A Cluster-Randomized Effectiveness Trial of a Physician-Pharmacist Collaborative Model to Improve Blood Pressure Control
The purpose of this study was to evaluate if a physician/pharmacist collaborative model would be implemented as determined by improved blood pressure (BP) control in primary care medical offices with diverse geographic and patient characteristics and whether long-term BP control could be sustained. Prospective, cluster-randomized trial of 32 primary care offices stratified and randomized to control, 9-month intervention (brief), and 24-month intervention (sustained). We enrolled 625 subjects with uncontrolled hypertension; 54% from racial/ethnic minority groups and 50% with diabetes mellitus or chronic kidney disease. The primary outcome of BP control at 9 months was 43% in intervention offices (n=401) compared with 34% in the control group (n=224; adjusted odds ratio, 1.57 [95% confidence interval, 0.99-2.50]; P=0.059). The adjusted difference in mean systolic/diastolic BP between the intervention and control groups for all subjects at 9 months was -6.1/-2.9 mm Hg (P=0.002 and P=0.005, respectively), and it was -6.4/-2.9 mm Hg (P=0.009 and P=0.044, respectively) in subjects from racial or ethnic minorities. BP control and mean BP were significantly improved in subjects from racial minorities in intervention offices at 18 and 24 months (P=0.048 to P<0.001) compared with the control group. Although the results of the primary outcome (BP control) were negative, the key secondary end point (mean BP) was significantly improved in the intervention group. Thus, the findings for secondary end points suggest that team-based care using clinical pharmacists was implemented in diverse primary care offices and BP was reduced in subjects from racial minority groups. URL: http://clinicaltrials.gov/ct2/show/NCT00935077. Unique identifier: NCT00935077. © 2015 American Heart Association, Inc.
A Cluster-Randomized Effectiveness Trial of a
Physician-Pharmacist Collaborative Model to Improve Blood
Barry L. Carter, PharmD; William Clarke, PhD; Gail Ardery, PhD; Cynthia A. Weber, PharmD;
Paul A. James, MD; Mark Vander Weg, PhD; Elizabeth A. Chrischilles, PhD; Thomas Vaughn, PhD;
Brent M. Egan, MD; on behalf of the Collaboration Among Pharmacists Physicians To Improve
Outcomes Now (CAPTION) Trial Investigators*
Abstract—Numerous studies have demonstrated the value of team-based care to improve blood pressure (BP) control, but
there is limited information on whether these models would be adopted in diverse populations. The purpose of this study
was to evaluate whether a collaborative model between physicians and pharmacists can improve BP control in multiple
primary care medical offices with diverse geographic and patient characteristics and whether long-term BP control can
be sustained. This study is a randomized prospective trial in 27 primary care offices first stratified by the percentage of
underrepresented minorities and the level of clinical pharmacy services within the office. Each office is then randomized
to either a 9- or 24-month intervention or a control group. Patients will be enrolled in this study until 2012. The results
of this study should provide information on whether this model can be implemented in large numbers of diverse offices,
if it is effective in diverse populations, and whether BP control can be sustained long term.
Clinical Trial Registration—URL: http://www.clinicaltrials.gov. Unique identifier: NCT00935077.
(Circ Cardiovasc Qual Outcomes. 2010;3:418-423.)
Key Words: hypertension
lood pressure (BP) control and guideline adherence are
low in the United States, with the lowest rates among
racial minorities and people of lower socioeconomic status.
The reasons for poor control include patient, physician, and
structural factors, but suboptimal treatment regimens and
clinical inertia are common causes.
The current debate on healthcare reform frequently notes
the need to develop the medical home for the delivery of
The physician-pharmacist collaborative model
(PPCM) is consistent with the medical home
in which the
patient has an ongoing relationship with a personal physician
who delegates responsibility to the pharmacist to assist with
achieving BP control. Use of this model has achieved high BP
control rates in 2 studies, primarily through resolving clinical
inertia. In 1 study (n⫽179), patients from 2 intervention clinics
achieved 89% BP control compared to 54% in 2 control clinics.
