Patient Centered Primary Care

7/27/2019 Patient Centered Primary Care

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Patient centered primary care is associated with patienthypertension medication adherence

Christianne L. Roumie Robert Greevy

Kenneth A. Wallston Tom A. Elasy Lisa Kaltenbach

Kristen Kotter Robert S. Dittus Theodore Speroff

Received: June 14, 2010 / Accepted: November 15, 2010 / Published online: December 16, 2010

Springer Science+Business Media, LLC (outside the USA) 2010

Abstract There is increasing evidence that patient cen-

tered care, including communication skills, is an essentialcomponent to chronic illness care. Our aim was to evaluate

patient centered primary care as a determinant of medica-

tion adherence. We mailed 1,341 veterans with hyperten-

sion the Short Form Primary Care Assessment Survey

(PCAS) which measures elements of patient centered pri-

mary care. We prospectively collected each patients

antihypertensive medication adherence for 6 months.

rPatients were characterized as adherent if they had med-

ication for[80%. 654 surveys were returned (50.7%); and

499 patients with complete data were analyzed. Antihy-

pertensive adherence increased as scores in patient cen-

tered care increased [RR 3.18 (95% CI 1.44, 16.23)

bootstrap 5000 resamples] for PCAS score of 4.5 (highest

quartile) versus 1.5 (lowest quartile). Future research is

needed to determine if improving patient centered care,

particularly communication skills, could lead to improve-ments in health related behaviors such as medication

adherence and health outcomes.

Keywords Medication adherence Hypertension

Patient centered care Communication

Introduction

For patients to effectively manage chronic illness, they

need understandable information, participation in deci-

sion making, goal setting, problem-solving and assis-

tance managing psychosocial issues (Bodenheimer 2003;

Bodenheimer et al. 2002a, b; Hibbard 2003; Hibbard and

C. L. Roumie R. Greevy K. A. Wallston

T. A. Elasy K. Kotter R. S. Dittus T. Speroff

VA Tennessee Valley Healthcare, Tennessee Valley Geriatric

Research Education Clinical Center (GRECC), Nashville,

TN, USA

C. L. Roumie R. Greevy K. A. Wallston

T. A. Elasy K. Kotter R. S. Dittus T. Speroff

HSR&D Targeted Research Enhancement Program Centerfor Patient Healthcare Behavior, Nashville, TN, USA

C. L. Roumie R. Greevy K. Kotter

Tennessee Valley VA Clinical Research Training Center

of Excellence (CRCoE), Nashville, TN, USA

C. L. Roumie T. A. Elasy R. S. Dittus T. Speroff

Department of Medicine, Vanderbilt University, Nashville,

TN, USA

C. L. Roumie T. A. Elasy R. S. Dittus T. Speroff

VA National Quality Scholars Program, Nashville, TN, USA

R. Greevy K. Kotter T. Speroff

Department of Biostatistics, Vanderbilt University, Nashville,

TN, USA

K. A. Wallston

School of Nursing, Vanderbilt University, Nashville, TN, USA

L. Kaltenbach

Duke Clinical Research Institute, Durham, NC, USA

T. Speroff

Department of Preventive Medicine, Vanderbilt University,

Nashville, TN, USA

C. L. Roumie (&)

Nashville VA Medical Center, 1310 24th Ave South GRECC

4B120, Nashville, TN 37212, USA

e-mail: [email protected]

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Peters 2003; Rothman and Wagner 2003; Wagner et al.

1996; Wagner et al. 2001). Many of these qualities are

attributes of patient-centered primary care (Cleary et al.

1993; Laine et al. 1996). The Picker Institute and the

Commonwealth Fund coined the term patient centered care

in 1986 (Beatrice et al. 1998). A high degree of consensus

exists regarding the key attributes of patient-centered care.

