Accepted Manuscript

Effectiveness of Community Pharmacist Prescribing and Care on Cardiovascular RiskReduction: Randomized Controlled RxEACH Trial

Ross T. Tsuyuki, BSc(Pharm), PharmD, MSc, FCSHP, FACC, Yazid N. Al Hamarneh,BSc(Pharm), PhD, Charlotte A. Jones, MD, PhD, FRCP(c), Brenda R. Hemmelgarn,MD, PhD, FRCP(c)

PII: S0735-1097(16)32407-X

DOI: 10.1016/j.jacc.2016.03.528

Reference: JAC 22446

To appear in: Journal of the American College of Cardiology

Received Date: 29 February 2016

Revised Date: 24 March 2016

Accepted Date: 25 March 2016

Please cite this article as: Tsuyuki RT, Al Hamarneh YN, Jones CA, Hemmelgarn BR, Effectivenessof Community Pharmacist Prescribing and Care on Cardiovascular Risk Reduction: RandomizedControlled RxEACH Trial, Journal of the American College of Cardiology (2016), doi: 10.1016/j.jacc.2016.03.528.

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Effectiveness of Community Pharmacist Prescribing and Care on Cardiovascular Risk Reduction: Randomized Controlled RxEACH Trial

Ross T. Tsuyuki, BSc(Pharm), PharmD, MSc, FCSHP, FACC1, Yazid N. Al Hamarneh, BSc(Pharm), PhD1, Charlotte A. Jones, MD, PhD, FRCP(c)2, Brenda R Hemmelgarn, MD, PhD, FRCP(c)3 1. EPICORE Centre, Department of Medicine, University of Alberta, Edmonton, AB. Mazankowski Alberta Heart Institute. rtsuyuki@ualberta.ca; yazid.alhamarneh@ualberta.ca 2. Southern Medical Program, University of British Columbia, Kelowna, BC. charlotte.jones@ubc.ca 3. Department of Community Health Sciences and Medicine, Cumming School of Medicine, University of Calgary, Calgary, AB. brenda.hemmelgarn@albertahealthservices.ca Brief Title: Pharmacist Prescribing to Reduce Cardiovascular Risk Acknowledgements We would like to acknowledge the funders of RxEACH: Alberta Health (Workforce Planning), The Cardiovascular Health and Stroke Strategic Clinical Network of Alberta Health Services (Agnes Lehman, Louise Morin, Dr. Blair O’Neill, Balraj Mann, Dr. Norm Campbell, and Dr. James Stone), the Interdisciplinary Chronic Disease Collaboration (Sarah Gil), and Merck Canada (investigator-initiated funding for the educational program). We would also like to acknowledge Craig Curtis and Carlee Balint (research pharmacists), Ian Creuer from the Pharmacy Department of Alberta Health Services, and Imran Hassan (biostatistician) from EPICORE Centre for their support. And, none of this could have taken place without the dedication, caring and courage of the RxEACH investigators, listed in descending order of recruitment: Jen Winter and Lonni Johnson (Winter's Pharmacy, Drayton Valley), Tyler Watson and Andrew Fuller (Pharmacare Specialty Pharmacy, Edmonton), Janelle Fox (Pharmasave #325, Bonnyville), Rick Siemens (London Drugs #38, Lethbridge), Jasbir Bhui and Jasmine Basi (Medicine Shoppe #170, Edmonton), Murtaza Hassanali, Shamas Arshad and Manpreet Mann (Shoppers Drug Mart #371, Edmonton), Theresa Lawrence, Michelle Ewen and Maged Radwan (Rexall Pharmacy #7222 and #7266, Blairmore and Pincher Creek), Anita and Bob Brown (Shoppers Drug Mart #2401, Okotoks), Leanna St. Onge, Otti Gohrbandt and Chelsey Collinge (Co-op Pharmacy, Rocky Mountain House), Jelena Okuka and Michelle Teasdale (Co-op Pharmacy, Lloydminster), Hyder Mohammed (Shoppers Drug Mart #2318, Lethbridge), Gehan Rizkalla (Loblaws Pharmacy #4950, Leduc), Dixied Richardson (Safeway Pharmacy #848, Edmonton), Roberta Taylor (Roots & Berries Pharmacy, Maskwacis), Marnie Kachman and Kristy Russ (Medicine Shoppe #264, Leduc), Anita Wong (Rexall Pharmacy #9801, Edmonton), Sheilah Kostecki (Safeway Pharmacy #2730, Calgary), Terrilynn Eriksen and Sharon Beaudry (Costco Pharmacy #254, Grande Prairie), Nader Hammoud (Shoppers Drug Mart #2326, Calgary), Jim Kitagawa (Pharmasave #345, Brooks), Morenike Olaosebikan (Shoppers Drug Mart #381, Edmonton), Rosalia Yeun (Medicine Shoppe #328, Edmonton), Carlene Oleskyn and Jelena Okuka (Meridian Pharmacy, Stony Plain), Dactin and Monika Tran (Sandstone Sarcee, Calgary), Rita

