Understanding Primary Care Phy

Treatment of Chronic Low Bac

Sean M. Phelan, MPH

PhD Candidate, Epidemiology

University of Minnesota School of Public Hea

Research Fellow, Center for Chronic Disease Outcome

Minneapolis VAMC

Contributors: Diana Burgess*, Michelle van Ryn#, M

Center for Chronic Chronic Disease Disease Outcomes Outcomes Research Research, Minneapolis Minneapolis VAMC* a

Family Medicine# & Biostatistics+, University of Minnes
Purpose

1. To empirically define classes of physic

according according to their approach approach to treatin

treatin

uncontrolled chronic low back pain

2. To identify physician characteristics, a

& b li f e e s and practice ch t i ti aracteristics t

predict class membership
Chronic Pain Treatment

• P l reva ence of ch i ron c non‐cancer pain hi hg a

VA.

– In one study, ~60% of VA patients discharged 

10/1/01 and 11/30/07 reported pain and 26% 

moderate moderate to severe pain. ( k ll Haskell et al, 2009)

– Much variability in physicians’ treatment deci

Hay et al 2008)

– Lack of consensus on treatment despite VA an

organizations’ guidelines

• VA/DoD Guidelines Guidelines specify specify that opioids opioids shoul

when other pain therapies are inadequate
Historical Trends

• Use of opioids to treat chronic pain increased t

1990 s’

– clinical community and regulatory boards more supportive 

(Gilson & Joranson 2001)

– compensation systems f d avore b f rie visits for medication m

(Gallagher & Rosenthal 2008)

– aggressive marketing (Olsen, Daumit, Ford 2006)

• Use leveled off in the 2000’s as concerns over t

side‐effects, diversion, and dependence grew

• More recently, use of opioid treatment has incr

there remains remains wide variability variability in whether whether opioi

opioi

• Little is known about frequency of multimodal 

treating chronic pain
Efficacy Efficacy of Opioids Opioids for Chron

Chron

• Recent meta‐analysis of studies of opio

efficacy for long‐term reduction in chrocancer pain found

• significant reduction in pain across studie• signs of opioid addiction in only .05%, and 

only .43% of p p articipants.

• However, 33% of p p articipants using ora

discontinued treatment due to side‐eff

12% withdrew due to insufficient pain 

(Noble et al 2008)
Efficacy of Psychological Psychological The

The

• Cl l inica trials provide evidence that Cog

Behavioral Therapy reduces pain severi

(Gl bi ki Glombiewski et al 2009, M l or ey et al 1999)

• Maladaptive coping strategies like

catastrophizing shown to increase pain 

while cognitive strategies like imagery,

distraction, and positive expectancy sh

reduce pain severity (Gatchel et al 2008)

• Meta‐analysis of anti‐depressant thera

chronic chronic pain shows it reduces reduces pain seve

seve

(Salerno et al 2002)
Social Factors Factors and Chronic Chronic 

• A number of social factors factors affect and a

affected by pain.

• Expectations based on previous medica

tt t rea ment may l d ea to post t ponement 

• Fr stration Frustration o er v la kc of relief or loss of 

work may exacerbate perceived severit

• Relationships, social support, family fu

can greatly influence perceived severit
Biopsychosocial Pain Mod

(Gatchel, et al 2007)

Bio Psyc

h

o 

Central Processes Activ

Livin

Biological CognitiveSomatic Affective---------------------------------------------------------------------

LivinEnviStre

Efferent Feedback 

Afferent Feedback

RelaFam

----------------------------------------------------------------------

Peripheral Processes

Autonomic Endocrine

SociIsola

Autonomic Endocrine

Immune Systems

---------------------------------------------------------------------

CultInsu

Genetic Predispositions Med

Histo
Biopsychosocial model

• Pain has physiological, physiological, psychological, psychological, a

components

• Ni i oc ception re

fers to nerve sti l mu us i 

n 

tissue damage

• Pain refers to subjective perception tha

influenced

b

y: ▫ genetic predisposition,

▫ past experiences,

▫ coping strategies,

▫ psychological status, and

▫ sociocultural background
Biopsychosocial model

• Does not imply that pain is not real

, ra

the complexity of the pain experience m

that there are multiple causes of pain a

o

f i t ti n

tervention.

• Avocates Avocates

a multimodal multimodal pain treatment treatment 

on emotion, cognition, functioning, beh

well as nociceptive nociceptive dysregulation dysregulation.
Current Study

• The current study was designed to und

variations in pain treatment by physicia

practice, and pati t en f t ac ors.

