Racial/Ethnic Disparities in Pain Management

Raymond Tait, PhDSaint Louis University

Disclosures

• Spouse is on the Speaker’s Bureau for Lilly• Center for World Health & Medicine (direct

report) has a project jointly funded by Lilly and J&J

• No discussion of unapproved uses

The study of error is not only in the highest degree prophylactic, but it serves as a stimulating introduction to the

study of truth.

--Walter Lippmann (1922)

Objectives

•To (briefly) review of the literature on racial/ethnic disparities in pain-related healthcare.

•To describe chronic pain characteristics that contribute to patient vulnerability to disparities in treatment and outcomes.

•To review patient, provider, and environmental factors that occasion disparate care.

AHRQ National Healthcare Disparities Report:2012 Quality of Care Indicators

Bl vs Wh As vs Wh AI/AN vs Wh Hisp vs NHW Poor vs Hi $0

20

40

60

80

100

BetterSameWorse

AHRQ National Healthcare Disparities Report:2000-02 vs. 2008-10 Quality of Care Indicators

Bl v Wh As v Wh AI/AN v Wh His v NHW Poor v High $

0

20

40

60

80

100

BetterSameWorse

Disparities in Pain Care: Multiple Conditions & Demographic Groups• Conditions

• Low back pain (Tait et al., 2004)• Acute pain (Salmon & Manyande, 1996)• Recurrent pain (Elander et al., 2006)• Cancer pain (Cleeland et al., 1997)

• Race/ethnicity• Todd et al., 1993; Green et al., 2003; IOM, 2003; Chibnall et al., 2005; Anderson

et al., 2009; IOM, 2011; Meghani et al., 2012• Gender

• Martin & Lemos, 2002; Taylor et al., 2005• Age

• Old (Hadjistravropoulos et al., 2007; Weiner et al, 2002)• Young (Howard, 2003; Anthony & Schanberg, 2005)

• Socioeconomic status• Morrison et al., 2000; Mayberry et al., 2000

Racial and Socioeconomic Factors in Disparate Care

• Socioeconomic factors co-vary with minority status (Mayberry et al., 2000; Meghani et al., 2012)

• Access• Analgesics (Morrison et al., 2000; Green et al., )• Medical care (Meghani et al., 2012)

• Insurance (Zuvekas and Taliaferro, 2003)

• Resources (Tait & Chibnall, 2012)

Disparities in Occupational Lumbar Injury Outcomes Research (DOLOR)

(Agency for Healthcare Research and Quality, R01 HS13087-01)

• Missouri cases of LB injuries that were settled between 1/01 and 6/02– St. Louis city, St. Louis county, Jackson county– 90% of African Americans in the state

• 2,934 cases– 50.3% completed survey– 14.7% refused survey– 35.0% could not be traced

• Data sources– WC database– Telephone survey instruments

Demographics(N = 1,475)

• Age 43.6 years• Education = 13.07 years• Gender = 896 males, 533 females• Race (self-identified) = 889 Caucasian, 540

African Americans, 43 mixed, 3 refused• Working full-time at time of injury = 95.2%• Working full-time now = 62.8%

WC Management Database by Race

Characteristic Caucasian African-American

Medical costs — mean $ (SD) 11,354 (17,755)

3,778 (6,752)

Settlement award — mean $ (SD) 15,328 (13,890)

7,795 (8,927)

Disability rating — mean (SD) 12.9 (10.7)

7.5 (6.4)

Claim duration, months — mean (SD) 23.2 (12.9)

18.2 (10.6)

Predictors of WC Management:Demographics, SES, and Injury*

(Tait et al., Pain, 2004)

Predictors Treatment Costs

Disability Rating

Settlement Award

Claim Duration

Demographics(race, gender, age)

0.10 0.08 0.14 0.10

SES (comp rate, education, income)

0.04 0.02 0.10 0.01

Injury (disc, legal rep, sprain/strain)

0.11 0.10 0.15 0.05

Model 0.25 0.20 0.39 0.16

* Simultaneous entry multiple hierarchical regression: R2 change (all P’s < 0.001)