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Lyster and Alex Lischuk (Ritas Apothecary, Barrhead), Barb Bryan and Arin Getz (Sobeys Pharmacy #1129, Calgary), Lyn Gilmore and Rick Krieser (Shoppers Drug Mart #2374, Edmonton), Nermen Kassam (Pharmacy Plus Ltd, Calgary), Azita Rezai (Shoppers Drug Mart #385, Calgary), Tony Nickonchuk, Stacy Billows (Walmart Pharmacy #1068, Peace River), Piere Danis, Brittany Dyjur and Meghan Gainer (Safeway Pharmacy #861, Edmonton), Paulise Ly (Walmart Pharmacy #1144, Calgary), Jody Keller and Wade Mannle (Pharmasave #378, Carstairs), Uzma Saeed (Walmart Pharmacy #1071, Vegreville), Rick Mah (Sobeys Pharmacy #1139, Calgary), Ken Pitcher (Save-On Foods Pharmacy #6642, Lethbridge), Mike, Pat and Vanda Kinshella (Value Drug Mart, Peace River), Nadine Abou-Khair, Aileen Coutts and Sonal Ejner (Coop Pharmacy, Calgary), Duy Troung (Shoppers Drug Mart #2300, St. Albert), Janice Chua (Shoppers Drug Mart #324, Wetaskiwin), Brendan Ihijerika (Guardian Pharmacy, Mundare), Marlene Bykowski (Remedy Rx 222, St. Albert), Jaclyn Katelnikoff (Stafford Pharmacy, Lethbridge), Rashid Jomha (Sobeys Pharmacy #3132, Edmonton), Nick Leong (Shoppers Drug Mart #328, Edmonton), Peter Lok (Shoppers Drug Mart #357, Ponoka), Kim Lau (Remedy's Rx #223, Calgary), Brittany Zelmer (Safeway Pharmacy #864, Edmonton), Anar Dato (Shoppers Drug Mart #2391, Calgary), Kelly Laforge (Shoppers Drug Mart #2448, Edmonton), Todd Pranchau (Shoppers Drug Mart #2450, Sylvan Lake), Folake Adeniji (Shoppers Drug Mart #310, Leduc), Brad Couldwell and Trudy Arbo (Shoppers Drug Mart #321, Calgary), Anita and Reid McDonald (Sunset Ridge Pharmacy, Calgary), Jacki Swindelhurst (Rexall Pharmacy #7245, Drayton Valley). Funding for the RxEACH study was provided by Alberta Health, the Cardiovascular Health and Stroke Strategic Clinical Network of Alberta Health Services and Merck Canada (for development of the educational materials only). None of these sponsors had any role in the design, conduct, collection, analysis or interpretation or data or the preparation, review or approval of this manuscript. Disclosures: Ross T. Tsuyuki: Investigator-Initiated Research Grants from: Merck, Sanofi, AstraZeneca Consulting: Merck All other authors have no disclosures. Corresponding Author: Ross T. Tsuyuki BSc(Pharm), PharmD, MSc, FCSHP, FACC Professor of Medicine (Cardiology), Faculty of Medicine and Dentistry University of Alberta EPICORE Centre, 4-000 Research Transition Facility University of Alberta Edmonton, Alberta, Canada T6G 2V2 Telephone: 780-492-8526 Fax: 780-492-6059 E-mail: rtsuyuki@ualberta.ca