The mean difference in systolic BP (SBP) was 8.7 mm Hg (95%
CI, 4.4 to 12.9 mm Hg). In a second study, among 402 patients
from 6 medical offices who achieved BP control, 62.9% were
from intervention clinics compared to 29.9% in the control
group (odds ratio, 3.2; 95% CI, 2.0 to 5.1; P⬍0.01).
A systematic review of controlled trials of team-based care
found significant improvements in BP control.
were small efficacy studies, did not use a standardized research-
measured BP, did not use intention-to-treat analysis, or included
few patients from minority groups.
The present study is designed to determine whether PPCM
will be adopted and implemented in diverse medical offices with
large minority populations and whether BP control deteriorates
after discontinuation of a 9-month intervention compared to a
24-month intervention. This effectiveness, or pragmatic trial,
will evaluate variation and provider attitudes to adoption of
PPCM following the Theory of Planned Behavior.
We will conduct a 5-year prospective, cluster-randomized, multi-
center clinical trial in 27 clinics from 13 states in the United States.
All clinics employ clinical pharmacists, and 47% of the patients are
Clinics were stratified and then ran-
domized to a 9-month PPCM arm (n⫽219), 24-month PPCM arm
(n⫽219), or control group (n⫽219) that also includes a distracter
From the Department of Pharmacy Practice and Science (B.L.C., G.A., C.A.W.), College of Pharmacy; Department of Family Medicine (B.L.C.,
P.A.J.), Carver College of Medicine; Department of Biostatistics (W.C.), College of Public Health; Department of Internal Medicine (M.V.W.), Carver
College of Medicine; Department of Epidemiology (E.A.C.), College of Public Health; Department of Health Management & Policy (T.V.), College of
Public Health; and Organizations, Systems, and Community Health Area (T.V.), College of Nursing, University of Iowa, Iowa City, Iowa; Iowa City
Veterans Administration (B.L.C., M.V.W.), Iowa City, Iowa; and Department of Medicine (B.M.E.), Medical University of South Carolina, Charleston, SC.
*A list of all CAPTION trial investigators is provided in the Appendix.
The online-only Data Supplement is available at http://circoutcomes.ahajournals.org/cgi/content/full/3/4/418/DC1.
Correspondence to Barry L. Carter, PharmD, Room 527, College of Pharmacy, University of Iowa, Iowa City, IA 52242. E-mail firstname.lastname@example.org
© 2010 American Heart Association, Inc.
Circ Cardiovasc Qual Outcomes is available at http://circoutcomes.ahajournals.org DOI: 10.1161/CIRCOUTCOMES.109.908038
intervention for asthma (Figure 1) (see online-only Data Supple-
ment). A study coordinator in each clinic will enroll 24 subjects with
hypertension who will be followed for 24 months (n⫽648). In
addition, we will perform a retrospective chart review for another
486 subjects (18 per clinic) with hypertension that will serve as an
observational cohort (pure control). The purpose of the observational
cohort is to determine whether the intervention diffuses into the rest
of the practice, even for patients not enrolled in the trial.
The primary hypothesis for the study is that BP control at 9
months will be significantly greater in patients from clinics random-
ized to the 2 intervention groups compared to the control group. The
secondary aims will compare mean BP among study arms and in
minority groups and patients from lower socioeconomic groups and
will evaluate the association between provider attitudes to deliver
PPCM by mean BP and BP control rates.
The study will be conducted in National Interdisciplinary Primary
Care Practice Based Research Network medical offices. Features of
the medical offices were previously published and showed that
85.4% are located in family medicine residencies, 10.4% in internal
medicine residencies, and 4.2% in faculty practices.
percent of the offices used electronic medical records when surveyed
The mean number of providers were 10 attending
physicians, 23 resident physicians, 6 nurses, 5 medical assistants, 0.4
nurse practitioners, 0.4 physician assistants, 0.7 psychologists, 0.3
social workers, 0.4 dieticians, and 0.4 patient educators.