They include: education and shared knowledge; involve-ment of family; collaboration and team management;

sensitivity to non medical and spiritual dimensions of care;

respect for patient preferences; and accessibility of infor-

mation including enhanced provider patient communica-

tion (Bergeson and Dean 2006; Bodenheimer et al. 2002b;

Lewin et al. 2001; Shaller 2007). Patient centered care is

postulated to lead to an increased sense of self efficacy

which leads to increased self-management behaviors

(Bodenheimer et al. 2002; Holman and Lorig 2004; Lorig

et al. 1999).

In 2001, Lewin et al. published a Cochrane review

of 17 trials which included interventions to promotepatient centered care. They found that interventions that

included training healthcare providers in patient-centered

approaches positively impacted patient satisfaction with

care. Six of the 11 studies that assessed patient satisfac-

tion demonstrated significant differences among the

intervention group on one or more measures. Few studies,

however, examined healthcare behavior or health out-

comes. Therefore, Lewin et al. concluded that there is

limited evidence on the effects of such interventions on

patient healthcare behaviors and further research was

required.

One key patient self management activity is taking

medications. Medication non-adherence or discordance

is the variance between patient medication self-adminis-

tration and the regimen prescribed by their provider

(Osterberg and Blaschke 2005). Poor medication adherence

is one factor that accounts for worsening of disease, and

increased costs (Gandhi et al. 2000; McDonnell and Jacobs

2002; Merz et al. 2002; Schiff et al. 2003).

Our objective was to explore the concepts of patient-

centered care and activation as a marker of productive

interactions within the chronic care model. Specifically

we focused on the relationships between patients percep-

tions of patient-centered primary care (a care environment

variable), medication adherence (a process of care vari-

able), and blood pressure (BP) control (a key outcome of

care) (Bodenheimer et al. 2002a, b; Wagner 2004; Wagner

et al. 1996, 2001; Wagner and Groves 2002). Our

hypothesis was that patients who score higher in the do-

main of patient-centered primary care will have greater

adherence to antihypertensive medications and, subse-

quently, better BP control.

Methods

Study design

We conducted a prospective cohort study among veterans

who had participated in a prior cluster randomized trial

conducted at the Veterans Affairs Tennessee Valley

Healthcare System (TVHS) involving interventions ofincreasing intensity designed to affect BP control and

results have been published (Roumie et al. 2006). Two

months after the trial ended, we conducted a cross-sectional

follow-up survey assessing veterans perceptions of the

care delivered at TVHS. Subsequently, patients antihy-

pertensive medication adherence and BP were assessed for

the 6-month period following survey completion. The

Institutional Review Board and the research and develop-

ment committee of the Veterans Affairs Tennessee Valley

Healthcare System approved this study.

Population and survey protocol

The inception cohort consisted of a convenience sample of

1341 participants who were mailed the short form of the

Primary Care Assessment Survey (PCAS) (Safran et al.

1998) 2 months after the trial ended (March 1, 2005). The

survey packet, which also included a cover letter and return

envelope, was mailed once. The cover letter stated that

participation was voluntary and patients could opt out of

the survey. The survey also included a one page ques-

tionnaire asking for general information about the partici-

pant as well as the 22 item patient activation measure

(PAM) (Hibbard et al. 2004). Non-responders were mailed

a reminder postcard 3 weeks after the initial mailing. Most

responders returned surveys within 8 weeks; however, we

accepted responses through 21 weeks (N= 9 responses

received between 921 weeks).

All patients (responders and non-responders) were fol-

lowed for 6 months (184 days) following the survey.

Patients were censored if they died during the follow-up

period or if they stopped filling any medications through

the VA; otherwise, cohort days were counted as number of

medication eligible days.

Survey instruments

Primary care assessment survey (PCAS)

The Short Form PCAS (Safran et al. 1998) is a validated

patient-completed questionnaire designed to measure seven

elements of primary care: access; continuity; comprehen-

siveness; integration of care; clinical interactions (includ-

ing both communication and exam skills); interpersonal

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treatment; and trust. We report the raw mean item scores

which range from 15 with higher scores representing more

of the attribute being assessed.