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ABSTRACT Background: Despite the risk associated with hypertension, diabetes, dyslipidemia, and smoking, these cardiovascular disease (CVD) risk factors remain poorly identified and controlled. Objectives: To evaluate the effectiveness of a community pharmacy-based case finding and intervention on cardiovascular risk. Methods: RxEACH was a randomized trial conducted in 56 community pharmacies across Alberta, Canada. Participants were recruited by their pharmacist, enrolling adults at high risk for CVD: those with diabetes, chronic kidney disease, previous vascular disease and/or Framingham Risk > 20% with ≥1 uncontrolled risk factor (blood pressure, LDL-cholesterol (LDL-c), HbA1c, or smoking). Patients were randomized to intervention or usual care groups. Intervention group received a Medication Therapy Management review from their pharmacist with CVD risk assessment and education. Pharmacists prescribed medications and ordered laboratory tests as per their scope of practice to achieve treatment targets. Subjects received monthly follow-up visits for 3 months. Usual care group received usual pharmacist care with no specific intervention. Primary outcome was difference in change in estimated CVD risk between intervention and usual care groups at 3 months. CVD risk was estimated using the greater of Framingham, International Score, or United Kingdom Prospective Diabetes Study risk engines. Results: We enrolled 723 patients. Mean age was 62 (standard deviation, SD 12) years, 58% male and 27% smokers. After adjusting for baseline values and center effect, there was a 21% difference in CVD risk (p<0.001) between intervention and usual care groups. Intervention group had greater reductions of 0.2 mmol/L in LDL-c (p<0.001), 9.37 mmHg systolic blood pressure (p<0.001), 0.92% HbA1c (p<0.001), and 20.2% in smoking cessation (p=0.002). Conclusions: RxEACH was the first large randomized trial of CVD risk reduction by community pharmacists, demonstrating a significant reduction in the risk for CVD events. Engagement of community pharmacists with an expanded scope of practice could have significant public health implications. Clinicaltrials.gov Identifier: NCT01979471 Key Words: blood pressure, dyslipidemia, diabetes, smoking, cardiovascular risk, pharmacists Abbreviations ACR = albumin to creatinine ratio ASA = acetylsalicylic acid, aspirin CVD = cardiovascular disease eGFR = estimated glomerular filtration rate HbA1c = glycated hemoglobin LDL-c = low density lipoprotein cholesterol SD = standard deviation UKPDS = United Kingdom Prospective Diabetes Study

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Introduction

Cardiovascular disease (CVD) is the leading cause of death worldwide, accounting for nearly

one third of all deaths (1). Most CVDs are caused by modifiable risk factors, including tobacco

smoking, hypertension, dyslipidemia, diabetes, physical inactivity, high fat diet and obesity (1).

Despite decreases in rates over the last few decades, CVDs remain one of the leading causes of

death in Canada and the United States (2, 3). CVD also carries a financial burden on the North

American economy with a cost close to $ 21 billion every year divided between loss of

productivity and healthcare costs in Canada (2) and $444 billion overall cost in the US (4).

Notwithstanding major advances in treatment, the prevalence of poorly controlled CVD risk

factors is still substantial in North America (5,-7). Recent studies have indicated that almost 50%

of the community dwelling patients with type 2 diabetes are not at their HbA1c, (8) or

cholesterol (9,10) targets, and between 50-62% are not at their blood pressure targets (9,10). In

one of these studies, only 13% achieved the composite triple target (10). Furthermore, less than

half of the patients with hyperlipidemia were reportedly receiving the appropriate treatment (9).

Guidelines recommend using CVD risk assessment equations to guide prevention and

management (11). Despite this, it is often not integrated into clinicians’ daily routine. In one

study, the majority of the patients attending physicians’ clinics reported that they had never

undergone cardiovascular risk assessment (11). Taken together, the high prevalence of CVD and

suboptimal assessment and management of risk factors indicate the need to consider alternative

approaches to this major public health problem.

Community pharmacists are accessible primary healthcare professionals who frequently see

patients with chronic diseases (12); as such, they are well positioned to identify patients with/at

high risk for CVD, determine their CVD risk and assist in their disease management. The

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efficacy of pharmacists’ intervention on individual CVD risk factors has been well demonstrated

(13-17), however their role in targeting multiple risk factors to reduce overall CVD risk has not

been determined. Expansion of the scope of practice of pharmacists; such as in Alberta, Canada,

provides an opportunity for pharmacists to independently prescribe and order laboratory tests.

These added privileges might help to address the phenomenon of therapeutic inertia (18) in the

community.

The purpose of the RxEACH study was to develop and implement a broad-based community

pharmacist-initiated vascular risk reduction case-finding and intervention program in patients at

high risk for cardiovascular disease and to evaluate its impact on risk for cardiovascular events.

Methods

The RxEACH study was a multicenter randomized controlled trial with the patient as the unit of

randomization (Figure 1), conducted in 56 community pharmacies in the province of Alberta,

Canada.

We included adults (≥18 years of age) who were at high risk for cardiovascular events: those

with diabetes, chronic kidney disease (estimated glomerular filtration rate (eGFR) of

<60mL/min/1.73m2 upon 2 consecutive measurements within a 3-month period or albumin to

creatinine ratio (ACR) of ≥30 (single measurement), or between 3-29 on 2 consecutive

measurements within a 3-month period), had established atherosclerotic vascular disease (via

patient health records or self-report) including cerebrovascular disease (prior stroke or transient

ischemic attack), cardiovascular disease (myocardial infarction, acute coronary syndrome, stable

angina, or revascularization), or peripheral arterial disease (symptomatic and/or ankle brachial

index <0.9), or primary prevention patients with multiple risk factors and Framingham risk score

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>20%. In addition, subjects must have had at least one uncontrolled risk factor (blood pressure

>140/90 or >130/80mmHg if diabetic, LDL-c >2.0 mmol/L, HbA1c >7.0%, or current smoker).