Only 2 of the 27 offices have pharmacies. All 27 offices have clinical
pharmacists (mean, 1.9 per clinic) who are faculty in the office and
are employed primarily to provide education for physicians and
patient care. They spend an average of 2 days per week (0.4 clinical
full-time equivalents) in direct patient care and cover clinic hours
an average of 75% of the time. Most have a PharmD degree (96%)
and a postdoctoral residency or fellowship (78%), and 43% are
board-certified pharmacotherapy specialists. Seventy percent of
clinics have had clinical pharmacy services for ⬎5 years.
Patient revenue is used to cover pharmacist salaries in 22% of
The mean racial/ethnic population of these clinics is 26% blacks and
21% Hispanics. We expect to recruit at least 40% of patients from
these minority groups. Payers include Medicaid or government
assistance (28%), Medicare (22%), private insurance (34%), no
insurance (12%), and other (4%).
We used a validated survey instrument
to score clinical pharmacy
services based on the extent of direct patient care services provided
in the medical office. Clinic scores fell into 2 distinct levels similar
to previous findings.
Clinics were stratified based on the phar-
macy structure scores (low and high) and percentage of minority
patients (⬍44% versus ⱖ44%).
Data and Safety Monitoring
A data and safety monitoring board was appointed following
National Heart, Lung, and Blood Institute guidelines and includes
internationally recognized experts in hypertension and team-based
care models. The data and safety monitoring board will meet at least
once a year to review the rate of patient recruitment, evaluate the
safety of the study, and make recommendations to the investigators
to improve the conduct of the study.
Providers in clinics randomized to the intervention arms received
training from 1 investigator (B.L.C.) on BP guidelines
to overcome clinical inertia and suggested methods of communica-
tion between physicians and pharmacists. Eight regional training
sessions were conducted between September 2009 and January 2010
and were delivered to 1 pharmacist and 1 physician investigator from
each medical office in train-the-trainer sessions. Separate training
programs occurred for providers from clinics randomized to either
the BP intervention or usual care (alternative asthma intervention).
The trainers also included a physician-pharmacist team from 1
Figure. Study design. HTN indicates hypertension; DCC, data coordinating center.
Carter et al Pharmacist Model To Improve Blood Pressure Control 419
community-based family medicine program that successfully imple-
mented the intervention model in a previous study.
uals encouraged physicians to improve participation of providers;
instilled confidence and enthusiasm; addressed strategies to over-
come barriers to BP control; and discussed methods to effectively
overcome clinical inertia, adverse drug reactions, and poor medica-
One to 3 months after the train-the-trainer session, each physician-
pharmacist pair delivered the same training program for all providers
in their own clinic. Pharmacists in clinics randomized to the 9-month
BP intervention will provide training sessions with their physicians
twice a year for 2 years, whereas those randomized to the 24-month
intervention will provide training sessions for 3 years.
Following the initial training sessions, 2 investigators will conduct
a telephone conference with each physician-pharmacist pair to
discuss questions or issues that the providers were not able to answer
regarding the intervention. The investigators will continue to support
all offices quarterly the first year, and twice a year in year 2 and year
3 (for clinics randomized to the long-term BP intervention).
Study Coordinator Training
A study coordinator (registered nurse, licensed practical nurse, or
medical assistant) employed in each medical office will enroll
patients, collect study data, and abstract medical records for the
observational cohort. All coordinators completed human subjects
education and were trained in Iowa City, Iowa, in December 2009 on
the Web-based case report forms that will be used on the secure Web
site operated by the study data coordinating center.
One investigator (B.L.C.) provided training and certification on
proper BP measurement technique using an automated Omron HEM
Study monitors from the data coordinating center
will make site visits to each medical office at least annually to
evaluate data fidelity and will recertify each research nurse in BP
measurement at each monitoring visit.
The suggested PPCM model will specify recommended visit fre-
quency and activities. However, because this is an effectiveness
study, strict adherence to the model and intervention schedule will
not be required. Instead, we will encourage the use of the model and
then measure the extent to which it is implemented. The pharmacist
will be asked to document all visits, medication recommendations
made to the physician, recommendations accepted by the physician,
and the time required to complete various steps in the study visit.