WC Database: Surgical vs. Non-Surgical Treatment

(Chibnall et al., Spine, 2006)

Surgery: No

Surgery: Yes Total

Caucasian N = 62470% w/in race

N = 26830.0% w/in race

N = 892100.0%

African American

N = 53692.4% w/in race

N = 447.6% w/in race

N = 580100.0%

Total N = 116078.8% w/in race

N = 31221.2% w/in race

N = 1472100.0%

2(1) = 106.1, P < 0.0001

OR = 4.0; 95% CI = 2.9 – 5.4

Claimants with HNP: Predictors of Surgery*

Variables Odds Ratio OR 95% CI P

Race 0.32 0.21-0.49 <.001

Radicular pain 2.86 1.21-6.74 <.05

Legal rep (2o to Rx dissatisfaction) 0.57 0.39-0.84 <.01

Legal representation 1.42 0.87-2.33 =.16

SES 1.14 0.96-1.36 =.13

Gender 0.91 0.61-1.35 =.63

Age 1.05 0.81-1.12 =.57

Lumbar degeneration 1.01 0.71-1.42 =.98

*No surgery vs surgery: 2(8) = 59.6, P < .001; R2 = 0.13 (N =640)

Clinical Outcomes: 2 Years Post-Settlement

(Chibnall et al., Pain, 2005)

African American Caucasian

Mean / SD Mean / SD

Usual Pain* 6.4 / 2.0 5.0 / 2.0

Catastrophizing* 28.3 / 12.8 22.7 / 12.3

PDI* 35.7 / 18.1 28.0 / 17.4

* P < 0.0001

6-Year Follow-Up: High Levels of Pain, Catastrophizing, and Disability

(Chibnall & Tait, Pain Medicine, 2011)

Criterion Variable: Long-term Follow-up*

Significant Predictors (P < 0.05)

OR (95% CI)

Pain intensity

Race (0 = Caucasian, 1 = African American)

2.6 (1.5-4.3)

Pain (high vs. < high) at baseline 6.2 (3.6-10.6)

Catastrophizing (PCS)

Race (0 = Caucasian, 1 = African American)

1.9 (1.2-3.1)

SES 0.48 (0.34-0.67)

Catastrophizing (high vs. < high) at baseline

3.6 (2.2-6.1)

Disability (PDI)SES 0.62 (0.43-0.83)

Disability (high vs. < high) at baseline 7.2 (4.1-12.7)

* 1 = high (pain ≥ 7; PCS ≥ 30; PDI ≥ 45) vs. 0 = less than high

Race Effects on Financial Court Actions: 5 Years Post-Settlement

(Tait & Chibnall, Spine, 2012)

00.5

11.5

22.5

33.5

44.5

55.5

66.5

77.5

88.5

99.510

Baseline Year 1 Year 2 Year 3 Year 4 Year 5

Post-Settlement Years

Pct.

Cha

nge

from

Bas

elin

e

Caucasian

African American

*

**

*

* *

*

Implications for Race & SES

• Race/ethnicity and SES are associated with differences in patient/provider approach to treatment and intermediate-term outcomes– Race/ethnicity appears to account for greater effect

during active clinical management• Race/ethnicity and SES are associated with

differences in long-term outcomes– SES accounts for greater long-term effects

• What accounts for disparate clinical management?

Judging Pain in Others: A Social Interaction

ENVIRONMENTPATIENT

PROVIDER

Judging Pain in Others: A Projective Test?