We excluded patients who were unwilling to participate or provide written informed consent,

unwilling or unable to participate in regular follow-up visits, or were pregnant.

Pharmacists used a proactive case-finding strategy (19), to identify potential participants, which

focused on their high-risk patients who were receiving metformin (as a marker for Type 2

diabetes), clopidogrel or ASA (for coronary artery disease), antihypertensive agents, statins for

dyslipidemic patients, and known smokers. In addition, pharmacists used newspaper or other

advertising outlets, or in pharmacy heart health clinics.

After obtaining written informed consent, patients were randomized in a 1:1 ratio to intervention

or usual care groups using a centralized secure website at the data management center

(EPICORE Centre). The randomization scheme was blocked (random block size) and stratified

by pharmacy.

Baseline assessment of cardiovascular risk factors was conducted and the patient’s family

physician was informed of the patient’s inclusion into the study. Any subsequent changes made

to participants’ treatment regimens were also communicated to the physician (as per usual

pharmacist practice in Alberta).

Intervention: Patients randomized to the intervention group received a Medication Therapy

Management consultation from their pharmacist (in Alberta, called a Comprehensive Annual

Care Plan or Standard Medication Management Assessment), which included:

• Patient assessment (blood pressure measurement according to Canadian Hypertension

Education Program guidelines (20), waist circumference, weight and height

measurements)

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• Laboratory assessment of HbA1c, fasting cholesterol profile (if not done within the past 3

months) eGFR and ACR (if not done within the past 12 months)

• Individual assessment of CVD risk and education about this risk:

o The cardiovascular risk was calculated using an online tool. Our system used the

appropriate risk engine based on the patient’s medical history. The United Kingdom

Prospective Diabetes Study (UKPDS) risk engine (21), the International model for

prediction of recurrent cardiovascular disease (22) and Framingham (23) were used

for patients with diabetes, previous vascular disease, CKD or primary prevention,

respectively. In the case where a patient had more than one co-morbidity, the risk

engine estimating the highest risk was used.

o Discussion of CVD risk with the patient using the interactive online tool to explain

his/her individual cardiovascular risk and targets for intervention (see

www.epicore.ualberta.ca/CVrisk) and healthy lifestyle options.

• Providing treatment recommendations based upon the most up to date Canadian clinical

practice guidelines for cardiovascular risk factors

• Prescription adaptation(s), and/or de novo prescriptions where necessary to meet lipid,

blood pressure and glycemic control targets and smoking cessation.

• Regular communication with the patient’s family physician after each contact with the

patient

• Regular follow-up with all patients a minimum of every 3-4 weeks for 3 months

Pharmacists in Alberta can bill the provincial health plan for providing such services.

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Usual care: Patients randomized to the usual care group received usual pharmacist care with no

specific interventions for 3 months. At the end of the 3 months of the usual care period, all

patients were offered the intervention outlined above.

Outcomes: The primary outcome was the difference in change in estimated cardiovascular risk

between intervention and usual care groups at 3 months. We defined cardiovascular risk as the

risk for future cardiovascular events (e.g., myocardial infarction, revascularization,

cardiovascular death) as calculated by the validated risk engines as described above. Secondary

outcomes included the difference in change in individual cardiovascular risk factors between

intervention and usual care groups at 3 months, including systolic and diastolic blood pressure,

LDL-c, HbA1c, and smoking cessation.

Sample size and analytical plan: Using the information from Grover and colleagues (24)

(baseline CVD risk and standard deviation), a reduction in estimated risk for cardiovascular

events of 25% in the intervention group and 17.5% in the control group (absolute difference of

7.5%), assuming 90% power and a 2-sided alpha of 0.05, required an overall sample size of 674

patients (337 in each group). This sample size was inflated to 704 (352 in each group) to account

for possible dropouts, losses to follow-up and withdrawals of consent.

All analyses were conducted on an intention to treat basis. In the case of missing data, a last

observation carried forward approach was used. The primary outcome was analyzed using

ANCOVA, adjusting for center effect and all covariates with p<0.25 between groups. Secondary

outcomes of blood pressure, dyslipidemia and HbA1c were analyzed using ANCOVA, adjusting

for center effect and all covariates with p<0.25 between groups. Smoking cessation was analyzed

using Chi Square.

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Data and trial management and biostatistical support was provided by EPICORE Centre

(www.epicore.ualberta.ca).

Pharmacist Training: Pharmacist training was based on the current Canadian guidelines (25-

30). The research team developed an online training program that was reviewed internally and

externally for content validity. The training program was hosted online at the Faculty of

Pharmacy and Pharmaceutical Sciences, University of Alberta server and provided at face-to-

face regional meetings. The training program included modules on case-finding, cardiovascular

risk calculation and patient communication of cardiovascular risk, chronic kidney disease,

hypertension, dyslipidemia, diabetes, smoking cessation, diet and lifestyle management, and

documentation of care plans for remuneration by Alberta Health. A hotline was made available

for participating pharmacists to connect them with experts in cardiovascular risk reduction and

study procedures.