The therapeutic strategies will be based on the Seventh Report of
the Joint National Committee on Prevention, Detection, Evaluation,
and Treatment of High Blood Pressure,
and the BP goal will be
⬍140/90 mm Hg for patients with uncomplicated hypertension and
⬍130/80 mm Hg for patients with diabetes or chronic kidney disease.
(We will modify these goals if the Eighth Report of the Joint National
Committee on Prevention, Detection, Evaluation, and Treatment of
High Blood Pressure changes the them.)
At baseline, the pharmacist will review the medical record and
perform a structured interview with the patient, including a detailed
medication history; assessment of patient knowledge of BP medica-
tions, purpose of each medication, goals of therapy, medication
dosages and timing, and potential medication side effects; potential
contraindications to specific BP medications; and expectations for
future dosage changes, monitoring, and issues that may become
future barriers to BP control (eg, side effects, nonadherence, patient
self-efficacy). The pharmacist will supply a wallet card listing all
medications and doses, contact phone numbers, and BP goals.
The pharmacist will create a care plan with treatment recommen-
dations for the physician at the baseline visit so that an immediate
change in medication can be made.
If the physician agrees with
the care plan or makes a modification in the plan, the pharmacist will
implement the plan. The study case report forms will capture
whether the physician accepted the pharmacist’s recommendations.
The suggested PPCM model includes structured face-to-face visits
with the patient at baseline, 1, 2, 4, 6, and 8 months; a telephone call
at 2 weeks; and additional visits if BP remains uncontrolled. If BP is
controlled, the recommended action will be for the pharmacist to
schedule the patient for routine follow-up every 3 to 6 months.
BP control is lost, the pharmacist is encouraged to increase visit
frequency similar to the baseline schedule.
Pharmacists in control sites will not provide the intervention for
patients with hypertension but will continue to provide curbside
consultations if physicians specifically ask questions about patients
with hypertension. Instead, pharmacists in the control group will be
providing an alternative intervention for patients with asthma (online
Patients will be eligible if they are English- or Spanish-speaking
men or women aged ⬎18 years with hypertension and uncontrolled
BP defined as ⱖ140 mm Hg SBP or ⱖ90 mm Hg diastolic BP (DBP)
for uncomplicated hypertension or ⱖ130 mm Hg SBP or ⱖ80 mm Hg
DBP for patients with diabetes or chronic kidney disease. Qualification
will be based on a seated BP (average of the second and third reading)
as measured in the office by the study coordinator. Patients will be
excluded with current signs of hypertensive emergency (acute angina,
stroke, or renal failure); SBP ⬎200 mm Hg or DBP ⬎114 mm Hg;
history of myocardial infarction, stroke, or unstable angina in the prior
6 months; systolic dysfunction with a left ventricular ejection fraction
⬍35% as documented by echocardiography, nuclear medicine study, or
ventriculography; glomerular filtration rate ⬍20 mL/min or proteinuria
⬎1 g/day; cirrhosis, hepatitis B or C infection, or laboratory abnormal-
ities (serum alanine aminotransferase or aspartate aminotransferase ⬎2
times control or total bilirubin ⬎1.5 mg/dL) in the prior 6 months;
pregnancy; pulmonary hypertension or sleep apnea (unless treated by
continuous positive airway pressure); life expectancy estimated at ⬍2
years; residence in a nursing home or dementia; and inability to give
informed consent or impaired cognitive function.
The study has been designed to minimize selection bias. Potential
patients will be identified from a list generated from each clinic and
then randomized for inclusion by the data coordinating center. Study
coordinators will receive the ordered lists and then review the
medical records in this order and invite a patient to participate if the
study criteria are met. The study coordinator will continue this
process until 24 patients are consented and enrolled. We will record
the reasons patients declined, did not meet criteria, or dropped from
the study in order to evaluate the generalizability of the selected
subjects to the entire population.
If a potential subject only speaks Spanish, we will use bilingual
coordinators or translators within the office to explain the study and
assist with obtaining informed consent. The consent form and scripts
have been translated into Spanish. All patient questionnaires are
scripted to ensure consistent administration.
