Background
The Influence of Primary Care
Practice Climate on Patient Trust
in Physician, Activation, and
Health
• Power in all physician-patient relationships is
inherently unequal.
– Patients are in a vulnerable position and seek knowledgeable
advice and competent care for resolution of their health problems.
– Physicians are in a dominant position and control knowledge and
treatments with potential to resolve patients’ health problems.
• Trust in the physician-patient relationship seeks to
counter the imbalance in power, information, and
control between the physician and patient. In a trusting
relationship, the patient believes:
Edmund R. Becker1 and Douglas W. Roblin2
1
Rollins School of Public Health at Emory University
2 Center for Health Research / Southeast, Kaiser
Permanente Georgia
– The physician’s words and actions are credible and can be relied
upon
– The physician will act in the patient's best interest
– The physician will provide support and assistance during health.
Project Funding
Centers for Disease Control and Prevention
NIH 1R01CD000033 (ER Becker, PI)
1
2
Background
Objectives
• Literature on organizational psychology and
sociology suggests that service providers working in
units with attitudes and behaviors supporting
delegation, collaboration, and teamwork are more
effective at attending to, and fulfilling, consumer's
needs and requests.
• We hypothesized:
– H1: Primary care teams with better practice
climates (better interdisciplinary teamwork and,
therefore, better patient orientation) will be
associated with higher trust of patients in team
practitioners.
– H2: Higher levels of trust in physicians will be
associated with greater patient activation.
• Service fulfillment increases the likelihood that a
consumer will be satisfied, and, in future
relationships, the words and actions of service
providers will be perceived as credible and
trustworthy.
– H3: Greater patient activation will have a positive
association with the practice of healthy lifestyle
and health status.
3
Study Population
•
•
4
Survey Instrument Development
Kaiser Permanente Georgia (KPGA)
members, aged 25-59, employed by
large public agencies or private
corporations in the Atlanta area.
Three condition cohorts were
sampled:
• Literature review to identify, brief reliable items
or scales administered in written surveys:
–
–
–
–
–
–
–
1. Low risk adults (no identifiable major morbidities)
2. Adults with elevated lipids (without acute CAD
history)
3. Adults with type 2 diabetes (without history of
micro- or macrovascular complications)
SF-12 (physical and mental function)
Trust in physician (PCAS)
Social climate (MIDUS)
Work climate (MIDUS)
Patient activation (PAM-13)
Physical activity (BRFSS)
Dietary intake (Block fat, F/V screeners)
• Cognitive pre-testing of draft instrument
among 4 focus groups
5
6
1
Survey Administration
Practice Team Sample and Survey
• Mixed mode survey (mail or Internet)
conducted by a professional survey firm from
10/1/05 thru 12/31/05
• 2,224 respondents among 5,309 sampled
(42% response rate)
• Primary care practitioners and support staff
affiliated with the 16 primary care teams in
2004
• Written survey administered during team
meetings in June/July 2004
– Respondents more likely to be female, older
– Diverse respondent sample: 60% female, 45% African
American, 18% HS education or less, 31% household
income < $50,000
– 35 items
– 83 practitioners (MD, PA, NP) among 97 (86%
response rate)
– 158 support staff among 187 (85% response rate)
• Psychometric properties of previously
validated scales were similar between these
survey respondents and respondents to
surveys where scales were initially used.
7
8
H1: Practice Climate as an Antecedent of Trust
H1: Practice Climate as an Antecedent of Trust
• Dependent variable: Trust in physician (PCAS; Safran
et al. 1998) measured at the patient-level
• Patients empanelled to primary care teams with more
favorable practice climates had significantly higher
average trust in their primary care physicians than
patients empanelled to teams with less favorable
practice climates.
– 9 item scale scored 0 (lowest) to 100 (highest)
– Cronbach’s α = 0.90
• Independent variable: Overall practice climate
measured at the team-level
– Average of 7 subscales (e.g. autonomy, team ownership, role
collaboration, task delegation) scored 0 (lowest) to 100
(highest)
• Fixed effects hierarchical linear regression of patient
(N=2,224) nested with primary care practice team
(N=16) accountable for their care
– Covariates: age, gender, condition cohort, race, martial
status, and education
– β = 0.11 point change in trust per point change in practice
climate (p ≤ 0.05)
• Patients empanelled to primary care teams with more
favorable practice climates were significantly more
likely to attribute “a lot” of influence on their
exercise or diet than patients empanelled to teams
with less favorable practice climates.