RxEACH was approved by the Health Research Ethics Boards of the University of Alberta and

the University of Calgary and was registered on clinicaltrials.gov (NCT01979471).

Results

The RxEACH trial began enrolment on January 27, 2014, with 56 sites (pharmacies) involved

(see Acknowledgements for list of pharmacist investigators). A total of 913 subjects were

screened, 827 of whom were eligible. We randomized 723; 353 were assigned to usual care and

370 to intervention (Figure 1). The last patient was enrolled June 3, 2015 and follow-up was

completed on September 24, 2015. There were 10 early withdrawals in the usual care group

(2.8%) and 19 in the intervention group (5.1%), mostly because of losses to follow-up in both

groups.

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Baseline characteristics are shown in Table 1. The two treatment groups were well balanced in

demographic and clinical parameters (Table 1). The average age was 62 (standard deviation, SD

12) years and 58% were male. In terms of CVD risk factors, 84% had hypertension, 83% had

dyslipidemia, 64% reported sedentary lifestyle, 27% were smokers, mean body mass index was

34 (SD 13.2). In addition, 79% had diabetes, 40% had chronic kidney disease, and 30% had

atherosclerotic vascular disease (stroke/transient ischemic attack, acute coronary syndromes,

angina, revascularization or peripheral arterial disease). A total of 53 patients were high risk

primary prevention (Framingham risk >20%). The inclusion criteria for the study required the

presence of at least one poorly controlled risk factor. Of all the patients enrolled, 79% of those

with diabetes had poor glycemic control (as measured by HbA1c), 72% had poorly controlled

blood pressure, 59% had poorly controlled dyslipidemia, and 27% were smokers (categories not

mutually exclusive).

At the baseline visit, mean blood pressure was 137 (SD 20) / 81 (SD 12), total cholesterol was

4.3 (SD 1.0) mmol/L, LDL cholesterol was 2.4 (SD 1.2) mmol/L and HDL cholesterol was 1.2

(SD 0.4) mmol/L. In the 573 patients with diabetes, the average duration of diabetes was 12 (SD

11) years, and mean HbA1c was 8.6 (SD 2)%. Estimated baseline cardiovascular risk was 26.6

(SD 19.3)% in the usual care group and 25.6 (SD 17.8)% in the intervention group (Table 1).

Estimated cardiovascular risk changed over the 3 month follow-up period from 26.6 (SD 19.3)%

to 25.9 (SD 19.6)% in the usual care group, compared to 25.6 (SD 17.8)% at baseline to 20.5

(SD 15.9)% in the intervention group. This, when adjusted for the center effect, corresponded to

a relative decrease in estimated cardiovascular risk of 21% (an absolute difference of 5.37, 95%

CI -6.56, -4.17, p<0.001) (Figure 2), the primary outcome.

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Table 2 outlines medication use and changes that were made in the study population, and show

more changes in hypgoglycemic, hypertension and dyslipidemia medications in the intervention

group. Secondary outcomes are shown in Table 3. The difference in LDL cholesterol was -0.2

(95% CI -0.31, -0.08, p=0.001) mmol/L, in systolic blood pressure was -9.37 (95% CI -11.07, -

7.67, p<0.001) mmHg, in diastolic blood pressure was -2.92 (95% CI -4.21, -1.62, p< 0.001)

mmHg, in HbA1c (in diabetics only) was -0.92 (95% CI -1.12, -0.72, p<0.001)%. There were

20.2% fewer smokers (95% CI 9.9, 30.4, p<0.001) in the intervention group. Figure 3 shows

achievement of targets for LDL cholesterol, blood pressure, HbA1c and smoking, with the

intervention group showing improvements across all categories. Body mass index changed from

34.08 (SD 15.3) to 32.9 (SD 8.0) in the usual care group, and from 33.27 (SD 10.8) to 32.6 (SD

8.8) in the intervention group. There were no adverse events reported during the trial.

Discussion

Cardiovascular diseases remain the most important causes of death and disability worldwide (1).

While the risk factors for cardiovascular disease are well known, poor identification of those at

risk and poor control of these factors remains an enigma (5-10). In the RxEACH study, we found

that engaging community pharmacists in identifying at-risk candidates (case finding) and

managing their cardiovascular risk factors using an advanced scope of practice that included

prescribing and ordering laboratory tests, resulted in a 21% reduction in their risk for

cardiovascular events in only 3 months. As pharmacists are highly accessible primary healthcare

providers, this could have major public health implications in reducing the burden of CVD if

these practices were widely adopted.