The study coordinator will measure BP in the sitting position after
at baseline, 6, 9, 12, 18, and 24 months.
study coordinator will collect the following at baseline: height,
weight, and pulse; the duration of hypertension; presence of other
cardiovascular risk factors, symptoms, and adverse drug reactions;
medication adherence; sociodemographics; comorbidities; current
medications and dose, how the patient actually took the medication;
and an evaluation of medication adherence using validated instru-
The timing of collection of these variables are shown in
Patients enrolled in the control group will receive usual care from
their physicians. Patients in intervention clinics will be referred to
the intervention pharmacist.
Study monitors from the data coordinating center will perform site
visits to compare the completeness of the case report forms with the
medical records and the Web-based database. Each site will be
visited at least once a year to evaluate data fidelity.
Observational Cohort (Pure Control Group)
The purpose of the retrospective observational cohort will be to
evaluate whether the effect of the intervention using our previous
diffuses throughout the practice for patients not
actively enrolled in the study. Once 24 patients have been enrolled
into the prospective interventional study at a given site, the study
coordinator will identify another 18 patients who meet the same
inclusion criteria. Qualification in the retrospective observational
420 Circ Cardiovasc Qual Outcomes July 2010
cohort will be an index visit that occurred during the study period
and based on a qualifying BP on the last 2 clinic visits. Patients
in the observational cohort will not be consented or have any
study visits, and all data will be collected retrospectively by
medical record audit.
We recognize the hazard of comparing research BP values with
clinic-measured BPs, so these will not be compared to the prospec-
tive data in the analyses. However, by comparing the observational
cohort across all 3 study groups, we will be able to determine
whether PPCM diffuses to nonstudy patients to evaluate BP in the
absence of the Hawthorne effect.
Predictors of Implementation
The theoretical model we have used to predict physician and
pharmacist behavior to adopt PPCM is the Theory of Planned
We will determine the providers’ attitudes (do they
favor it), their social pressures (subjective norm), and whether they
feel in control of the action (perceived control).
instrument will be administered to physicians in all clinics prior to
patient enrollment and again at the end of the study.
Current procedural terminology codes for pharmacist medication
management have been developed but are not routinely recognized
At baseline and at the end of the study, we will ask
the pharmacists to provide for the most recent year the total
amount billed and collected for all clinical services and the total
amount billed and collected strictly for services related to hyperten-
sion. The amounts collected will be used as covariates to predict BP
We will evaluate and control for self-reported adherence at baseline,
9, and 24 months using a recently published strategy.
We will use a
symptom survey from our previous studies and evaluate symptoms
among the 3 study arms at baseline, 9, and 24 months.
Costs will be assigned to each BP medication at baseline, 9, and
24 months. All clinic visits (including pharmacist), telephone follow-
up, emergency department visits, hospitalizations, and laboratory
procedures will have costs assigned, and the 3 groups will be
compared using methodologies previously described.
costs as a function of differences in BP will be calculated at baseline,
9, and 24 months. These findings will be expressed as dollars per
incremental reduction in BP (mm Hg). We will compare the costs
associated with this intervention to that of other studies that have
estimated the value of controlled BP to society.
Formative evaluations will be conducted with physicians, phar-
macists, study coordinators, and office administrators once the study
has been completed. A detailed description of the formative evalu-
ations appears in the online supplement.
The primary end point is BP control at 9 months among study arms.
Secondary end points will include(1) BP control and mean BP
differences among groups at 12, 18, and 24 months; (2) between-
group comparison of BP control and mean BP in patients from
underrepresented minorities, education level, and household income;
(3)medication intensification; (4) provider-level variables as predic-
tors of mean BP and BP control; and(5) pharmacist-level variables
(billing and collections) as predictors of mean BP and BP control. A
separate analysis for items 1 to 5 will be conducted across the 3 arms
for patients in the observational cohort.
