overcoming healthcare disparities: the role of patient-centered care lisa a. cooper, md, mph...
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Overcoming Healthcare Disparities:The Role of Patient-Centered Care
Lisa A. Cooper, MD, MPH
Professor of Medicine, Epidemiology, and Health Policy and Management
Johns Hopkins Medical Institutions
Racial and ethnic disparities in health are documented
• Life expectancy at birth – Blacks vs. Whites,10 year gap for men, 5 year gap for women
• Infant mortality rate – Blacks and Native Americans vs. Whites: twice as high
• Death rate – Blacks vs. whites: greater for cancer, diabetes, heart disease, HIV/AIDS, homicide; Hispanics vs. Whites: greater for diabetes
• Morbidity – most ethnic minorities vs. Whites: higher for cancer, diabetes, hypertension, obesity, HIV/AIDS, tuberculosis, hepatitis
Potential Reasons for Disparities in Health
•Biologic factors•Socioeconomic status•Environmental factors•Discrimination/Stress•Cultural factors•Health risk behavior•Access to healthcare•Quality of healthcare
Race Health
Access to Health Care for Racial and Ethnic Groups
Barriers Health Care Processes
Use of Services
Mediators
Outcomes
Visits
primary care specialty emergency Procedures preventive diagnostic therapeutic
Health Status mortality morbidity well-being functioning
Equity of Services Patient Views of Care
experiences satisfaction effective
partnership
Quality of providers cultural competence communication skills medical knowledge technical skills bias/stereotyping Appropriateness of care Efficacy of treatment Patient adherence
Personal/Family acceptability cultural language/literacy attitudes, beliefs preferences involvement in care health behavior education/income
Structural availability appointments how organized transportation
Financial insurance coverage reimbursement
levels public support
Modified From Access to Health Care in America (1993, Millman M, ed).Cooper LA, Hill MN, and Powe NR. JGIM 2002; 477-486
Unequal Treatment: A Report of the Institute of Medicine*
Whites Ethnic minorities
Clinical Appropriateness and Need, Patient Preferences
Systems, Legal, Regulatory
Discrimination, Bias, Clinical uncertainty
Disparity
Difference
Qua
lity
of
Car
e
*National Academy Press, Washington DC, 2003
Racial and ethnic healthcare disparities are pervasive
• Conditions: cancer, diabetes, heart disease, kidney disease, HIV/AIDS, mental health, respiratory diseases (e.g., asthma)
• Populations: young, old, urban, rural, men, women, immigrants, non-immigrants
• Settings: primary care, emergency care, hospital care, specialty care, nursing homes
• Levels and types of care: preventive, acute care, chronic disease management
• Dimensions of healthcare quality: timeliness, effectiveness, safety, patient-centeredness
Dimensions of Health Care Quality
• Structure: “characteristics of the settings in which care is delivered…”
• Process: “ …the care itself, or activities undertaken by the health care system…”
• Outcome: “the effect of care on the health and welfare of individuals or populations…”
Donabedian A. JAMA 1988;260:1743-1748
Process
Structure Outcome
interpersonal, technical care, or
appropriateness of care
race concordance, staff expertise, availability, organization, coordination,
patient ratings of care, equity of services
death, complications
Examples of Structure, Process, and Outcome Variables
Disparities in Process of Care• Technical care – many studies
– Ethnic minorities receive fewer preventive services, diagnostic and therapeutic tests and procedures, and fewer appropriate medications
• Patient-centered or interpersonal care – fewer studies– Ethnic minority patients rate interpersonal care from
physicians more negatively than whites– It is unclear whether this is due to ethnic/racial
discordance, poor communication, bias, or mistrust
• Few disparities studies make links between structure, processes, and outcomes
Process
Structure Outcome
Interpersonal or Patient-centered Care
Race Concordance
Patient ratings of PDM
* physicians’ participatory decision-making style
Concordance• What is it?