Our results add to an already rich literature on the efficacy of pharmacist care on the individual

components of cardiovascular risk factors. These non-prescribing trials have been elegantly

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summarized in a meta analysis by Santschi and colleagues (15), who noted significant

improvements in dyslipidemia, hypertension, and smoking cessation. Furthermore, our group has

recently published trials of independent pharmacist prescribing in patients with poorly controlled

diabetes (31) and hypertension (32). To our knowledge, RxEACH is the first large scale

randomized trial of overall cardiovascular risk reduction, targeting multiple risk factors together.

O’Donovan and colleagues conducted a literature review to study pharmacist’s use of CV

screening tools and reported that the majority of the screenings were either opportunistic or

referral-based. They highlighted the lack of proactive case finding approach in such programs

(33). Our results take their findings to the next level. They are also consistent with the findings

of Mc Namara and colleagues (34, 35) who conducted a pilot longitudinal pre-and-post-test

study to evaluate the impact of a medication review and educational intervention on patients’ CV

risk in a community pharmacy setting, and reported a significant CV risk reduction over a 6-

month period. RxEACH is also a validation of the merits of a broader scope of practice for

pharmacists, in this case, of independent prescribing authority and ability to order and interpret

laboratory tests. Indeed, we reported recently that of the patients receiving baseline assessments

in RxEACH, 290 had chronic kidney disease, of whom 40% had previous unrecognized chronic

kidney disease (i.e., was identified by the pharmacist in the course of targeted screening for

CKD) (36, 37). As a practice-based trial of an approach to cardiovascular risk reduction, we can

only speculate that the improvements seen were due to changes in medication use (as seen in

Table 2), dosage adjustment, and improved adherence to lifestyle and medications – all of which

were enhanced by the guidelines-recommended follow-up visits performed by the pharmacists.

A number of strengths and limitations warrant mention. Use of a randomized controlled design

portends a high level of causal inference. In terms of sustainability of the intervention, we used

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the medication management remuneration program already established by the Alberta

government (and also present in most US states) which reimburses pharmacists for their care.

Indeed, our study could be seen as a validation of these medication management programs. With

respect to limitations, our follow-up duration was relatively short. The reason for this short

duration was a compromise decision made because investigators (pharmacists) had expressed

concerns over “usual care” in these high-risk patients. We decided to shorten the follow-up

duration to 3 months, and allow usual care allocated patients to cross over to receive the

intervention after 3 months. While 3 month outcomes for smoking cessation are rather short (and

could certainly be subject to recidivism), they may bias against the intervention because of the

short duration to achieve reductions in LDL cholesterol (which respond slowly to medication

changes), blood pressure (which often takes several weeks to see the full effects of a medication

change) and HbA1c (which takes up to 3 months to show full effects of changes in glycemic

control). As such, we may be underestimating the impact on these parameters. Another potential

limitation is generalizability to other pharmacists in other jurisdictions. While pharmacists in the

province of Alberta certainly have a broad scope of practice which includes independent

prescribing and the ability to order laboratory tests, many jurisdictions in North America do

allow for medication management reviews, ability to adjust and adapt prescriptions, make

recommendations to physicians, and receive remuneration for these activities. Training on

cardiovascular risk reduction is widely available and should not limit generalizability of our

findings. We used risk estimation equations for our primary outcome. We acknowledge that

these equations were not designed to measure change. Nevertheless, we wished to capture the

overall effect of a cardiovascular risk reduction program and reported a relative reduction in risk

(as such, biases and limitations would presumably equally present at baseline and at the end of

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follow-up for all patients). Similarly, the lack of a validated equation for patients with CKD

almost certainly underestimated the risk for these patients, but again, reporting of a relative

reduction in risk should alleviate this concern. With regards to smoking cessation, we used

patient self report and assessment by the pharmacist to determine smoking status rather than

methods such as carbon monoxide detection. Finally, due to the nature of the intervention, we

could not blind investigators to treatment allocation.

Cardiovascular diseases remain important public health problems in the United States,

Canada and worldwide (1). As such, our study demonstrating the impact of an advanced scope of

pharmacist practice might have important public health implications. Indeed, engaging

pharmacists could bring another 450,000 helping hands in the United States and Canada to help

reduce the burden of cardiovascular disease. It is important to note that the reductions in

cardiovascular risk were achieved on top of (not instead of) usual physician care.

Interprofessional communication and collaboration remain key. We would encourage

policymakers to consider broadening the scope of practice of pharmacists (like in Alberta) and

for pharmacists and pharmacy professional organizations to seize these opportunities for the

betterment of patient care.