Given that many veterans are dual users of VA and

private sector services, we modified the PCAS to clarify

that questions are related to their VA provider. Because

the questions were changed, we conducted an exploratory

principal components factor analysis. A single factorexplained 77% of the variance and had high internal con-

sistency (Cronbachs a = 0.93). We named that factor

patient-centered primary care.

Patient activation measure (PAM)

The PAM (Hibbard et al. 2004) assesses four concepts in

activation: believes an active role is important; confidence

and knowledge to take action; taking action; and staying

the course under stress. The PAM has high reliability

estimates (Cronbachs a = 0.91) which are stable across

health status, gender and age. Scores on the PAM weretransformed from the continuous logit scale to a continuous

0100 score with high scores representing high activation.

Process and outcome measures

We prospectively collected all participants medication fills

and outpatient blood pressure measurements for 6 months

from the initial date the survey was mailed (184 days from

March 1, 2005). The Mid-South Data warehouse is a

relational database updated monthly which contains

patient-specific information including billing, prescrip-

tions, vital signs, diagnoses, and laboratory data. The

pharmacy data files contain data for each prescription fill.

Medication adherence

The primary process measure was adherence to antihy-

pertensive medications. Using prescription information we

determined if a patient had any antihypertensives on each

medication eligible day or medications in hand. Medi-

cations that were included in the adherence assessment

included the following classes: angiotensin converting

enzyme inhibitor or receptor blocker; beta-blocker;

diuretics (except furosemide); calcium channel blocker;

centrally acting antihypertensive or alpha adrenergic anti-

hypertensive agents. Furosemide was excluded from the

adherence calculations given the potential for variable use.

Often patients stockpile medications; therefore we

derived an estimate that ascertained how many pills a

patient had each day. For example, if a patient received

90 days of lisinopril and refilled on day 80 then the patient

had 100 days of medications in hand (90 from the new fill

+10 left over from initial fill). This was necessary because

many patients in the VA system receive medications

through the mail and for various lengths of time (usually

3090 days supply). Days supply in hand was reset to 0

when a dosage change was made to the medication.

Adherence was calculated using a modification of the

Steiner method (Steiner et al. 1988, 1993; Steiner and

Prochazka 1997): the number of days with at least one

antihypertensive medication available divided by thenumber of eligible medication days. This ratio could range

from 01 and higher values indicate greater adherence. A

patient who received an adherence score of 1 refilled their

antihypertensive medication within the expected time for a

refill 100% of the time. After a patients adherence score

was calculated, we dichotomized each patient as adherent

using C0.8 or non-adherent using \0.8 (Andrade et al.

2006; Bagchi et al. 2007; Elliott et al. 2007; Hess et al.

2006; Yang et al. 2007). For patients who filled no medi-

cations at the VA in the 184 day window their adherence

was considered missing.

BP control

The dichotomous outcome measure was an outpatient BP

of 140 mm Hg (systolic) and B90 mm Hg (diastolic)

during follow-up among all patients including those with

diabetes. If more than one BP reading was available, we

used the BP closest to day 184 post survey to determine if

the patient reached goal (range 93273 days). We coded

the outcome 1 if the patient reached this BP goal, and

0 if the goal was not reached.

Statistical analysis

Each respondent must have completed C75% of the sur-

veys questions to be included in the analysis. If the survey

contained some unanswered questions, scale rules were

applied according to instructions to calculate the score. We

examined the distributions of the PCAS and all covariates.

After the PCAS score was calculated it was used in a

multivariate logistic regression model to independently

predict the process or outcome variables (adherenceC0.80

or BP 140/90 mm Hg). To avoid assuming a linear

association with adherence, PCAS was fit with third degree

polynomial curves. Covariates were determined a priori

based on clinical significance. These included patient age,

self reported race (white, nonwhite), education (\12th

grade, C12th grade), duration of hypertension (less than 1,

25, 610, 1115, 1620,[20 years), and VA-only care

versus any private sector care for the treatment of hyper-

tension. We also adjusted for PAM score (degree of self-

assessed patient activation). We accounted for the provider

as a random effect to adjust for clustering. Given that there

were 499 patients in the adjusted analysis we chose the

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most clinically significant covariates so as not to overfit our

adjusted models.