One Patient

Two Providers

Opinion #1 Opinion #2

Distinctions between Acute and Chronic Pain

Acute1. Pain as symptom2. Biologic utility3. Anxiety4. Opioids OK5. Low addiction potential6. Pathology recognized7. Cure likely

Chronic1. Pain as disease2. Little utility3. Depression4. Opioids problematic5. Poly-addiction potential6. Pathology unclear7. Cure often not possible

Glasgow Illness Model(Adapted from Waddell et al., Pain, 1993)

Pain/Illness

Attitudes & Beliefs

Psychological Distress

Illness Behavior

Sick Role

Internist Judgments of Chronic Low Back Pain(Chibnall, Dabney & Tait, Pain Medicine, 2000)

• 48 internists from an academic school of medicine• 2 x 4 mixed between and within-subjects design• Vignettes describing hypothetical low back pain

patients varied by pain severity (low vs. high) • Internists provided 4 waves of clinical information

(history physical exam findings functional disability diagnostic test results)

• Measures = MD judgments regarding patient medical/psychological/disability status, treatment, diagnostic testing, and referral options

MD Judgments: Reliability Across 4 Waves of Information

Outcome VariablesIntra-Class Correlation

Within MD Between MD

Vertebral or diskal lesion 0.72 0.07

Soft tissue, musculoskeletal 0.71 0.03

Personality factors 0.75 0.06

Orthopedic surgery referral 0.87 0.04

Psychiatry referral 0.49 0.04

Physical therapy referral 0.91 0.04

Prescribe opioids 0.88 0.05

Order MRI 0.69 0.12

Occupational disability level 0.63 0.11

RATES OF AGREEMENT IN PATIENT & CAREGIVER PAIN RATINGS(from Grossman et al., Correlation of patient and caregiver ratings of cancer pain,

J. Pain Symp Manag, 1991; 6:53-57)

Patient VAS Ratings of Pain

Low (VAS 0-2)

Medium (VAS 3-6)

High (VAS 7-10)

Patient/Nurse 82% 51% 7%

Patient/House Officer 66% 26% 20%

Patient/Oncology Fellow 70% 29% 27%

Patient/Care Giver (Avg) 79% 37% 13%

High Pain Severity: Implications for Clinical Judgment

Pain Report

Low(1-3)

Moderate(4-6)

High(7-10)

Little likelihood of context

effects

Some likelihood of context effects

without objective evidence

High likelihood of context effects with/without

objective evidence

The Patient (“The Target”): Characteristics that Influence Judgments

Patient Factors that Influence Judgments

• Chronicity– Klein et al., 1982; Teske et al., 1983; Taylor et al., 1984; Leclere et al.,

1990; Eccleston et al., 1997; Hahn, 2001 • Distribution

– Ransford et al., 1976; Von Baeyer et al., 1983; Margolis et al., 1986; Tait et al., 1990

• Behavior– Prkachin et al., 1994; Krause et al., 1994; Solomon et al., 1997;

Prkachin et al., 2001 • Demographic

– Race/ethnicity– Age– Gender

Ethnicity as a risk factor for inadequate emergency department analgesia(Todd, Samaroo, Hoffman. JAMA, 1993)

Sample: Hispanic and white emergency department patients with isolated long-bone fractures

Hispanics more than twice as likely as whites to receive NO analgesic medication for pain.

Significant predictors of analgesics:

EthnicityNeed for fracture reductionPatient primary languageTotal time in ER

Analgesic non-predictors:Patient genderInsurance statusOccupational injuryTime of presentationAdmission status

The Context (“The Situation”):Characteristics that Influence Judgments

Factors that Influence Judgments: Situational Features

• Compensation status– Hadler, 1994; Kennedy, 1997; Chibnall and Tait,

1999; Merskey and Teasell, 2000; Kappesser et al., 2006

• Medical evidence– Carey et al., 1988; Birdwell et al., 1993; Tait and

Chibnall, 1994; Chibnall and Tait, 1995; Chibnall et al., 1997; Tait et al., 2006

Medical Procedures for Assessment of Chronic Pain

(Rudy et al, Pain, 1988)

1. Neurological exam2. Gait/posture3. Spinal mobility4. Muscle function (tone, mass, strength)5. Soft tissue exam6. Mobility of weight bearing joints7. Plain radiography8. Mobility of non-weight bearing joints

9. CT scan10. Electromyography11. Contrast radiography12. Internal organ exam13. Nuclear medicine14. Laboratory tests15. Thermography16. Blood count17. EEG18. ECG

Incremental Certainty of Disability: Low Back Pain

(Carey et al., J Clin Epidemiol 1988;41:691-697)