• Opportunity Opportunity to apply latent variable variable te

te

to evaluate whether physicians are util

multimodal approach to treat chronic

nonmalignant pain

• Measuring Measuring characteristics characteristics of physicians physicians 

utilize a multimodal approach may info

future physician training
Methods
Photonovella

• B t e ween‐subj t ec s d i es gn

• Physicians randomly assigned to receiv

patient scenarios that varied by patien

age, facial expression, and ‘red vs. gree

d l ia ogue ( ht ese factors are ad d juste fo

analysis)

• Patient ‘clinic note’ history identical

– Identified patient as veteran

• Four images of patient in a clinical sett

accompani de by di l a ogue
Clinic Note

A 45‐year old male patient with complaint of severe intermittent low ba

months. The patient noted the onset of pain after lifting a heavy box 

pain has been increasing increasing in intensity intensity over the past few months.

He reports that his previous primary care physician prescribed naproxen

reflux symptoms and was subsequently discontinued. He tried physic

this made the pain worse, so he st d oppe going. He has been t ki a ng ex

Tylenol 2 tablets bid with no improvement in the pain.

He gives a history of drinking heavily in the military but reports that he c

d k rin s 1‐2 beers every other week. No history of illicit drug use.

His old medical records are currently not available.

On physical physical exam, he appears appears in moderate moderate pain when moving on and of

Spine is normally aligned. No focal tenderness over the lumbar spine 

paraspinal muscles are mildly tender to palpation bilaterally. Forward 

lumbar spine is limited to 60 degrees by pain. Gait is stable but slow d

Lower extremity strength is 5/5 bilaterally and deep tendon reflexes are 

Straight leg raise is negative bilaterally.

Lumbar spine x‐rays are normal.
Images from Questionna
Dialogue 2. Doctor: When do you have 

1. Doctor: So, what’s going on today? What brings you in?

Patient: Well, it’s pretty muc

the time, I guess.

Patient: This pain in my back again, it’s pretty bad.

4. Doctor: Well, your physidoesn’t show anything abno

from last time. What have 

Patient: Not much really, I 

3. Doctor: Are you able to do 

your usual activities? Go to work, sleep, that sort of thing?

y,

take anything. I tried that Tgave me a couple times, buIt helped right after but it di

, p, g

Patient: Well, I do my job, of course, I do what I have to do.

It helped right after but it di

Maybe I should try somethi

Doctor: Have you tried phy

course, I do what I have to do. I’ve had to miss a few weeks, 

though. It does bother me some 

at night when I’m trying to

Doctor: Have you tried phyPatient: I went to physical 

l f ti b t it t 

at night when I m trying to

sleep, I’ve got to admit.

couple of times, but it actua

pain worse. 
Sample

• Questionnaires Questionnaires sent to national national samp

1000 general internal medicine docto

randomly randomly within region from the AMA

Masterfile

• 953 were delivered to known address• 382 (40%) were returned returned

– 30% female– Average Age = 45; SD=12

– 58% white; 22% Asian/PI; 7% Latino/Hispanic; 5

4% Southwest Southwest Asian/Indian; Asian/Indian; 5% Other race
Outcome Measure

Please indicate how likely you would be to take e

following actions actions with this patient patient...

1. Discuss emotional issues and their possible

contribution to pain?

2. Order further diagnostic testing?

3. Perform functional assessment?4. R f e er for phil ys ca th ? erapy5. Refer for mental health evaluation?6. Refer to a pain clinic or specialist if available7. Further Further question question patient patient about drugs and alc

alc
Outcome Measure

Please indicate how likely you would be to take e

following actions with this patient...

8. Instruct patient to take the Tylenol 3 more re

at a higher dose?

9. Change patient’s treatment to a different sch

opioid?

10. Treat this patient patient with a short‐acting Schedu

Schedu

(such as Dilaudid or Percocet) on an as‐need

11. Treat with a long‐acting Schedule 2 opioid (su

Fentanyl Patch, Oxycontin, methadone, or su

release morph ) ine on a f d ixe around‐the‐cl 

o
Latent Class Analysis

• Multivariate data reduction technique• Indicator variables relate to a latent co

variable variable that is not directly directly observable observable

• Can be thought of as factor analysis ap

categorical indicators that results in acategorical latent variable variable (classificatio

(classificatio

people).
Latent Class Analysis

• Creates categories b d ase on posterior

probability of a certain response to an 

item, given membership in a particular 

• Conditional Independence: If we could

condition on the latent class variable, t

observed indicator variables would be

independent

– In other words, each individual’s latent cla

category is the underlying cause of all obsassoci ti a ons
LCA

different schedule short acting schelong-acting schedTylenol 3 more re

Patient Expression Order further diag

Perform functiona

Patient Expression

Patient Age

Latent Treatment 

Class

(Treatment Style)

Perform functionaRefer for physica

Patient Race

Patient Age

( y)

Patient Dialogue

Refer for mental hRefer to a pain clDiscuss emotionaQuestion about d
LCA Model Selection

