Barry L. Carter

In the past year, American College of Clinical Pharmacy (ACCP) has released white papers on quality measures of clinical pharmacy services in ambulatory care, acute care, and transitions of care. While reviewing established metrics and proposing new measures, these papers call out the lack of development, standardization, and validation of quality measures for the practice of pharmacy. This commentary provides a call to action for ACCP and the pharmacy enterprise.

More than 50% of Americans possess at least one chronic condition and another 25% suffer from two or more, leaving primary care teams tasked to care for the chronic, acute, and preventive care needs of their large patient panels. Pharmacists can reduce the burden on busy providers by effectively managing chronic diseases as members of health care teams. Many private physician practices lack the resources to include pharmacists on their teams. A centralized, remote clinical pharmacy services model allows pharmacists to remotely manage chronic disease in patients in collaboration with primary care providers. The purpose of this report is to describe how a centralized, remote clinical pharmacy team was developed, trained, and effectively integrated into multiple, diverse primary care settings across the U.S.

Hydroxychloroquine combined with azithromycin has been investigated for activity against coronavirus disease 2019 (COVID‐19), but concerns about adverse cardiovascular (CV) effects have been raised. This study evaluated claims data to determine if risks for CV events were increased with hydroxychloroquine alone or combined with azithromycin. We identified data from 43,752 enrollees that qualified for analysis. The number of CV events increased by 25 (95% confidence interval [CI]: 8, 42, p=0.005) per 1000 people per year of treatment with hydroxychloroquine alone compared with pretreatment levels and by 201 (95% CI: 145, 256, p<0.001) events per 1000 people per year when individuals took hydroxychloroquine and azithromycin. These rates translate to an additional 0.34 (95% CI: 0.11, 0.58) CV events per 1000 patients placed on a 5‐day treatment with hydroxychloroquine monotherapy and 2.75 (95% CI: 1.99, 3.51) per 1000 patients on a 5‐day treatment with both hydroxychloroquine and azithromycin. The rate of adverse events increased with age following exposure to hydroxychloroquine alone and combined with azithromycin. For females aged 60 to 79 years prescribed hydroxychloroquine, the rate of adverse CV events was 0.92 per 1000 patients on 5 days of therapy, but it increased to 4.78 per 1000 patients when azithromycin was added. The rate of adverse CV events did not differ significantly from zero for patients 60 years of age or younger. These data suggest that hydroxychloroquine with or without azithromycin is likely safe in individuals under 60 years of age if they do not have additional CV risks. However, the combination of hydroxychloroquine and azithromycin should be used with extreme caution in older patients.

The authors examined whether using home BP measurements collected via a custom‐built bi‐directional‐texting platform incorporated into patients’ electronic medical records would lead to treatment calibration and improved BP management. Patients were randomized to either the intervention group and collected home measurements based on reminders and reported via bi‐directional texting, or to the control group, with home BP measurement reporting via standard practice (eg, phone, electronic medical record portal) and instructed to return 7 morning and 7 evening BP measurements. Outcomes included number of BP measurements submitted, the number of medication changes, reduction in BP, and BP control. 72% of the intervention group submitted at least 14 readings, compared with 45% of the control group. BP control improved in both groups. However, the authors found no statistically significant difference in BP or the number of BP‐medication changes at 1, 3, or 6 months compared with the control group.

Background: The use of clinical pharmacists in primary care has improved the control of several chronic cardiovascular conditions. However, many private physician practices lack the resources to implement team-based care with pharmacists. The purpose of this study was to evaluate whether a centralized, remote, clinical pharmacy service could improve guideline adherence and secondary measures of cardiovascular risk in primary care offices in rural and small communities. Methods and Results: This study was a prospective trial in 12 family medicine offices cluster randomized to either the intervention or usual care. The intervention was delivered for 12 months, and subjects had research visits at baseline and 12 months. The primary outcome was adherence to guidelines, and secondary outcomes included changes in key cardiovascular risk factors and preventative health measures. We enrolled 302 subjects. There was no improvement in the Guideline Advantage score from baseline to 12 months in the control group (64.7% versus 63.1%, respectively; P =0.21). There was a statistically significant improvement in the intervention group from 63.3% at baseline to 67.8% at 12 months ( P =0.02). The estimated benefit of the intervention was 5.0%±2.4% (95% confidence interval=−0.5% to 10.4%; P =0.07). Several criteria were significantly better for intervention subjects, including appropriate statin therapy ( P P P P =0.10). Conclusions: The centralized, remote pharmacist intervention was successfully implemented. The improvements in outcomes were modest, in part because of higher than expected baseline guideline adherence. Future studies of this model should focus on patients with uncontrolled conditions at high risk for cardiovascular events. CLINICAL TRIAL REGISTRATION: URL: https://www.clinicaltrials.gov . Unique identifier: NCT 01983813