Sample size calculations assumed that there will be 1:1:1 random-
ization to 2 intervention arms and 1 control arm and that the primary
comparison is that of the BP control rate in the 2 intervention arms
combined with the BP control rate in the control arm. Effect sizes of
25% versus 60% at 6 months were determined from our previous
Sample sizes were computed to ensure that there would be a
sufficient number of minority group patients for a 5%-level test
(alpha) of proportions to achieve 90% power to detect a difference of
60% in the combined intervention arms versus 35% in the control
arm using the method described by Donner and Klar.
computes a sample size for independent observations then inflates
the sample size 15% to account for the correlation among patients in
the same clinic. Briefly, the sample size calculations inflate the
number of subjects needed for independent samples by a multipli-
cative factor to account for the correlation among subjects at the
same clinic. The required sample size is n'⫽m*(1⫹(n⫺1)
*), where m
is the sample size computed assuming independent samples, n is the
number of subjects in each clinic,
is an estimate of the dependence
among subjects in the same clinic, and n⬘ is the sample size adjusted to
take into account the correlation among subjects in a clinic. For
continuous responses (SBP and DBP), likelihood-based mixed models
with random patient effects will be fit in SAS Proc Mixed to incorporate
all available data from baseline through 9 months in an intention-to-treat
analysis. For BP control, a generalized estimating equation model using
the binomial distribution and the logit link was fit in SAS Proc Genmod,
accommodating the correlations across patients. This analysis accounts
for the correlation among subjects from the same clinical center. The
model will contain a term for treatment assignment (PPCM versus
control), baseline SBP, baseline DBP, and age. The analysis will provide
an estimate and 95% CI for the odds ratio of achieving BP control in the
combined intervention arms compared to the control arm adjusted for
any differences in baseline BP and age. These calculations suggested
that we would need to enroll 648 subjects in 27 clinics.
The primary comparison between the 3 groups at 9 months will
have a minimal detectable difference in BP control of 35% versus
50% with an alpha of 5% and 90% power and 35% versus 48% with
80% power. We assumed for approximately 40% of subjects in the
minority group that the minimal detectable difference for either of
the 2 minority subgroups (black, Hispanic) would be 35% versus
60% with 90% power and 35% versus 58% with 80% power. The
model will contain a term for treatment assignment (intervention
Table. Data Elements
Element Source Baseline Follow-Up 24-Months
Primary end point
Secondary end points
Provider attitudes Surveys X X
Pharmacist billing Encounter forms X X
Weight and BMI Measurement/
Comorbidity Medical records X X X
No. of clinic visits Medical records,
Interview X X X
Interview X X X
Adverse reactions Interview X X X
Smoking status Interview X X X
Data in the observational cohort will be collected by retrospective medical
record review. BMI indicates body mass index.
Carter et al Pharmacist Model To Improve Blood Pressure Control 421
versus control), baseline BP, and age. If a patient’s BP control status
is missing at 9 months, that subject will be considered to have
uncontrolled BP. We will perform a sensitivity analysis to determine
the potential dependence of the results of the primary analysis on the
missing values, which will include using multiple methods to impute
the missing values to determine the effect of the choice of imputation
on the results. Methods will include worst case (patients with
missing BP not controlled in the intervention group, but patients
with missing data have controlled BP in the control group), best case
(missing assumed controlled in the intervention group and assumed not
controlled in the control group), random assignment of outcome, and
use of regression methods to predict the outcome for each subject with
a missing value based on his or her baseline values of known
predictors of BP. Because randomization is by center, there may be
differences among the treatment groups with respect to other potent
predictors of outcomes, including patient-, physician-, or clinic-
specific factors. Although the primary analysis will include only
baseline BP and age, we will explore the effects of other potential
covariates in a separate secondary analysis, including sex, race,
education, insurance status, household income, marital status, smok-
ing status, alcohol intake, body mass index, number of coexisting
conditions at baseline, number of baseline antihypertensive medica-
tions, baseline medication adherence, and total number of clinic
visits. We will first determine whether there are significant (clinical
or statistical) differences among the treatment groups with respect to
any of these potential covariates. Second, we will repeat the
generalized estimating equation analysis but with the additional
covariates identified in the previous step. To avoid multicolinearity,
we will first fit univariate models to identify covariates that appear
to have some influence on the effect of the treatment and then
include those covariates whose univariate probability values are
ⱕ0.2 in multivariate models. These analyses will provide estimates
of the effect size for the intervention adjusted for differences among
the treatment groups with respect to important potential confounders.