• We considered a 2,3,4,5,and 6‐latent class s• The 3‐class model had superior sample‐size 

Bayesian Bayesian Information Information Criterion Criterion and made se

conceptually

• Probability of endorsing each treatment op

g p rou s presented on next slide

– Yellow cells: within‐group probability > overall 

probability,

– Brown cells: within‐group probability < overall – White cells: within‐g p rou p y robability within 5% 

sample probability
LCA Results

Conditional Probability of Treatment Use, Given Class Membership (Column)Treatment

Overall Sample 

Class 1

Multimodal / 

Class 

Psychosoc

Treatment 

n=381 Aggressive

(14%) n=54

Non-opi

(48%) n=

1) Discuss emotional issues 1) Discuss emotional issues 57% 79% 73% 2) Order further diagnostic testing 63% 77% 61% 3) Perform functional assessment 60% 81% 72% 4) Refer for physical therapy 50% 50% 58% 

5) Refer for a mental health evaluation 15% 17% 28% 

6) R f t i li i / i li t 6) Refer to pain clinic/specialist 56% 71% 61% 7) Question about drugs/alcohol 62% 85% 84% 8) Tylenol 3 regularly/at higher dose 17% 29% 8% 9) Change to different schedule 3 opioid 18% 53% 0% 

10) Treat w/ short-acting schedule 2 opioid 14% 41% 0% 

11) T i h l 11) Treat with long-acti h d l 2 i id ing schedule 2 opioid 11% 40% 0% 

on fixed basis

11% 40% 0% 
Latent Classes

• M li d l Multimodal / A i ggressive treatment (MA) ‐ 14%

– Endorsed every option at the overall sample probability o– Medication and psychosocial psychosocial options options– Also question about drug/alcohol use at high rate

• Psychosocial / Non‐opioid (PNO) – 48%

– Endorsed non‐opioid treatments at higher‐than‐average r– Most likely to refer to physical physical therapy therapy or mental health ev

ev

– Almost no endorsement of opioid therapies

• Low action (LA) – 38%

– About as likely as average to utilize opioid therapies– Less lik l e y to utilize psych il osoc al th i erap es
Discussion 1

• Novel approach to capturing different app

treating chronic pain

• Without LCA, it is somewhat more difficult 

vignettes vignettes to capture capture physicians physicians’ approach approach t

treatment since one is restricted to compa

various treatments in isolation isolation

• Latent variable methods allows data to def

“types” of physicians

• Multimodal / Aggressive class (MA) perhap

consistent with treatment that follows the

Biopsychosocial Model of Pain.

– S ll t ma es group (14%)
Moving Physicians into Multim

Treatment Group

• Based on our interpretation that the M

represents represents a pattern pattern of aggressive aggressive mul

mul

treatment, stage 2 of analysis focuses o

d ibi escribing the ch t i ti haracteristics of ph i

ys c 

this group in comparison to physicians 

other two groups in order to better un

these p yh sicians and identify factors th

be modifiable to encourage multimodatreatment of chronic chronic pain.
Regression Methods

• The second stage of analysis consisted 

multivariate multinomial logistic logistic regre

regre

model evaluating differences in physic

characteristics, attitudes, beliefs and p

factors across latent treatment patter
Measures – Physician Tra

• Physician demographic traits

– Sex, race/ethnicity, age

• Jefferson Scale of Physician Empathy (9 

– “I try to imagine myself in my patients’ shoes whe

care”

– Cronbach’s alpha=.86; Item‐scale correlations .47‐

• Medical Authoritarianism Scale (5 items

– “ hT ose who contribute the most to society sh ld ou 

health care”

– Cronbach Cronbach s’ alpha= 82; . Item‐scale correlations correlations .47‐
Measures – Physician Tra

• Revised Revised Pain Attitudes Attitudes Questionnaire Questionnaire 

fortitude subscale (5 items)

–

“ I go on as if nothing had happened when I am 

– Cronbach’s alpha=.81; Item‐scale correlations .5
Measures – Pain Attitude

• Positive attitude toward opioids (3 item

– “Opioids are underused in treatment of chronic 

pain”

– Cronbach’s alpha=.60

• N i egat ve atti d tu e toward treating pain 

– “I do not look forward to managing patients with 

probl ” ems

– Cronbach’s alpha=.59

• “There is always a physical cause for ch

even if doctors doctors cannot diagnose diagnose it.”