– a structural dimension of health care quality– shared identities between patients and health
professionals
• Why do we care? – Because most ethnic minorities see physicians who
differ from them in key social characteristics
• Patients and physicians may be concordant in:– Visible demographic factors such as race/ethnicity,
gender, age, education, social class, language– Less visible factors such as beliefs, values,
expectations, preferred roles
Patient-centered Care
“Providing care that is respectful of and responsive to individual patient preferences, needs, and values, and ensuring that patient
values guide all clinical decisions…”
*Institute of Medicine, “Crossing the Quality Chasm, 2001
Race, Gender, and Partnership in the Patient-Physician
Relationship• Design: Cross-sectional telephone survey • Subjects: 1816 adults (784 W, 814 AA, 218 Other)
who had seen their MD (n=65) within the past 2 weeks• Setting: 32 primary care practices, large network style
managed care organization in Washington D.C. area• Predictor variables: race and gender concordant or
discordant status in patient-physician relationship• Main Outcome: patients’ ratings of their MD’s
participatory decision-making (PDM) styleCooper-Patrick L et al, JAMA 1999;282:583-589
Measurement of Physicians’ Participatory
Decision-Making Style*Patient is asked:• If there were a choice between treatments, how
often would this doctor ask you to help make the decision?
• How often does this doctor make an effort to give you some control over your treatment?
• How often does this doctor ask you to take some of the responsibility for your treatment?
*Kaplan SH et al, Medical Care 1995;33:1176-1187Each item contributes 33.3 points. Maximum score is 100 points.
Ethnic minorities rate their visits with physicians as less participatory
77.1
73.9 73.8
72
73
74
75
76
77
78
PD
M s
core
Whites
Blacks
Others
PDM scores range from 0-100. A higher score means visit is more participatory.
Cooper-Patrick L , JAMA 1999;282:583-589
P=0.007
P=0.05
Patients in race-concordant relationships rate their physicians as
more participatory
61.1
63.3
58.5
61.7
56
57
58
59
60
61
62
63
64
Race Gender
concordant
discordant
Adjusted for patients’ age, gender, education, marital status, health status, length of the patient-physician relationship, physician gender (race concordant analysis) and physician race (gender concordance analysis). Cooper-Patrick L, JAMA 1999;282:583-589
P=0.02
Mea
n P
DM
Sty
le S
core
P-value NS
Process
Structure Outcome
Interpersonal or Patient-centered Care:
Communication
Race Concordance Patient ratings of PDM* and Satisfaction
* physicians’ participatory decision-making style
Patient-physician communication is related to important outcomes
• Patient adherence
• Patient satisfaction
• Clinical outcomesGlycemic controlBP controlPain reductionDepression resolution
Roter 1988, Greenfield 1988, Kaplan 1989, Stewart 1995, Kaplan 1995
Patient-Centered Communication, Ratings of Care and Concordance
of Patient and Physician Race• Design: cross-sectional study using pre-visit and
post‑visit surveys and audiotape analysis • Participants: 458 African American and white
adult patients receiving care from 61 PCPs• Setting: urban primary care practices serving
managed care and fee-for-service patients• Patient recruitment: ~10 patients per MD
recruited consecutively from waiting roomsCooper LA, Roter DL, Johnson RL, Ford DE, Steinwachs DM, Powe NR.
Ann Intern Med 2003;139:907-915
Functions of Clinical Communication
• Data-gathering
• Educating and counseling patients
• Relationship-building
• Partnering with patients to negotiate diagnostic and treatment decisions
Lipkin, Putnam, & Lazare, 1995
Measuring Clinical Communication*
• Content (questions and information-giving)– Biomedical talk– Psychosocial talk
• Affect – Emotional Talk - Negative talk– Positive talk - Social talk
• Process– Orientation (directions or instructions)– Facilitation (includes partnership-building)
*Roter Interaction Analysis System (RIAS)
Roter D, Larson S. Patient Educ Couns 2002;46:243-51
Examples from RIASCommunication Categories
• Biomedical talk “Your blood pressure is 100 over 70.”“I was in the hospital last year for ulcers.”
• Psychosocial talk“You really need to get out and meet more people.”“I guess every marriage has its ups and downs.”
• Emotional talk“This must be very hard for you.”“I hope you’ll be feeling better soon.”
• Partnership-building“Do you follow me?” “How does that sound to you?”