We conducted exploratory subgroup analyses to deter-

mine if any of the individual questions or subscales in the

PCAS was associated with medication adherence. For these

analyses we divided the 5 point Likert response scale into a

binary predictor and calculated the odds of adherence using

logistic regression for those who responded positivelycompared to those who responded negatively to each item.

We also conducted a sensitivity analysis to determine

the stability of our adherence measure of 80%. We varied

the adherence definition and reran the analysis for all cut-

offs between 0% and 100%. Likelihood ratio tests were

used to determine the statistical significance of variables

assuming a = 0.05. A bootstrap procedure (N= 5,000)

was used to determine confidence intervals. We report

relative risks (RR) or odds ratios (OR) and 95% confidence

intervals (95% CI). Statistical analyses were conducted

using Stata 8.2 and SAS for Windows 9.1.

Results

We received 756 of the 1341 surveys (56.4%). Fifty-two

surveys were returned incomplete (opt outs). After

excluding surveys sent to incorrect addresses (n = 31) or

to patients who were identified by family as dead or de-

mented (n = 19), our response rate was 50.7% (654/1291).

Non-responders (637/1291 = 49.3%) were those who ac-

tively chose to opt out and those who did not return

surveys. Because we required that 75% of the survey be

completed, 584/654 (89.3%) PCAS and 624/654 (95.4%)

PAM surveys contained usable data. A total of 560/654

(85.6%) patients answered both surveys (Fig. 1).

Patient characteristics

Responders were 97.3% male, and older than non-

responders (67.0 11.3 vs. 63.4 12.7; t (1289) P\

0.0001). Responders were more likely to have their BP

controlled at survey baseline than non-responders [68.5%

vs. 57.3%; X2(1) P\ 0.0001] and responders were more

likely to be adherent to their antihypertensive medications at

survey baseline (58.0% vs. 42.1%; X2(1) P\ 0.0001) and

continued to be more adherent at the 6 month follow up

(72.7% vs. 57.8%; X2(1) P\ 0.0001).

Table 1 demonstrates the characteristics of persons in-

cluded in the adherence analysis (N= 499). The majority

of patients were older white males. The mean PCAS item

score was 3.57 (Standard deviation [SD] 0.84; Median 3.65

[Interquartile Range (IQR)] 34.23]). A slightly higher

proportion of patients with diabetes (7.6 vs. 4.7%; X2(1)

P = 0.337) and hyperlipidemia (49.3 vs. 44.7%; X2(1)

P = 0.434) were included in the analysis. A higher pro-

portion of patients included in the analysis had their BP

controlled at baseline compared to those excluded due to

missing adherence measures or covariates (71.3 vs. 55.3%;

X2(1) P = 0.003).

Primary process measure: medication adherence

Adherence could be calculated for 528/560 survey

responders (94.3%). As shown in Table 2, as PCAS score

increased, the proportion of patients considered adherent

increased (X2(3) P = 0.03).

In a regression model that adjusted for covariates as well

as the provider as a random effect, we observed that, as

PCAS scores increased, antihypertensive medication

adherence also increased (Random-effects logistic regres-

sion [N= 499 observations in 113 groups] Likelihood

Ratio X2(3) P = 0.001) (Fig. 2). The relative risk of anti-hypertensive adherence for a patient with a PCAS score of

4.5 (highest quartile) compared to a patient in the lowest

quartile (score 1.5) was 3.18 (95% CI: 1.44, 16.23 boot-

strap 5,000 resamples).