Selection bias and non-participation bias are major methodological concerns which impact external validity. Cluster-randomized controlled trials are especially prone to selection bias as it is impractical to blind clusters to their allocation into intervention or control. This study assessed the impact of selection bias in a large cluster-randomized controlled trial. The Improved Cardiovascular Risk Reduction to Enhance Rural Primary Care (ICARE) study examined the impact of a remote pharmacist-led intervention in twelve medical offices. To assess eligibility, a standardized form containing patient demographics and medical information was completed for each screened patient. Eligible patients were approached by the study coordinator for recruitment. Both the study coordinator and the patient were aware of the site’s allocation prior to consent. Patients who consented or declined to participate were compared across control and intervention arms for differing characteristics. Statistical significance was determined using a two-tailed, equal variance t-test and a chi-square test with adjusted Bonferroni p-values. Results were adjusted for random cluster variation. There were 2749 completed screening forms returned to research staff with 461 subjects who had either consented or declined participation. Patients with poorly controlled diabetes were found to be significantly more likely to decline participation in intervention sites compared to those in control sites. A higher mean diastolic blood pressure was seen in patients with uncontrolled hypertension who declined in the control sites compared to those who declined in the intervention sites. However, these findings were no longer significant after adjustment for random variation among the sites. After this adjustment, females were now found to be significantly more likely to consent than males (odds ratio = 1.41; 95% confidence interval = 1.03, 1.92). Though there appeared to be a higher consent rate for females than for males, the overall impact of potential selection bias and refusal to participate was minimal. Without rigorous methodology, selection bias may be a threat to external validity in cluster-randomized trials. NCT01983813 . Date of registration: Oct. 28, 2013.

You breathe a huge sigh of relief because you just received the official notice of award that your grant was funded by the American Heart Association (AHA), the National Heart, Lung, and Blood Institute (NHLBI), or the Patient‐Centered Outcomes Research Institute (PCORI). Your award will fund a

Physician–pharmacist collaboration improves blood pressure, but there is little information on whether this model can reduce the gap in healthcare disparities. This trial involved 32 medical offices in 15 states. A clinical pharmacist was embedded within each office and made recommendations to physicians and patients in intervention offices. The purpose of the present analysis was to evaluate whether the pharmacist intervention could reduce healthcare disparities by improving blood pressure in high-risk racial and socioeconomic subjects compared with the control group. The analyses in minority subjects were prespecified secondary analyses, but all other comparisons were secondary, post hoc analyses. The 9-month visit was completed by 539 patients: 345 received the intervention, and 194 were in the control group. Following the intervention, mean systolic blood pressure was found to be 7.3 mm Hg (95% confidence interval 2.4, 12.3) lower in subjects from racial minority groups who received the intervention compared with the control group ( P =0.0042). Subjects with ≤12 years of education in the intervention group had a systolic blood pressure 8.1 mm Hg (95% confidence interval 3.2, 13.1) lower than the control group with lower education ( P =0.0001). Similar reductions in blood pressure occurred in patients with low incomes, those receiving Medicaid, or those without insurance. This study demonstrated that a pharmacist intervention reduced racial and socioeconomic disparities in the treatment of blood pressure. Although disparities in blood pressure were reduced by the intervention, there were still nonsignificant gaps in mean systolic blood pressure when compared with intervention subjects not at risk. Clinical Trial Registration—: URL: http://clinicaltrials.gov . Unique identifier: NCT00935077.