Measuring Emotional Tone of Visits using the RIAS
Coders are asked to rate overall emotional tone of the visit for patients and physicians:
• Physician positive affect = (assertiveness + interest + responsiveness + empathy) - hurried
• Patient positive affect = (assertiveness + interest + friendliness + responsiveness + empathy)
The Patient-CenteredClinical Interview
• Visit duration is longer• Speech speed is lower• Physicians are less verbally dominant
• doctor talk to patient talk ratio is close to 1
• Patient-centeredness ratio is high: more psychosocial, emotional, and partnership talk than biomedical talk
• More positive emotional tone
Physicians communicate differently with black and white patients
Communication measure Whites
n=202
Blacks
n=256
p-value*
Physician verbal dominance 1.50 1.73 <0.01
Physician positive affect** 14.1 13.2 0.02
Patient positive affect** 16.7 15.8 <0.01
Patient-centeredness ratio 1.91 1.58 0.08
Adjusted for: patient age, gender, education level, and self-rated health status; and physician gender, race, time since completing training, and report of how well he/she knows each patient.*p-value from linear regression with GEE.** Patient and physician affect scores are derived from audiotape coders’ impressions of the overall emotional tone of the medical visit.
Johnson RL, Roter DL, Powe NR, Cooper LA. Am J Public Health 2004;94:2084-2090.
17.518.2
16.4
13.2
15.4
19.2
15.8
12.7
10
15
20
Visitduration,minutes
Speechspeed per
minute
Patientpositive
affect
Physicianpositive
affect
concordant
discordant
Race-concordant visits are longer with slower speech and more
positive patient emotional tone
Adjusted for patient age, race, gender, and health status, physician gender & yrs in practice Cooper LA et al, Ann Intern Med 2003;139:907-915
P=0.01P=0.03
P=0.05
P=0.19
Patients in Race-Concordant Relationships Rate Their Physicians Better
76.1 73 7368
5157
0
10
20
30
40
50
60
70
80
ParticipatoryDecision-making
Overall Satisfaction Recommend MD to afriend
concordant discordant
Analyses adjusted for patient gender, race, age, and health status, physician gender, years in practice, and patient-centered communication.
Cooper LA et al, Ann Intern Med 2003;139:907-915
Me
an
Sc
ore
/Pro
ba
bili
ty P=.01 P<.01 P=.03
Summary• African American patients experience visits in which
physicians are less patient-centered
• African Americans in race-discordant relationships with their physicians experience:
– Lower levels of satisfaction
– Less participation in medical decisions
– Shorter visits with less positive emotional tone
• Differences in communication do not explain why patients in race-discordant relationships rate their care worse
• Other factors, such as physician and patient attitudes, may play a role
Process
Structure Outcome
Interpersonal Care:Bias
Race Concordance Patient ratings of care
Explicit vs. Implicit Bias
• Explicit (conscious) bias: attitudes and beliefs we recognize and know we have
• Implicit (unconscious) bias: attitudes that are unavailable to introspection and outside of conscious cognition– Can unintentionally affect behavior– Are better predictors of behavior than self
reported measures of prejudice, stereotyping and discrimination
Clinician Racial Bias, Communication Behaviors and
Patient Experiences of Care• Design: Cross-sectional study• Participants: 39 primary care clinicians and
213 of their African American patients• Setting: 24 urban, community-based primary
care practices in Baltimore, Maryland and Wilmington, Delaware
• Main predictor variables: Clinicians’ implicit attitudes about race (race attitude IAT and patient race/medical compliance IAT)
The Race Implicit Association Test(http://www.implicit.harvard.edu)
• An indirect measure of an individual’s implicit (unconscious) attitudes
• Images appear rapidly on computer screen and subjects respond by sorting pairs of images and attributes using right and left keys
• Premise: individuals will respond faster to concepts that are strongly associated compared to those that have weak associations
• If subjects match white+good/black+bad pairings faster than black+good/white+bad pairings, then the race IAT score differs from zero and is positive – labeled implicit white preference
Greenwald, McGhee, Schwartz, 1998
Implicit preference for whites:Response to these pairings is faster…
&African
American unpleasant
pain
death
stink
grief
agony
filth
tragedy
vomit
European American&pleasant
gentle
happy
smile
joy
warmth
pleasure
paradise
rainbow
…than response to these pairings
& unpleasant
pain
death
stink
grief
agony
filth
tragedy
vomit
European American
African American&pleasant
gentle
happy
smile
joy
warmth
pleasure
paradise
rainbow
Implicit association for European American and compliant patient
Response to these pairings is faster…