The Collaboration Among Pharmacists Physicians To Im-
prove Outcomes Now (CAPTION) trial will be the first study
of team-based care to be conducted in a national practice-
based research network. The study is designed to address
several aspects of the National Institutes of Health Roadmap
and the National Heart, Lung, and Blood Institute strategic
plan. This study will implement a proven team-based care
strategy to improve the use of BP guidelines and BP control,
thus translating basic and clinical research to the community.
The National Institutes of Health has a strong desire to
implement models that work, overcome provider and health
system barriers, and sustain the effect of interventions so that
they can eventually be scaled up for broader use. The
CAPTION trial is designed to address these goals and to
determine how to implement and sustain the team-based
intervention in a very diverse group of clinics and patients. If
this model yields a 10 mm Hg difference in SBP and can be
implemented broadly in US clinics that currently use clinical
pharmacists, there would be 20% fewer coronary deaths and
25% fewer stroke deaths.
The current healthcare reform
debate has focused on the medical home as 1 strategy to
1 component of which is team-based care. The
CAPTION trial will help to determine how effective team-
based care may be for controlling BP in diverse medical
offices and for underrepresented minorities.
The CAPTION study will have patients enrolled through
2012. The results of this study should provide information on
barriers and facilitators to implementing this PPCM to im-
prove BP control and on whether the intervention is effective
in underrepresented minorities.
Site investigators for the CAPTION study: Renu Singh, PharmD,
Marie Williams, MA, and Carlos Rojas, MD, Fourth & Lewis Family
Medicine, San Diego, Calif; Grace Kuo, PharmD, MPH, Nathan
Painter, PharmD, Alita Newsome, MA, and Dustin Lillie, MD,
Scripps Ranch Family Medicine, San Diego, Calif; Eric Jackson,
PharmD, Alan Cementina, MD, and Evelyn Pianko, MA, Family
Medicine Center at Asylum Hill, Hartford, Conn; John Gums,
PharmD, Steven Smith, PharmD, Delores Buffington, RN, and
Karen Hall, MD, University of Florida Family Practice, Gainesville,
Fla; Eduardo Gonzalez, MD, Kevin Sneed, PharmD, H. James
Brownlee Jr, MD, and Kymia Love Jackson, BBA, University of
South Florida Department of Family Medicine, Tampa, Fla; Mark
Jones, PharmD, Katherine M. Brasch, LPN, and Andrew Andresen,
MD, Genesis Family Medical Center, Davenport, Iowa; CoraLynn
Trewet, PharmD, Mary Froehle, BS, CHES, and Larry Severidt, MD,
Broadlawns Family Health Center, Des Moines, Iowa; James Hoe-
hns, PharmD, Pam Trenkamp, RN, CCRP, and Jim Poock, MD,
Northeast Iowa Family Practice Center, Waterloo, Iowa; Brandon
Mickelsen, DO, Rex Force, PharmD, John Holmes, PharmD, and
Mary Macdonald, LPN, Pocatello Family Medicine Clinic,
Pocatello, Idaho; Jennifer Goldman-Levine, PharmD, Sandy Cogli-
ano, MA, and Greg Sawin, MD, Tufts University Family Medicine,
Malden, Mass; Angela Wisniewski, PharmD, Meredith Snyder, BA,
MPH, and Jeanette Figueroa, MD, Jefferson Family Medicine Clinic,
Buffalo, NY; Timothy Ives, PharmD, Betsy Bryant-Shilliday,
PharmD, and Robb Malone, PharmD, University of North Carolina
Enhanced Care Clinic, Chapel Hill, NC; Phillip Rodgers, PharmD,
Tracie Rothrock-Christian, PharmD, Lynn Bowlby, MD, and Angela
Braswell, LPN, Duke University Medical Center, Durham, NC;
Rebecca Edwards, PharmD, Geraldine Zurek, MEd, CCRP, and
David Townsend, MD, Northwest Area Health Education Center,
Wake Forest University, Winston-Salem, SC; Patricia Klatt,
PharmD, Roberta Farrah, PharmD, Sandra Sauereisen, MD, and M.