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14C

ert

ain

ty o

f d

isa

bil

ity

The Provider (“The Judge”):Characteristics that Influence Judgments

Cognition in Intuition and Reasoning(from Kahneman, American Psychologist, 2003)

Intuition ReasoningProcesses Fast Slow

Parallel Serial

Automatic Controlled

Effortless Effortful

Associative Rule-governed

Slow-learning Flexible

Emotional Neutral

Content Conceptual representations

Past, present and future

Can be evoked by language

Key Constructs of Cognitive Miser

• Tends to attribute behavior to personal disposition, not situational factors– Behavior “engulfs the field” (Heider, 1958)

• Makes common use of stereotypes– Cognitive structures that represent simplified

knowledge about a concept or type of stimulus– Facilitates “top-down,” conceptually driven

information processing– Shapes expectations

Features of Stereotypes• Usually cued by visually prominent physical

features • Commonly applied to attributes such as gender,

race, SES, age, mental health, attractiveness• Operates on perceptions at earliest moments (i.e.,

expectancies)• Creates less complex concepts• Stereotype consistent information more easily

remembered than inconsistent information– Encoding inconsistent information requires effort

Judging Pain: Physician Specialty(Tait et al., 2010)

VariableNeurosurgeons

Mean (SD)Internists

Mean (SD)

Pain severity (0-10)** 4.46 (1.56) 5.71 (1.54)

Home disability (0-10)* 3.83 (1.77) 4.61 (1.70)

Social disability (0-10)* 3.69 (1.97) 4.71 (2.01)

Work disability (0-10)* 4.40 (2.12) 5.37 (1.62)

Occupational disability (0-100)** 27.6 (19.2) 45.1 (22.8)

* P < 0.05; ** P < 0.001

Pain Management: A Social Transaction

• Pain management is an interactive phenomenon – Social transaction (Craig et al., 2010)– Participative decision-making (Frantsve & Kerns, 2006)– Social contract (Kappesser et al., 2008)

• Contract influenced by assumed roles (patient and provider) • Implied contractual demands of patients with severe, chronic pain

– Fix me – At least help me—analgesic medications (opioids?)– Handle any regulatory implications– Assume long-term management (not cure)– Embrace high (ongoing?) time demands– Recognize the likelihood of associated psychological distress– Tackle disability-related sequelae– Manage sick role, litigation and other system issues– Treat likely co-morbidities– Prepare for high costs of care

Conclusions I: Pain management as Social Judgment

• Judgments regarding pain assessment and treatment fit a (complex) social cognition model

• Racial/ethnic stereotypes appear to operate in clinical encounter

• Social cognitive influences are greatest when pain is severe and supporting medical evidence is lacking– Patient factors (e.g., race/ethnicity) susceptible to symptom

discounting under conditions of high pain severity • Pain management best viewed as a social transaction

Situational Factors that Influence Judgments

Invalidating Influence Validating Influence

No objective medical evidence Objective medical evidence

Litigation No litigation

Time urgency No time pressure

Patient Factors that Influence Judgments

Invalidating Influence Validating Influence

High pain severity Low/moderate pain severityChronic Acute

Non-dermatomal distribution Dermatomal distribution High pain behaviors Moderate pain behaviors

Old/young age Middle ageMinority status Non-minority statusFemale gender Male gender

Dramatic presentation Business-like presentationHigh psychological distress Low psychological distress

Provider Factors that Influence Judgments

Invalidating Influence Validating Influence

Clinical over-exposure Pain-specific training

Negative valence Positive valence

High provider burden Low provider burden

Low empathy High empathy

Single provider model Multi-disciplinary model

Conclusions II: Strategies to Reduce Disparities in Care

• Treatment guidelines/education may minimize errors in judgment– Evidence-based medicine?

• Multidisciplinary approaches– Maximize sources of input – Distribute treatment burden – Lessen empathy influences

• Multiple sources of information to reduce bias– Pain severity, pain distribution, pain behavior – Levels of pain-related disability – Psychological distress as modifying, not invalidating

pain experience