A Horse of a Different Color: Outcomes and Health Services

Research

Ethan A. Halm, MD, MPH

Professor of Internal Medicine and Clinical Sciences

Biomedical Research Spectrum

• Bench Research: Basic Science• Translational Research

– Bench to bedside• Clinical Research

– Bedside is the lab• Outcomes & Health Services

Research– Real world care in communities

and populations is the lab

What is Outcomes and Health Services Research?

• Evaluating the impact of health care on health outcomes of patients and populations

• Drugs, devices, procedures, clinical strategies, system interventions

• Focus on care delivered in real-world settings not ideal care in randomized controlled trials

• Assess impact of health care on a broad range of patient-oriented outcomes: mortality, morbidity, symptom burden, functional status, quality of life, satisfaction, utilization, costs

Traditional Medical Research Framework

Causal Factor(bacteria, gene)

Modifying FactorsPatient factorsEnvironmentHealth care

Outcome(disease)

Outcomes & Health Services Research Framework

Health Care(treatment)

Modifying FactorsPatient factorsEnvironment

Outcomes(survival)

Why Evaluate Health Services?• Too hard to figure out the cause of disease• Figuring out the “cause” of disease might not

necessarily cure it (CF, Sickle Cell Anemia)• Assess how well something works in real world

practice, for whom, in which settings• To see if what we do is worth the money• Identify ways to improve health and health care• Identify care that could be harmful: overuse, errors

Two Examples

• Lung cancer

• Stroke prevention surgery

Understanding Racial and Ethnic Differences in Lung Cancer Outcomes

• Lung cancer is common and deadly• 80% are non-small cell lung cancer • Early stage non-small cell lung cancer is

potentially curable with surgery• Blacks have worse lung cancer outcomes

than Whites– 5-year survival: 26% Blacks v. 34% Whites

• Are there also Hispanic v. White differences?– And if so, WHY???

Combining National Datasets to Evaluate Ethnic Differences in Cancer Outcomes

• National cancer registry (SEER)• Registry of newly diagnosed cancer cases• Representative of US population• Data on age, gender, race, ethnicity, cancer

stage, initial cancer treatment• Medicare insurance billing data (Age ≥ 65 yrs)

• More complete info on: other health problems, what care people got over time

• National Death Index: long term survival

National Cancer Registry (SEER)

Methods

Identified all cases of early stage lung cancer in SEER-Medicare database between 1991-2000

16,000 patients treated in real world practice

Compare rates of death due to lung cancer for White v. Hispanics several ways:

Unadjusted rates of death due to lung cancer Adjust for other things that alter life expectancy

(age, gender, other health problems) Adjust for most important factor—potentially

curative surgery

0 2 4 6 8 10

Years after Diagnosis

0

0.2

0.4

0.6

0.8

1.0P

ropo

rtio

n S

urvi

ving

1 3 5 7 9

0.1

0.3

0.5

0.7

0.9

Whites

Hispanics

P= 0.008

Whites Had Better 5 Year Survival Compared to Hispanics: 62% v. 54%

Wisnivesky J, McGinn T, Iannuzzi M, Halm E. AJRCCM 2005.

0

0.2

0.4

0.6

0.8

1.0

0 2 4 6 8 101 3 5 7 9

0.1

0.3

0.5

0.7

0.9

Years after Diagnosis

Pro

port

ion

Sur

vivi

ng

Whites, with surgery

Hispanics, with surgery

P= 0.12

Whites, without surgery

Hispanic , without surgery

P= 0.52

Ethnic Differences in Survival Were Due to Differences in Receiving Curative Surgery

Conclusions• Hispanics with early stage lung cancer had

worse survival as compared with Whites

• Disparities are due lower rates of surgery and higher rates of worse cancer stage

• Patient-level study interviewing patients and physicians to identify barriers to minorities getting the most effective cancer treatment

Carotid Endarterectomy (CEA) Made Ridiculously Simple

• 1 in 4 strokes due to carotid artery disease• CEA seeks to prevent stroke by removing carotid

artery plaque that can embolize, clot, or occlude• Internal carotid artery supplies the retinal, anterior

and middle cerebral artery • Carotid distribution strokes and TIAs manifest as

eye, hand, arm, or leg symptoms or language/speech difficulties

• Intermediate risk vascular procedure lasting 90 minutes (general or local anesthesia)

Who has Carotid Artery Disease?