When we tested each covariate in the model, duration of

hypertension and using the VA as the primary source of

hypertension care were associated with medication adher-

ence. Patients had increased odds of adherence if the

duration of hypertension was 610 years (Odds Ratio [OR]

1.92; 95% CI: 1.09, 3.39 Random-effects logistic regres-

sion [N= 499 observations in 113 groups] X2(5) or

1115 years (OR 2.70; 95% CI: 1.27, 5.78) compared to

those with hypertension for\5 years. For patients who

received all of their hypertension care through the VA the

odds of medication adherence was 2.30 (95% CI: 1.39,

3.83 Random-effects logistic regression [N= 499 obser-

vations in 113 groups] X2(1) P = 0.004) compared to those

who received some or all of their hypertension care in the

private sector. The remaining covariates in the model were

non- significant [Random-effects logistic regression

[N= 499 observations in 113 groups] Likelihood Ratio

tests PAM score (X2(3) P = 0.34); patient age (X2(3)

P = 0.17); race (X2(1) P = 0.50); and education (X2(1)

P = 0.68)].

In follow-up exploratory analyses, two questions on the

PCAS that asked about the providers communication skills

had the greatest association with patient medication

adherence (Table 3).

We conducted additional analyses including all a priori

selected covariates as well as number of antihypertensive

medications, and Charlson comorbidity score. We also

conducted an analysis on the subgroup of patients who

indicated that the VA provides all of their care. In both

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additional analyses we demonstrated that patient centered

care remains associated with antihypertensive medication

adherence (data not shown).

Primary outcome measure: BP control

Follow-up BP measurements at 6 months were available

for 400/560 (71.43%) responders (table 2). There was no

relationship between increasing PCAS score and 6 month

BP control (X2(3) P = 0.56). After adjusting for covariates

(N= 376) there was no statistically significant relationship

between BP control and the PCAS (RR 1.85; 95% CI: 0.80,

6.42; P = 0.28 bootstrap 5,000 resamples) for highest

quartile PCAS compared to lowest. To examine whether

medication adherence predicted BP control we performed

an unadjusted logistic regression analysis predicting BP

control for the subsample (N= 861) with both 6 month

adherence and BP measures. With increasing medication

adherence the odds of BP control also increased (Logistic

regression X2(1) OR 1.52; 95% CI: 1.04, 2.24; P = 0.03).

Sensitivity analysis

Our definition assigns patients as adherent if they have at

least 1 antihypertensive pill for 80% of the medication

eligible days. Our sensitivity analysis varied the definition

of adherence. The significant association between adher-

ence and PCAS was robust to the cutoff choice. While 80%

1341 surveys sent to participants of randomized trial

19 sent to dead/demented patients

31 returned for incorrect address

Non responders (49.3% N=637/1291)

52 returned with no data (opt-outs)

585 never returned

654 returned with some survey data (50.7%)

624 with completed PAM584 with completed PCAS

Exclude surveys with


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is often reported in the literature, any cutoff between 55

and 91% would have yielded the same conclusions.

Discussion

Our findings show an association between perceived

patient-centered primary care, particularly providers com-

munication skills, and patient antihypertensive medication

adherence behavior. Patients reporting the lowest patient-

centered primary care scores had the lowest adherence

scores. Our results also confirm a relationship between

medication adherence andblood pressure control; the greater

the adherence, the better the control. Our analysis, however,

was unable to demonstrate a relationship between patient

centered care and blood pressure control outcomes.

Several studies establish the connection between a strong

patient-physician relationship and medication adherence

(Inui et al. 1976; Piette et al. 2005; Roberts 2002; Schneideret al. 2004; Wroth and Pathman 2006). A study of patients

with HIV tested six patient centered care scales (commu-

nication, HIV-specific information, participatory decision

making, satisfaction, willingness to recommend physician,

and trust). Scores on these scales were compared to self

reported adherence. In four domains-communication, sat-

isfaction, willingness to recommend and trustthere was a

strong association with adherence (Schneider et al. 2004).

