outcomes were analyzed for 301 patients (87.0%) who attended their scheduled index primary care visit. Of these 301 patients, 44.5% were black, 65.8% were female, and the mean age was 63 years. At baseline, ther...

Effect of clinical pharmacists pharmaceutical care intervention to control hypertensive outpatients in China

“…These results suggested that early interventions of drug treatment were very important and directly affect the final outcomes in the study. Furthermore, the importance of early intervention also might be used for other chronic diseases, such as diabetes, liver diseases and blood disorders (Kirwin et al, 2010). Foreign study also found that early use of antihypertensive treatment can prevent complications, prolong life, and especially reduce the actual costs when compared with the late use patients with antihypertensive drugs (McCombs et al, 1994;Sokol et al, 2005).…”

What works to increase attendance for diabetic retinopathy screening? An evidence synthesis and economic analysis

“…However, 33 studies (48.5%) [58][59][60]62,65,68,69,71,72,74,76,78,[81][82][83][84]88,[91][92][93][94][95][96][97]99,100,[103][104][105][106][107]119,121 were judged to be at high risk of bias in at least one domain. The domains most commonly at high risk of bias were 'incomplete outcome data addressed' [15 studies 65,68,72,76,78,[81][82][83][84]88,93,94,100,103,105 (22.7%)], 'protected against contamination' [seven studies 60,62,…”

“…The domains most commonly at high risk of bias were 'incomplete outcome data addressed' [15 studies 65,68,72,76,78,[81][82][83][84]88,93,94,100,103,105 (22.7%)], 'protected against contamination' [seven studies 60,62,96,99,104,107,119 (10.6%)] and 'similar baseline outcome measurements' [five studies 58,69,92,95,106 (7.6%)]. It was possible to judge if a study was free from selective outcome reporting for only 17 studies (25.7%) 58,59,63,64,67,69,72,77,78,83,84,94,96,99,100,121,123 because of a lack of availability of a prospectively published trial registration or protocol. Although studies were rarely judged to be at a high risk of bias for adequate sequence generation and adequate allocation concealment, the methods associated with these domains were frequently poorly reported.…”

“…Care guide workstations were located in the clinic waiting rooms, to facilitate face-to-face interactions with patients, providers, and nurses Adair et al 59 We explored publication bias using a funnel plot for the main comparison of any intervention with usual care (56 studies [58][59][60][61][62][63][65][66][67][68][69][70][71][72][74][75][76][77][78][80][81][82][83][84][85][86][87][88][89][92][93][94][95][96][97][98][99][100][101][102][103][104][105][108][109][110][111][112]…”

“…Thirty-one (47%) 58,60,[64][65][66][67][68][69][70]73,74,[76][77][78][79]81,83,84,[90][91][92][93][94]97,100,101,[104][105][106]110,123 of the 66 trials were cluster RCTs. Only nine 65,67,69,70,73,83,93,101,123 of these reported an ICC and the ICC reported typically did not relate specifically to DRS outcomes.…”