• Patients with stroke, TIA• Other high risk patients

– Coronary artery disease– Peripheral vascular disease – HTN, DM, high cholesterol, smokers– Elderly patients

Major Clinical Indications

• Symptomatic: more to gain– Stroke – Carotid TIAs

• Asymptomatic: less to gain– Asymptomatic CEA alone– Asymptomatic combined with CABG– Vertebrobasilar TIAs

Early Use of Carotid Endarterectomy

• In the 1980s, carotid endarterectomy (CEA) was controversial

• Data on efficacy was lacking and complication rates were high

• RAND Medicare study of CEA in 1981:– 32% were for inappropriate indications– 75% were for symptomatic carotid stenosis

(Strokes and TIAs)

Clarifying the Benefits and Risks of Carotid Surgery: Clinical Trials• Randomized controlled trials done to see if

surgery is better than medical treatment , and determine which patients benefit

• Over 10,000 patients randomized in North American & Europe (incl. UT Southwestern) at cost of $100 million

• In ideal settings of carefully selected patients & surgeons surgery was better

• Rare investment in trials to evaluate medical or surgical procedures

Outcomes and Use of Carotid Surgery in Real World Practice

• Assess if investment in clinical trials improved rates of appropriateness of surgery– Does better evidence change practice?– Is there a return on investment in clinical trials?

• Measure surgical outcomes in real world practice (risk of death and stroke)– Do patients in real world care do as well?

• Examine the impact of other health problems on risk of surgical complications– Can you produce more personalized info for

individual decision making?

Did Evidence Influence the Use of Carotid Endarterectomy?

0

20

40

60

80

100

120

140

160

1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002

Nu

mb

er (

1000

's)

NASCET: SX

ACAS: ASX

New York Carotid Artery Surgery (NYCAS) Study

• Collaborative grant between NIH and national Medicare agency

• Used Medicare billing records to identify all CEAs in Medicare patients in NY State

• Research nurses reviewed hospital records and collected detailed clinical info about patients, surgery, outcomes within 30 days of CEA

• 9,588 patients, 166 hospitals, 488 surgeons

Defining Appropriateness: RAND Group Judgment Methodology• Multidisciplinary, national expert panel to rate,

discuss, and re-rate appropriateness of 1557 indications for CEA

• Indication is clinical scenario in which CEA might be considered

• Appropriateness rating for each clinical scenario:– Inappropriate: risks > benefits– Uncertain: benefits = risks– Appropriate: benefits > risks

Appropriateness of CEA in NYCAS: 1998-1999

0.87

87%Appropriate

4% Uncertain

9% Inappropriate

Does Evidence Change Practice? Appropriateness of

Surgery Improved

Appropriate Uncertain Inappropriate0

102030405060708090

100

35 32 32

87

49

RAND

NYCAS

Percent

P<.0001

Halm et al. Neurology 2007

Are Outcomes in Real World Practice as Good as the Trials? 30 Day Stroke/Death Rates (%)

Observed Benchmark

CEA Alone

Symptomatic 6.4 < 6

Asymptomatic 3.0 < 3

Carotid + Heart Surgery

Asymptomatic 11.1 ???

Conclusions• Since large investment in RCTs of CEA:• Good news: Triumph of evidence based medicine

– Inappropriateness (32% to 9%)– Complication rates in unselected practice similar to RCTs

• Not so good news:– 1 in 11 still inappropriate– Extrapolates to 12,000 unneeded CEAs/yr in US

• Bad news:– Shift from high benefit symptomatic Pts to lower benefit

asymptomatic Pts (25% to 72%)

Other Health Problems IncreaseRisk of Death/Stroke: Asymptomatic Pts

2.5%2.0%

4.0%

7.1%

0%

1%

2%

3%

4%

5%

6%

7%

8%

Death/stroke*

NoneLowModerateHigh

*p<.001

Comorbidity

Thinking Beyond the RCTs: Asymptomatic v. Symptomatic

3.0%

6.4%

0%

5%

10%

15%

Asymptomatic Symptomatic

Dea

th/S

tro

ke

Halm et al, Stroke, 2008

Risk of Complications after CEA and Neurological Acuity

2.7%4.1%

5.6%

7.9%

13.3%

0%

5%

10%

15%

ASX,No HxCVD

ASX,PastCVD

TIA CVA Acute

Dea

th/S

tro

ke

Halm et al, Stroke, 2008Symptomatic

Multivariable Risk Factors for 30-Day Death or Stroke

Risk Factor Odds Ratio DomainAge >80 yrs 1.3Non-White 1.8 SESASX: Distant Hx TIA/CVA 1.4TIA as indication for CEA 1.8 Neurologic

AcuityCVA as indication for CEA 2.4Acute syndrome 3.6Contralateral stenosis >50% 1.4 Disease severityDeep carotid plaque ulcer 2.1Admitted from ED 1.9Severe disability 2.9CAD 1.5 ComorbidityDM on insulin 1.6

Racial and Ethnic Disparities in Outcomes and Appropriateness of

Carotid Endarterectomy

Background: Disparities in Carotid Endarterectomy (CEA)

• Non-Whites have higher rates of stroke but are less likely to have CEA – NYCAS 5% were Black or Hispanic

• Prior studies showed inconsistent effects of race on outcomes of CEA

• Most focused solely on mortality, used claims data, or limited to Black v. White differences