Finally, in a study of 752 patients with diabetes, information

giving and collaborative decision making were associated

with better medication adherence, diet, exercise and self

management behaviors (Piette et al. 2003).The shift in patterns of disease toward chronic illness

necessitates greater patient participation in disease man-

agement but also requires the provider to engage in edu-

cation and collaborative decision making (Bodenheimer

2007; Roter and Hall 1991). A survey of patients and

physicians asked each group to rate domains of outpatient

care (Laine et al. 1996). Both groups agreed that the most

important element was clinical skills; however, they dis-

agreed on the relative importance of effective information

communication. Patients ranked provision of information

second in importance whereas physicians ranked it sixth.

Few potentially modifiable determinants of medication

adherence have emerged and most have targeted a variety

of potentially important factors, each with a small contri-

bution such as, simplifying dose regimens, patient medi-

cation understanding, motivation and self efficacy,

components of patients drug-taking behavior such as

organization of medications (pillboxes) or behavioral cues

(alarms) and cost (waiving co-payments) (DiMatteo 2004;

DiMatteo et al. 2002; Gregoire et al. 2002; Zolnierek and

Dimatteo 2009). Results have been mixed, and these

multifaceted complex programs are difficult to sustain in

regular practice (Schroeder et al. 2004). The relationship

between the provider and patient and the focus on com-

munication skills is one in which there has been less

research.

However, two recent studies are of particular note. The

first was conducted in Canada where starting in 1992, all

physicians had to complete the Medical Council of Canada

national clinical skills examination (Tamblyn et al. 2010).

The clinical skills examination assesses communication,

history, and physical examination skills and clinical man-

agement by direct observation of physicians in 1820

Table 1 Characteristics of responders included in adherence analysis

N= 499

M (SD) Count (%)

Age 66.75

(11.06)

Male gender 489 (98.00)

White race 454 (90.98)

Location of carea

Teaching hospital 169 (33.87)

Community based clinic 286 (57.31)

Primary care provider type

Staff Physician (N= 68 providers) 310 (62.12)

Resident Physician (N= 12 providers) 21 (4.21)

Non Physician Clinician (N= 33

providers)

168 (33.67)

Source of Hypertension treatmentb

VA care only 361 (72.34)

Non VA care only 10 (2.00)

Combination VA and Non VA care 94 (18.84)

Diabetes 38 (7.62)

Hyperlipidemia 246 (49.30)

Baseline Antihypertensives prescribedc

1 Antihypertensive medication 345 (69.14)

2 Antihypertensive medications 99 (19.84)

C 3 Antihypertensive medications 13 (2.60)

Baseline adherence[ 0.8 336 (67.33)

Baseline BP controlled 356 (71.34)

Education C 12th grade 387 (77.56)

Years of hypertension

B1 37 (7.41)

25 188 (37.68)

610 114 (22.85)

1115 65 (13.03)

1620 38 (7.62)

[20 57 (11.42)

a All providers were primary care providers: 44 persons missing

Location of primary careb 34 persons reported no treatment or did not answer questionc 42 persons had no antihypertensive or only furosemide prescribed

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standardized patients. Previous research has shown that

lower exam scores predict complaints about poor com-

munication and quality of care (Tamblyn et al. 2002,

2007).

The investigators hypothesized that physicians who

possess greater proficiency in communication and/or

medical management will achieve better medication

adherence among their patients with hypertension. Within

6 months after starting treatment, 2,926 of the 13,205

newly diagnosed hypertensive patients discontinued anti-

hypertensives. The risk of discontinuation was reduced for

patients who were treated by physicians with better com-

munication ability (OR 0.88; 95% CI 0.781.00) specifi-

cally data collection skills.

A second important contribution in physician patient

communication and the potential link to adherence was a

meta-analysis published in 2009 (Zolnierek and Dimatteo

2009). The meta-analysis sought to address 2 questions.