&
willing
cooperative
compliant
reliable
adherent
helpful
European American
African American&
doubting
reluctant
hesitant
apathetic
resistant
lax
ReluctantPatient
Compliant Patient
…than response to these pairings
&
doubting
reluctant
hesitant
apathetic
resistant
lax
European American
African American&
willing
cooperative
compliant
reliable
adherent
helpful
Compliant Patient
ReluctantPatient
Methods, continued• Main outcomes:
– Audiotaped Measures: Clinician and patient communication behaviors measured by Roter Interaction Analysis System (RIAS)
– Patient ratings of care: overall satisfaction, trust in clinician, participation in decision-making, and quality of interpersonal care measured by post-visit survey
• Analysis: determine whether clinicians’ implicit attitudes predict differences in communication and patient ratings of care*
*Linear and logistic regression with generalized estimating equations to account for clustering of patients by clinician
Measuring Clinical Communication*
• Content (questions and information-giving)– Biomedical talk– Psychosocial talk
• Affect – Emotional Talk - Negative talk– Positive talk - Social talk
• Process– Orientation (directions or instructions)– Facilitation (includes partnership-building)
*Roter Interaction Analysis System (RIAS)
Roter D, Larson S. Patient Educ Couns 2002;46:243-51
Audiotape Ratings of Clinicianand Patient Emotional Tone
• Clinician behaviors– Positive affect – average of 6 items each rated on
a 5-point scale: interest, warmth, engagement, respect, and sympathy
– Negative affect – average of 2 items each rated on a 5-point scale: dominance and hurried/rushed
• Patient behaviors– Positive affect – average of 5 items each rated on
a 5-point scale: interest, warmth, engagement, sympathy, and respect
Patient Ratings of Clinician• Overall satisfaction
– Overall, I was satisfied with this visit– I would recommend this provider to a friend
• Quality of interpersonal care– My provider has a great deal of respect for me– My provider likes me– I like this provider
• Participation in decision-making– If there were a choice, this provider would ask me to help
make the decision
• Trust in provider– I trust this provider to act in my best interests
Responses are on 5-point Likert scale from strongly agree to strongly disagree.
Interpersonal CareQuality Measures
• Patient-centeredness ratio is high: more psychosocial, emotional, and partnership talk than biomedical and procedural talk
• Clinicians and patients exhibit more positive emotional tone and less negative emotional tone
• Patients report higher levels of trust, respect, and satisfaction, and participation in decision-making
Characteristics of CliniciansCharacteristic (N=39)
Mean age, yrs (SD) 44.1(8.2)
Practice experience, yrs (SD) 13.5 (7.4)
Female gender,% 64
Caucasian, % 49
African American,% 21
Asian, % 23
Liberal political idealogy, % 73
Internal medicine training, % 77
Board certified,% 90
Characteristics of Patients
Characteristic N=213
Mean age, yrs (SD) 54.5 (13.3)
High school graduate, % 81
Female gender, % 73
African American,% 100
Have health insurance,% 91
Annual income < $35,000, % 60
Poor/fair self-rated health status 46
Known by clinician (not first visit) 90
Clinician Responses to IAT(N=39)
14%
26%
26%
10%
14%
5%
5%
Strong preference for Whites
Moderate preference for Whites
Slight preference for Whites
Little to no preference
Slight preference for Blacks
Moderate preference for Blacks
Strong preference for Blacks
Percent of respondents with each score
66%
The IAT D (difference score) ranges from -2 to +2, with 0 indicating no relative preference for blacks compared to whites, and positive scores indicating some degree of implicit bias favoring Whites. [mean score for this sample is +0.24 (.49)]
27%
27%
16%
17%
6%
4%
2%
Strong preference for Whites
Moderate preference for Whites
Slight preference for Whites
Little to no preference
Slight preference for Blacks
Moderate preference for Blacks
Strong preference for Blacks
Percent of Harvard website respondents with each score
70%
Implicit Preference for White vs. Black People by732,881 respondents on Project Implicit websites,
July 2000- May 2006
Association of Clinician Implicit Racial Bias with
Communication BehaviorsCommunication behavior β-coefficient P-value
Patient-centeredness -0.67 0.29
Clinician positive affect -0.28 0.21
Clinician negative affect +0.23 0.03
Patient positive affect -0.18 0.03The beta coefficient means for each 1-point increase in the IAT score --indicating more pro-white bias among clinicians – clinician’s negative affect was higher and African American patients’ positive affect was lower . Adjusted for patient age, education, health status, clinician’s gender, race, and the interaction of clinician race with implicit bias.