– Endorsed (4,5 / 5) by 13%
Measures Measures – Perception Perception of the 

• Patient Trustworthiness

In your opinion, how likely is it that this patient– 1) has pain that is psychosomatic in origin– 2) has substance abuse problems,– 3) can be trusted,– 4) may be exagg g erating his p , ain– 5) may be at risk for addiction,– 6) may be drug seeking,– 7) would be difficult to work with,– 8) is trying to take advantage advantage of you

• Cronbach’s alpha=.88, I‐S correlations .49‐.78
Measures – Perception Perception of the P

P

• Perceived Compliance

In your opinion, how likely is it that this patient– 1) Is likely to follow treatment recommendation

– 2) Is likely to follow‐up for clinic visits

• C b h’ ronbach’s al h 75 p a=.75, Item correl ti a on .60

• Patient Contributing to Pain

In your opinion, how likely is it that this patient

– 1) Needs to take more responsibility for pain m

– 2)may be contributing to his pain by his own be

• Cronbach’s alpha=.74, item correlation .59
Measures – Concerns about O

• How concerned would you be about the f 

o 

issues if you prescribed opioids for this pat

– Drug Use: Tolerance, physical dependence, re

chance other treatments treatments will be utilized utilized, addic

addic

diversion for illegal use, physician’s risk of lega

actions/sanctions.

• Cronbach’s alpha=.85, I‐S correlations .55‐.75

– Effectiveness: lack of effectiveness in treating 

effectiveness in improving function

• Cronbach’s alpha=.87, item correlation .77
Measures – Resources

• I have adequate consultation/referral 

to help patients patients with chronic chronic nonmalig

nonmalig

pain

– 4 5, / 5: 56%

• My knowledge knowledge of pain evaluation evaluation and

treatment is sufficient

– 4,5 / 5: 37%
Measures – Practice Characte

• A i tl pproximately wh t a percentage of you

– Are less than 18 years old?– Are between 18 and 65 years old?

– Are over 65 years old?

– Are non‐white

– Receive Medicaid or other government assistanc

– Have chronic nonmalignant pain

• R i eg on of US from AMA mailing addres
Analysis

• Bivariate models (linear or logistic) ide

factors factors that differed differed across latent class

• Factors associated with class at p<.20 w

entered into a multinomial logistic modpredicting predicting class (3‐level outcome) outcome), and 

eliminated using step‐wise backward

eli i ti limination.
Results of Final Model

Multimodal / Aggressive Group compared to...

...Psychosocial/Non‐opioid

...

Ahi i i Authoritarianism 1 69 . (1 15 . , 3 57) . 1 Patient is not trustworthy .86 (.47, 1.57) 2Concern Concern about drug use .70 ( 40 . , 1 23) . 1 Concern about effectiveness 1.39 (.94, 2.04) 1Positive Positive attitude attitude toward opioids opioids 1 80 . (1 13 . , 2 86) . 1 Chronic pain always has a physical cause 1.84 (.91, 3.75) 3

Adequate consultation/ referral resources .86 ( , .43 1.72) 2

>35% of patients has Medicaid 2.84 (1.43, 5.64) 2

<5% of patients <18 3.05 ( , .98 9.53) 4

Odds Ratios (95% Confidence Intervals)
Discussion

• Compared to the psychosocial/non‐opi

group...

– the MA group was more authoritarian – w

consistent with tendency of authoritarians 

strict rule‐followers and adhere to clinical 

whi hc in the VA (for exampl ) e specify that 

should be used when other therapies are 

effective.

– Not surprisingly, the MA group expressed 

positive attitude toward opioids, which su

education about safety and efficacy of opi

be successf l u in ch i ang ng practice.
Discussion

• Compared to the low action group...

– MA physicians had a more positive attitude 

opioids, and were more likely to believe tha

pain has a phil ys ca cause.

• This belief is widely endorsed by chronic pain patients, an

source of conflict between p yh sicians and patients.

• This finding suggests that changing some physicians’ beli

source of some patients’ pain may improve their treatme

and improve improve patient patient satisfaction satisfaction with the quality quality of the m

m

encounter.

– MA physicians physicians were more likely to report ha

adequate consultation/referral resources, s

physicians use multiple modes of treatment 

resources are available to them.
Discussion

• Compared to the low action group...

– the MA group felt that the patient was less trust– MA ph ii ys c ans were more lik l e y to be concerned 

effectiveness of opioids.

• It is noteworthy that the group most likely to a

opioids has more misgivings about its use and 

pati t en less than other groups

• Perhaps lack of trust and concern about effect

contributed to decision to use opioid alternativ

refer for other care in addition to opioid therap

“rule followers”
Limitations

• Non‐response ( ) 60% typ , ical but makes ext

validity difficult to assess.

• The sample was mostly Non‐VA physicians physicians

difficult to know whether patient’s veteran 

influenced p yh sicians differently than it wo

physician or if their institutional model of differed from VA.

• Do not know if these patterns are valid if t

sy p m toms are new; our patient was alread

opioids.

• Latent class models and other latent mode

have multiple interpretations