The first, based on the patient centered care model, was is

there a positive association between provider communica-

tion and patient adherence across studies? The second

question was does physician training (in communication)have a positive effect on patient adherence? The first

question yielded 106 journal articles while the second only

21 studies. Among the 106 articles which were pooled to

answer the question regarding the relationship between

patient adherence and provider communication (all except

2 demonstrated a positive relationshipthat better com-

munication was predictive of better adherence). Non-

adherence was 1.47 times greater (standardized relative

risk) among physicians who were poor communicators

compared to good communicators. Among the 21 studies

reporting patient adherence as an outcome of an interven-

tion designed to train physicians in communication skills,all effects were positive (training in better communication

skills was predictive of better patient adherence). The

standardized relative risk of non adherence is 1.27 times

greater among patients of untrained physicians.

While communication is an important component of

patient centered care; trust, knowledge of the patient, and

interpersonal treatment appeared to also be important

components within the PCAS, while system factors such as

integration of care and organizational access surprisingly,

appeared less important in their associations with medica-

tion adherence. We also postulated a high degree of patient

activation, a measure similar to patient self efficacy would

be associated with medication adherence (Bandura 1991).

We found no relationship between high levels of activation

and medication adherence; however, this was the first time

this measure has been used in the veteran population. In

prior studies in a Medicare population (Hibbard et al. 2004,

2007) the PAM was associated with decreased healthcare

utilization, better medication adherence and improved self

management behaviors. Our negative findings with the

PAM may be due to multiple factors including our re-

sponse rate and the administration to a veteran population

in which this survey may not have performed as robustly as

the population in which it was developed.

Limitations to our study may have impacted our find-

ings. Non response is a common, well recognized limita-

tion of survey methodology; our response rate of 50.7% is

within expected range (Reijneveld and Stronks 1999). We

suspect we also had non-response bias that is typically seen

in surveys, including fewer responses from younger,

healthier patients and nonwhites (Ives et al. 1994; Lasek

et al. 1997; Solberg et al. 2002). We demonstrate that our

responders differed from nonresponders in adherence and

Table 2 Unadjusted relationship between PCAS measure with

6 month antihypertensive adherence or 6 month BP control

N adherenta/N

in quartile (%)

total N= 528

N BP controlledb/N

in quartile (%)

total N= 400

PCAS Quartile 1

score[ 1 to B 3.0

83/132 (62.8) 47/88 (53.4)

PCAS Quartile 2

score C 3.01 to\3.65

97/131 (74.0) 52/107 (48.6)

PCAS Quartile 3

score C 3.65 to\4.22

95/131 (72.5) 58/100 (58.0)

PCAS Quartile 4

score C 4.22

106/134 (79.1) 53/105 (50.5)

Responders to PCAS and had an adherence measure available

(N= 528) and responders to PCAS with6 month BP available

(N= 400)a Adherence defined as having antihypertensive medications avail-

able for at least 80% of medication eligible daysb BP control defined as 6 month BP with Systolic\ 140 mmHg and

Diastolic BP\ 90 mmHg

0

.2

.4

.6

.8

1

0

.2

.4

.6

.8

1

medicationadherence

1 2 3 4 5

Patient centered care score

Estimated Proportion adherent

95% Confidence Intervals

Fig. 2 PCAS Score versus the estimated proportion adherent (black

line) and 95% confidence intervals (gray lines). Dashed line indicates

80% adherent to antihypertensive medications

250 J Behav Med (2011) 34:244253

123
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in BP control, but we are uncertain if they differed in their

perception of patient centered care because nonrespondersdid not complete the PCAS. Second, it is possible that the

patients assessment of patient centered primary care is a

global positive or negative patient attitude regarding

medical care in general rather than an independent measure

of their particular patient provider relationship. Our out-

come measures, however, were objective, thereby reducing

confounding. Third, nine persons included in the adherence

analysis returned their survey after 8 weeks. At that time,

medication fills may have already occurred. Therefore, for

a small number of patients (1.80%), a portion of the out-

come assessment may have preceded exposure however,our sensitivity analysis determined alternative cut points

for adherence and our results remained robust. Further-

more, our definition of adherence only takes into account

prescription filling, not consumption. Finally, although we

found positive relationships between PCAS and adherence

and between adherence and BP control, we were unable to

demonstrate an association between PCAS score and BP

control. This could be due to multiple factors including

reduced statistical power or variables other than adherence

Table 3 Adjusted odds of adherence based on response to PCAS item for 499 respondents

