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The Influence of Primary Care Practice Climate on Patient Trust

in Physician, Activation, and Health

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

Project FundingCenters for Disease Control and Prevention

NIH 1R01CD000033 (ER Becker, PI)

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Background• 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:– 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.

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Background• 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.

• 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.

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Objectives• 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.

– H3: Greater patient activation will have a positive association with the practice of healthy lifestyle and health status.

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Study Population

• 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:

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)

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Survey Instrument Development

• Literature review to identify, brief reliable items or scales administered in written surveys:– 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

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Survey Administration

• 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)– 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

• Psychometric properties of previously validated scales were similar between these survey respondents and respondents to surveys where scales were initially used.

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Practice Team Sample and Survey

• 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– 35 items– 83 practitioners (MD, PA, NP) among 97 (86%

response rate)– 158 support staff among 187 (85% response rate)

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H1: Practice Climate as an Antecedent of Trust

• Dependent 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

• 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

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H1: Practice Climate as an Antecedent of Trust

• 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.– 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

Predicted Trust in Physician and 95% Confidence Intervals by Lowest to Highest Team Practice Climate Scores

61

62

63

64

65

66

67

68

Teams (Ordered by Practice Climate Scores)

Pre

dic

ted

Tru

st

Predicted 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

-30

-25

-20

-15

-10

-5

0

5

10

15

20

25

30

LOWEST MID-LOW MID-HIGH HIGHEST

Respondents Classified by Quartiles of Trust in Physician

Dif

fere

nc

e i

n P

erc

en

t o

f R

es

po

nd

en

ts S

tati

ng

"A

lo

t" a

nd

Pe

rce

nt

Sta

tin

g "

No

ne

"

Exercise Diet

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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– 13 item scale scored 0 (lowest) to 100 (highest) – Cronbach’s α = 0.95

• 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

• Ordinary least-squares linear regression– Covariates: age, gender, condition cohort, race, martial

status, and education

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H2: Influence of Trust on Patient Activation

• Patient activation was significantly, positively associated with trust in physicians.– β = 0.20 point change in patient activation per

point change in trust in physician (p ≤ 0.01)

• Patients in the upper quartile of trust in physician had significantly greater average activation than patients in the lower quartile of trust in physician.

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H2: Influence of Trust on Patient Activation

Predicted Activation and 95% Confidence Intervals by Quartiles of Trust in Physician

63.7

67.2

69.6

73.5

60

62

64

66

68

70

72

74

76

78

LOWEST MID-LOW MID-HIGH HIGHEST

Trust in Physician Quartiles

Pre

dic

ted

Ac

tiv

ati

on

Predicted Activation

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H3: Influence of Patient Activation on Lifestyle and Health

• Dependent variables: – 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) – 13 item scale scored 0 (lowest) to 100 (highest) – Cronbach’s α = 0.95

• Ordinary logistic or 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

• Patients with higher activation were more likely (p<0.05) to report recommended exercise levels.

• Patients with higher activation had better dietary intake: – 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).

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H3: Influence of Patient Activation on Lifestyle and Health

Predicted Probabilities and 95% Confidence Intervals for Achieving Recommended Exercise Levels by Quartiles of Activation

44.1%

53.2%

59.5%

68.1%

35%

40%

45%

50%

55%

60%

65%

70%

75%

80%

Least Activated Mid-Low Mid-High Most Activated

Activation Quartiles

Pre

dic

ted

Pro

ba

bil

ity

Predicted Probability

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H3: Influence of Patient Activation on Lifestyle and Health

Predicted Percent Fat in Diet by Quartiles of Activation

46.0

45.0

44.4

43.4

42

43

44

45

46

47

Least Activated Mid-Low Mid-High Most Activated

Activation Quartiles

Pre

dic

ted

Pe

rce

nt

Fa

t

Predicted Pct Fat

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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.

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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.