Conclusions

Cardiovascular diseases and their associated risk factors remain an important public health

problem. In the RxEACH study, we demonstrated that pharmacists with an advanced scope of

practice could identify patients with poorly controlled risk factors and significantly reduce their

risk for cardiovascular events. Adopting these practice innovations could have major public

health benefits.

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Figure Legends

Figure 1: Case-finding, enrolment, randomization and completeness of follow-up. This

figure describes the screening and randomization and follow-up of patients in the study.

Figure 2: Primary Outcome: Effect of pharmacist care on estimated risk for

cardiovascular events. This figure outlines the effect of the pharmacist care intervention on

reduction in estimated risk for cardiovascular events from baseline to 3 months in patients

randomized to usual care or intervention groups. Relative risk reduction between usual care

and intervention was 21% (a 5.37% absolute reduction, 95% CI -6.56, 4.17, p< 0.001), after

adjustment for baseline values and the center effect. Est. CV Risk = estimated risk for

cardiovascular events

Figure 3: Achievement of cholesterol, blood pressure and glycemic targets and smoking

status at 3 months. This figure shows the number and proportion of patients achieving the

recommended targets for LDL-c (<2.0 mmol/L), blood pressure (<140/90mmHg or

<130/80mmHg if diabetic), glycemic control via HbA1c (<7,0%), and current smoking status

at the end of follow-up. In all cases, pharmacist care (intervention) resulted in significantly

more patients reaching targets: for LDL-c, an absolute difference of 9.9% (95% CI 2.2, 17.5,

p=0.012); for BP, an absolute difference of 23.1% (95% CI 16.0, 30.1, p<0.001); for HbA1c,

an absolute difference of 17.6% (95% CI 9.9, 25.4, p<0.001); and for smoking, an absolute

difference of 6.9% (95% CI 0.6, 13.2, p=0.032).

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Table 1: Baseline Demographics Baseline Characteristics Usual Care (n=353) Intervention (n=370)

Age, mean, y (SD) 61 (12) 62 (12)

Gender (% male) 58% 57%

Hypertension 82% 85%

Dyslipidemia 82% 83%

Smoking 28% 26%

Sedentary lifestyle 64% 64%

BMI, mean (SD) 34 (15) 33 (11)

Estimated glomerular

filtration rate

mL/min/1.73m2

79.5 (24.4) 78.7 (23.1)

Random ACR (median,

interquartile range) 2.0 (0.8, 7.5) 1.8 (0.9, 6.6)

Diabetes 287 (81%) 286 (77%)

Chronic kidney disease 147 ( (40%) 143 (41%)

Atherosclerotic vascular

disease 101 (28.6%) 119 (32.2%)

Stroke/TIA 11% 8%

Acute coronary

syndromes 7% 7%

Angina 8% 9%

Revascularization 8% 12%

Peripheral arterial

disease 7% 8%

Blood Pressure

Systolic, mmHg 137 (19) 137 (20)

Diastolic, mmHg 81 (12) 81 (11)

Total cholesterol, mmol/L 4.37 (1.3) 4.5 (1.4)

LDL-cholesterol, mmol/L 2.34 (1.1) 2.47 (1.2)

HDL-cholesterol, mmol/L 1.17 (0.38) 1.18 (0.41)

High Risk Primary

Prevention (Framingham

Risk >20%)

28 (7.6%) 25 (7.1%)

Heart failure 13% 5%

Atrial fibrillation 7% 6%

Social factors

Married/Common law 68% 69%

High school or higher 87% 92%

Working for pay/profit 47% 43%

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Caucasian 76% 75%

No alcohol use 59% 55%

No specific diet 64% 68%

Study Qualification:

Uncontrolled HbA1c 230/287 (80.1%) 225/286 (78.7%)

Uncontrolled blood

pressure 257/353 (72.8%) 266/370 (71.9%)

Uncontrolled LDL-c 185/330 (56.1%) 209/346 (60.4)

Current smoking 99/353 (28.1%) 97/370 (26.2%)

Estimated cardiovascular

risk 26.6% (19.3) 25.6% (17.8)

LDL = low density lipoprotein, HDL = high density lipoprotein All values are means (and standard deviation, SD) unless otherwise indicated.