Association of Clinician Race/Medical Compliance Bias with Communication Behaviors
Communication behavior β-coefficient P-value
Patient-centeredness -3.12 0.004
Clinician positive affect -0.14 0.38
Clinician negative affect +0.02 0.95
Patient positive affect -0.04 0.81
The beta coefficient means for each 1-point increase in the IAT score --indicating more pro-white bias among clinicians – the communication in the visit was less patient-centered. Adjusted for patient age, education, health status, clinician’s gender, race, and the interaction of clinician race with implicit bias.
Clinician Racial Bias andPatient Reports of Care
0 0.5 1.0 1.5 2.0 4.0 6.0 8.0 10.0
I trust this doctor
I would recommend this doctor to a friend
I like this doctor
This doctor asks me to help decide my treatments
This doctor respects me
I was satisfied with this visit
Odds Ratio
0.63
0.24
0.32
0.22
0.47
0.48
As the implicit bias score increases the patient has lower odds of strongly agreeing
Clinician Race/ Medical Compliance Bias and Patient Reports of Care
0 0.5 1.0 1.5 2.0 4.0 6.0 8.0 10.0
I trust this doctor
I would recommend this doctor to a friend
I like this doctor
This doctor asks me to help decide about my treatments
This doctor respects me
I was satisfied with this visit
Odds Ratio
0.49
0.48
0.57
0.89
0.55
0.20
As the implicit bias score increases the patient has lower odds of strongly agreeing
Summary• This is the first study to explore links among
implicit bias, clinician behaviors, and patient ratings in actual patient encounters
• Primary care clinicians in this sample display implicit attitudes about race that are similar to those measured in large samples of society
• Implicit bias favoring whites and the association of white race with medical compliance predicts:– less patient-centered communication – more negative clinician emotional tone– less positive patient emotional tone– poorer ratings of care by African-American patients
Implications• Research – Examine links among clinician
attitudes, behaviors, and health outcomes• Health Professional Education - employ patient-
centered communication skills programs that emphasize rapport building and affective dimensions and enhance awareness of bias and intercultural skills
• Clinical Practice - implement patient activation programs; improve scheduling, increase time to build rapport and develop continuity of care
• Policy - increase numbers of underrepresented ethnic minorities among health professionals
Minority Health Policy Timeline
1970 20081990
1985 DHHS Heckler Report
Minority Health and Health Disparities Research and Education Act of 2000
2003 IOM Report “Unequal Treatment” and first National Healthcare Disparities Report published
1972Tuskegee Syphilis Study becomes public
1980
Health Revitalization Act of 1993 establishes the Office of Research on Minority Health
2000
Evolution of Research on Health Disparities
1980 20001990Describing the problem
Understanding mechanisms Designing interventions Evaluating outcomes
Patient-Physician Partnership to Improve
HBP Adherence• Design: Randomized controlled trial• Population: 50 primary care MDs and 500
patients (60% AA) with high blood pressure• Setting: 15 urban, community-based clinics in
East and West Baltimore• Interventions: Communication skills training on
interactive CD-ROM for MDs; Patient activation by community health worker
• Main Outcomes: patient adherence, BP controlSupported by the National Heart, Lung, and Blood Institute
R01HL69403, 09/01/01-08/31/07
• Design: Randomized controlled trial• Population: 30 primary care clinicians and 250
African American patients with depression • Setting: Urban, community-based clinics in
Delaware and Maryland• Interventions: standard quality improvement vs.
patient-centered, culturally tailored program• Main Outcomes: Depression remission,
depression level, guideline-concordant care
Blacks Receiving Interventions for Depression and Gaining Empowerment
Supported by the Agency for Healthcare Research and Quality R01 HS13645-01, 09/30/03-09/29/09
Funding Sources• National Heart, Lung, and Blood Institute
– R01HL69403 and K24HL083113
• Agency for Healthcare Research and Quality– R01HS013645
• National Center for Minority Health and Health Disparities (P60MD000214)
• Robert Wood Johnson Foundation Amos Medical Faculty Development Program
• The Commonwealth Fund• Fetzer Foundation
Acknowledgments
• Debra Roter• Neil Powe• Daniel Ford• Rachel Johnson• Don Steinwachs
• Mary Catherine Beach• Thomas Inui• Anthony Greenwald• Janice Sabin• Kathryn Carson