Maggie Folan, PhD, University of Pittsburgh Medical Center, St
Margaret Family Medicine, Pittsburg, Pa; Kelly Ragucci, PharmD,
Sarah Shrader, PharmD, Allison McCutcheon, MPH, and Eric
Matheson, MD, MS, Medical University of South Carolina, Depart-
ment of Family Medicine Clinic, Charleston, SC; Lori Dickerson,
PharmD; Allison McCutcheon, MPH, and Peter Carek, MD, MS,
Trident Family Medicine, Charleston, SC; Adrienne Z. Ables,
PharmD, I.S. Simon, MD, and Lynda Lowe, RN, Spartanburg
Family Medicine, Spartanburg, SC; Eric MacLaughlin, PharmD,
Debbie Hermes, LPN, and Rodney Young, MD, Texas Tech Center
for Community and Family Medicine, Amarillo, Tex; Debra Lopez,
PharmD, Patricia Kaplan, MA, and Terrell Benold, MD, Blackstock
Family Practice, Austin, Tex; Jeri Sias, PharmD, Ulysses Urquidi,
MD, and Jose Rodriguez, CPHT, CCRP, Texas Tech Community
Partnership Clinics, El Paso, Tex; Margie Perez-Padilla, PharmD,
and Jose Luna Jr, MD, University of Texas, Centro San Vicente, El
Paso, Tex; Julie Adkison, PharmD, Michael Crouch, MD, and
Dianne Torres, MA, Memorial Family Medicine Program, Sugar
Land, Tex; Oralia Bazaldua, PharmD, John Tovar, PharmD, Bryan
Bayles, PhD, Ramin Poursani, MD, and Mark Nadeau, MD, Univer-
sity of Texas Health Science Center, San Antonio, Tex; Carrie
Stoltenberg, RPh, Jody Pankow, BSN, RN, and Louis Sanner, MD,
Northeast Family Practice, Madison, Wis; Connie Kraus, PharmD,
Anna Legreid Dopp, PharmD, Terri Carufel-Wert, RN, and Beth
Potter, MD, Wingra Family Medical Center, Madison, Wis; and
Elizabeth Musil, PharmD, Victoria Mertins, RN, and Jesse DeGroat,
MD, Wheaton Franciscan Medical Group, Racine, Wis.
We thank the Executive Committee of the National Interdisciplinary
Primary Care Practice-Based Research Network who assisted with
the development of this network and the study design: John Gums,
422 Circ Cardiovasc Qual Outcomes July 2010
PharmD; Lori Dickerson, PharmD; Oralia Bazaldua, PharmD; Tim-
othy Ives, PharmD; Connie Kraus, PharmD; Grace Kuo, PharmD,
MPH; and John Tovar, PharmD. We also thank the data and safety
monitoring board: Barry Davis, MD, PhD (Chair); Keith Ferdinand,
MD; Michael Murray, PharmD, MPH; and Nakela Cook, MD, MPH.
Sources of Funding
This study is supported by the National Heart, Lung, and Blood
Institute, RO1 HL091841. Drs Carter and Chrischilles are supported
by the Agency for Healthcare Research and Quality Centers for
Education and Research on Therapeutics Cooperative Agreement
#5U18HSO16094. Drs Carter, Vander Weg, and Vaughn are sup-
ported by the Center for Research in Implementation in Innovative
Strategies in Practice, Department of Veterans Affairs, Veterans
Health Administration, Health Services Research and Development
Service (HFP 04 –149).
The views expressed in this article are those of the authors and do
not necessarily reflect the position or policy of the Department of
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Carter et al Pharmacist Model To Improve Blood Pressure Control 423