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Table 2: Medication Use and Changes

Medications

Baseline

Usual care

Final

Usual care

Baseline

Intervention

Final

Intervention

Hypoglycemic

Medications

N=287 N=282 N=286 N=271

No Medication

19

(6.6%)

13

(4.6%)

26

(9.1%)

12

(4.4%)

1 Medication

121

(42.2%)

116

(41.1%)

115

(40.2%)

100

(36.9%)

2 Medications

99

(34.5%)

106

(37.6%)

97

(33.9%)

96

(35.4%)

3 Medications

43

(15.0%)

44

(15.6%)

42

(14.7%)

52

(19.2%)

4 Medications

4

(1.4%)

2

(0.71%)

5

(1.8%)

8

(3.0%)

5 Medications

1

(0.4%)

1

(0.35%)

1

(0.4%)

3

(1.1%)

Median Number of

Medications/Patient

2

(1-2)

2

(1-2)

2

(1-2)

2

(1-2)

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(Interquartile

Range)

Mean Number of

Medications/Patient

(Standard

Deviation)

1.6

(0.89)

1.7

(0.84)

1.6

(0.93)

1.8

(0.96)

Patients With Any

Medication Change

-

59/282

(20.9%)

-

106/271

(39.1%)

Patients with

Dosage Change

Only

-

93/223

(41.7%)

-

67/165

(40.6%)

Hypertension

Medications

N=289 N=283 N=316 N=300

No Medication

30

(10.4%)

27

(9.5%)

19

(6.0%)

8

(2.7%)

1 Medication

91

(31.5%)

87

(30.7%)

111

(35.1%)

111

(37.0)

2 Medications

91

(31.5%)

84

(29.7%)

116

(36.7%)

100

(33.3%)

3 Medications 59 63 48 55

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(20.4%) (22.3%) (15.2%) (18.3%)

4 Medications

18

(6.2%)

20

(7.1%)

21

(6.7%)

25

(8.3%)

5 Medications 0 2 (0.7%) 1 (0.3%) 1 (0.3%)

Mean Number of

Medications/Patient

(Standard

Deviation)

1.8

(1.1)

1.9

(1.1)

1.8

(1.0)

1.9

(1.0)

Patients With Any

Medication Change

-

62/283

(21.9%)

-

86/300

(28.7%)

Patients With

Dosage Change

Only

-

29/221

(13.1%)

-

35/214

(16.4%)

Dyslipidemia

Medications

N=289 N=280 N=308 N=291

No Medication

80

(27.7%)

71

(25.4%)

89

(28.9%)

94

(22.0%)

1 Medication

196

(67.8%)

197

(70.4%)

202

(65.6%)

208

(71.5%)

2 Medications 11 11 17 19

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(3.8%) (3.9%) (5.5%) (6.5%)

3 Medications

2

(0.7%)

1

(0.4%)

0 0

Median Number of

Medications/Patient

(Interquartile

Range)

1

(0-1)

1

(0-1)

1

(0-1)

1

(1-1)

Mean Number of

Medications/Patient

(Standard

Deviation)

0.8

(0.54)

0.8

(0.51)

0.8

(0.53)

0.8

(0.51)

Patients With Any

Medication Change

-

24/280

(8.6%)

-

54/291

(18.6%)

Patients with

Dosage Change

Only

-

8/256

(3.1%)

-

10/237

(4.2%)

“Patients with any medication change” refers to patients who had any change (addition or discontinuation) of medication by their pharmacist. For example, this might include a change from fluvastatin to rosuvastatin. This category excludes those with dosage changes to existing medications. “Patients with dosage change only” refers to patients who had the dosage adjusted of their medication (either upwards or downwards) by their pharmacist. This category excludes changes to the medication from one drug to another or discontinuation of a medication. “Hypoglycemic medications”, “Hypertension Medications” and Dyslipidemia Medications” refer to only those patients with diabetes, hypertension and dyslipidemia, respectively (hence the

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different denominators). The “Final” visit column excludes patients not completing their final visit.

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Table 3: Secondary Outcomes: Changes in Individual Risk Factors

Risk Factor

Usual Care

Baseline

Usual Care

3 months

Intervention

Baseline

Intervention

3 months

Difference

(95% CI and p

value)

Systolic Blood

Pressure

(mmHg)

137.11

(19.42)

136.27

(17.32)

137.44

(19.68)

127.24

(13.80)

-9.37 mmHg

(-11.07, -

7.67;

p<0.001)

Diastolic Blood

Pressure (mmHg)

81.10

(12.09)

79.95

(11.46)

80.78

(11.43)

76.96

(10.49)

-2.92 mmHg

(-4.21, -1.62;

p<0.001)

LDL-c (mmol/L)

2.34

(1.13)

2.23

(1.02)

2.47

(1.20)

2.07

(0.96)

-0.2 mmol/L

(-0.31, -0.08;

p=0.001)

HbA1c (n = 573)

8.62

(1.96)

8.54

(1.93)

8.61

(1.86)

7.60

(1.43)

-0.92%

(-1.12, -0.72;

p<0.001)

Current smoking,

proportion (%)

99/353

(28.1%)

91/342

(26.6%)

97/370

(26.2%)

69/350

(19.7%)

-20.2%

(-9.9, -30.4;

p<0.001)

Data are presented as mean (SD) unless otherwise stated N = 353 usual care, 370 intervention, unless otherwise indicated

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LDL-c: low density lipoprotein cholesterol

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