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H1: Practice Climate as an Antecedent of Trust
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H1: Practice Climate as an Antecedent of Trust
Primary Care Team Influence on Exercise ("A lot of Influence" - "No Influence")
by Quartiles of Trust in Physician
P redicted Trust in Physician and 95% C onfidence Intervals by Low est to Highest
Team Practice C lim ate Scores
30
Difference in Percent of Respondents Stating "A
lot" and Percent Stating "None"
68
67
65
64
63
62
st
15
he
25
20
15
10
5
0
LOWEST
MID-LOW
MID-HIGH
HIGHEST
-5
-10
-15
-20
-25
ig
14
13
12
11
9
10
8
7
6
5
4
3
2
w
es
t
61
H
Lo
Predicted Trust
66
-30
Team s (O rdered by Practice Clim a te S cores)
Respondents Classified by Quartiles of Trust in Physician
Predicted Trust
Exercise
11
Diet
12
2
H2: Influence of Trust on Patient Activation
H2: Influence of Trust on Patient Activation
• Dependent variable: Patient activation measure,
short-form (PAM-13; Hibbard et al. 2005) measured
at the patient-level
• Patient activation was significantly,
positively associated with trust in
physicians.
– 13 item scale scored 0 (lowest) to 100 (highest)
– Cronbach’s α = 0.95
– β = 0.20 point change in patient activation per
point change in trust in physician (p ≤ 0.01)
• Independent variable: Trust in physician (PCAS;
Safran et al. 1998) measured at the patient-level
– 9 item scale scored 0 (lowest) to 100 (highest)
– Cronbach’s α = 0.90
• Patients in the upper quartile of trust in
physician had significantly greater average
activation than patients in the lower quartile
of trust in physician.
• Ordinary least-squares linear regression
– Covariates: age, gender, condition cohort, race, martial
status, and education
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H3: Influence of Patient Activation on Lifestyle
and Health
H2: Influence of Trust on Patient
Activation
• Dependent variables:
Predicted Activation and 95% Confidence Intervals by Quartiles of Trust in
Physician
–
–
–
–
78
76
Predicted Activation
74
73.5
72
70
67.2
66
– 13 item scale scored 0 (lowest) to 100 (highest)
– Cronbach’s α = 0.95
63.7
62
• Ordinary logistic or least-squares linear regression
60
LOW EST
Recommended exercise level (BRFSS)
Dietary intake (Block fat and F/V screeners)
BMI
HbA1c (diabetes cohort), lipids (diabetes and elevated
lipids cohorts)
• Independent variable: Patient activation measure,
short-form (PAM-13; Hibbard et al. 2005)
69.6
68
64
14
MID-LOW
MID-HIGH
HIGHEST
– Covariates: age, gender, condition cohort, race, martial
status, and education
Trust in Physician Quartiles
Predicted Activation
15
H3: Influence of Patient Activation on Lifestyle
and Health
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H3: Influence of Patient Activation on Lifestyle
and Health
• Patients with higher activation were more likely
(p<0.05) to report recommended exercise levels.
• Patients with higher activation had better dietary
intake:
Predicted Probabilities and 95% Confidence Intervals for Achieving
Recommended Exercise Levels by Quartiles of Activation
80%
75%
70%
Predicted Probability
68.1%
– lower fat intake (p<0.05)
– higher F/V and fiber intake (all p<0.05).
• Patients with higher activation had lower average
BMI (p<0.05).
• Adults with diabetes or elevated lipids had higher
average HDL (p<0.05).
65%
60%
59.5%
55%
53.2%
50%
45%
44.1%
40%
35%
Least Activated
Mid-Low
Mid-High
Most Activated
Activation Quartiles
Predicted Probability
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18
3
H3: Influence of Patient Activation on Lifestyle
and Health
Predicted P ercent Fat in D iet by Q uartiles of Activation
47
Predicted Percent Fat
46
46.0
45.0
45
44.4
44
Conclusions
• Collaboration and teamwork among practitioners
and support staff in primary care teams is one factor
ultimately contributing to patient health.
• Practice climate does not influence patients'
lifestyles and health directly, but appears to be
mediated by how practice climate influences patient
trust and patient activation.
43.4
43
42
Le ast Activated
M id-Lo w
M id-H igh
M ost Activated
Activa tion Q uartile s
P redicted P ct Fat
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Conclusions
• Understanding the role of these mediating factors is
important. As Hibbard (HSR, 2005, p. 1919)
summarizes the importance of patient activation:
– “[W]hen clinicians encourage patient engagement in their care, they do so
blinded to any information on the patient’s capabilities for taking on a
self-management role. What often results is a “one size fits all” patient
education approach. If, however, clinicians had information on their
patients’ level of knowledge and skill to self-manage, they could target
self-care education and support to individual patient needs and presumably
be more effective in supporting patient’s self-management.”
• A favorable practice climate supporting the ability of a
practice team to better attend to patient needs and
values, and tailor prescriptions to those needs and
values, may be a key element for achieving effective
care delivery and health outcomes.
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