PCAS questions Adjusted OR

of adherencea (95% CIs)

Physician patient interaction

Communication

How would you rate the thoroughness of your doctors questions about your symptoms and how

you are feeling?

b

3.74 (1.86, 7.49)

When you visit and talk with your provider how often do you leave with unanswered questions?c 5.34 (1.24, 22.99)

Interpersonal treatment

How would you rate your providers caring and concern for you?d 1.92 (0.99, 3.73)

Knowledge of patient

Doctors knowledge of what worries you most about your healthd 2.83 (1.59, 5.01)

Doctors knowledge of you as a person (your values and beliefs)d 1.75 (1.07, 2.87)

Trust

I completely trust my providers judgments about my medical careb 1.93 (1.04, 3.55)

I would recommend this provider to my family and friendsb 1.66 (0.93, 2.99)

Thoroughness of physical exam

How would you rate the thoroughness of the doctors physical examination of you to check

your health problems?d

1.88 (0.96, 3.67)

Structural and organizational factors

Visit based continuity

When you are sick and go to the doctor, how often do you see your regular doctor (not an

assistant or partner)?b0.81 (0.48, 1.35)

Organizational access

How would you rate the usual wait for an appointment when you are sick and call the doctors

office asking to be seen?d1.57 (0.97, 2.55)

How would you rate the ability to speak to your doctor by phone when you have a question or

need medical advice?d1.43 (0.91, 2.25)

When you phone your doctors office, how often are you able to get your concern addressed

within 24 h?b1.40 (0.86, 2.27)

Integration of care

How often does your provider seem informed and up to date about the care you received from

specialists that he/she sent you to?b1.04 (0.60, 1.77)

How would you rate the coordination between other providers and your regular provider? d 1.66 (0.93, 2.94)

a Odds of adherence adjusted for PAM score (3rd degree polynomial), patient age (3rd degree polynomial), self reported race, education, duration

of hypertension (6 categories), use of VA care versus any private sector care and clustering by the provider (logistic regression model N= 499

patients in 113 groups (15 df)b Patients who answered: often, usually or always are compared to those who answered never or sometimesc Reverse scoring item: Patients who answered this question as Never or sometimes are compared versus those who answered often usually or

alwaysd Patients who answered: good, very good or excellent are compared to those who answered poor or fair

J Behav Med (2011) 34:244253 251

123


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that are unrelated to patient centered care that could affect

BP control.

The goal of this research was to test the hypothesis that

higher quality patient-provider relationships are predictors

of better health behaviors and outcomes. Our results con-

firm this finding and suggest that the patient physician

relationship, particularly enhanced communication skills,

is potentially a point for interventions designed to increaseadherence.

Improving the providers communication skills could

have an important impact on health outcomes in chronic

diseases and deserves further investigation. Although we

applied the PCAS to patients treated for hypertension, the

questions are certainly not limited to this population. Fur-

ther investigation is necessary to determine if patients who

report high levels of patient centered care, particularly in

the domain of communication have higher levels of

adherence in other chronic diseases including diabetes and

hyperlipidemia.

Acknowledgments This material is based upon work supported by

the Veterans Affairs Clinical Research Center of Excellence and the

Geriatric Research Education and Clinical Center Tennessee Valley

Healthcare System, Nashville Tennessee. VA Career Development

Transition Award 04-342-2.

Conflicts of interest There are no conflicts of interest to disclose.

The principal investigators and co-investigators had full access to the

data and were responsible for the study protocol, statistical analysis

plan, progress of the study, analysis, reporting of the study and the

decision to publish.

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