Study Aims

• Measure differences in indications for CEA and perioperative risk in Blacks and Hispanics compared to Whites

• Compare the risk of death or stroke within 30 days of CEA in Blacks, Hispanics, and Whites

• Understand reasons for disparities in perioperative outcomes by adjusting for other risk factors that influence outcomes

Higher Rates of Symptomatic Indications for CEA in Non-Whites

73%

19%

8%

64%

19% 17%

67%

18%15%

0%10%20%30%40%50%60%70%80%

Asymptomatic TIA Stroke

White Black Hispanic

Halm, Stroke 2009 *p<.001

Higher Rates of Comorbidity and Perioperative Risk in Non-Whites

0%

10%

20%

30%

40%

50%

60%

70%

None/Low Moderate High

White Black Hispanic

Revised Cardiac Risk Index, *p<.0001

Higher Overall Rates of 30 Day Death/Stroke after CEA in Blacks

and Hispanics

6.9%

3.8%

9.5%

0%1%2%3%4%5%6%7%8%9%

10%11%12%13%14%15%

White Black Hispanic *p<.0001

Disparities in Perioperative Complications: Death, Stroke

2.7%2.2%

5.6%4.8%

3.1%

1.1%

3.0%

7.0%6.5%

0%1%2%3%4%5%6%7%8%9%

10%

Death* Any stroke** Non-fatalstroke**

WhiteBlackHispanic

*p<.05, **p<.005

Disparities in 30 Day Death/Stroke: Asymptomatic Patients (N=6503)

5.5%

2.8%

7.6%

0%1%2%3%4%5%6%7%8%9%

10%11%12%13%14%15%

White Black Hispanic *p<.001

3% benchmark

Disparities in 30 Day Death/Stroke: Symptomatic Patients (N=2590)

9.4%

6.3%

13.0%

0%1%2%3%4%5%6%7%8%9%

10%11%12%13%14%15%

White Black Hispanic *p<.05

6% benchmark

Reasons for Disparities in Death or Stroke: Multivariate Analyses

UnadjustedOR

AdjustedModel 1

Adjustment None Indication

White 1.0 1.0

Black 1.89* 1.75*

Hispanic 2.67* 2.54*

*P<.05

Reasons for Disparities in Death or Stroke: Multivariate Analyses

UnadjustedOR

AdjustedModel 1

AdjustedModel 2

Adjustment None Indication Pt factors

White 1.0 1.0 1.0

Black 1.89* 1.75* 1.51†

Hispanic 2.67* 2.54* 2.26*

*P<.05, † P=.13Patient factors: indication, age, sex, comorbidity, % stenosis, ED admission, deep ulcer, Rankin disability score

Reasons for Disparities in Death or Stroke: Multivariate Analyses

UnadjustedOR

AdjustedModel 1

AdjustedModel 2

AdjustedModel 3

Adjustment None Indication Pt factors Pt, MD,Hospital

White 1.0 1.0 1.0 1.0

Black 1.89* 1.75* 1.51† 1.37

Hispanic 2.67* 2.54* 2.26* 1.95*

*P<.05, † P=.13Patient factors: indication, age, sex, comorbidity, % stenosis, ED admission, deep ulcer, disabilityMD/Hospital factors: high and low volume

Inappropriateness by Race/Ethnicity

• Disparities in Inappropriateness: – Hispanics (16%), Black (12%), White (8%)*

• Disparities greatest for asymptomatic patients:– Hispanic (18%), Black (15%), White (8%)*

• Reasons for inappropriateness did not differ in the 3 groups

• More minority Pts presented with high comorbidity

• Among all Pts with high comorbidity, same % inappropriate across race/ethnic groups

*p<.001

Disparities: Worst of All Worlds

• CEA is underused among eligible Non-Whites• Among Non-Whites who have CEA, rates of

inappropriateness is higher (overuse)• Non-Whites have worse outcomes• Reasons for the disparities in outcomes were

multifactorial

Health Services Research Question:

Does Managed Care Affect Quality? Appropriateness, Referral Patterns and Outcomes of Carotid Endarterectomy

Rates of Appropriateness: Fee-For-Service to Managed Care

86.9

4.48.6

88.6

38.4

0102030405060708090

100

Appropriate Uncertain Inappropriate

Percent FFS

MC

P=.78Halm et al. Am J Med Quality 2008

No Difference in 30 Day Outcomes of CEA: FFS v. MC

0123456789

10

Death

Stroke

Non-fata

l stro

ke

Death

/Stro

ke MI

TIA

Co

mp

lica

tio

n R

ate

(%)

FFS

MC

P > .51 for all

Other Areas of CEA Research• MD/Hospital volume-outcome relationships

– How do high volume folks get better outcomes?• Subspecialty Differences• Long term outcomes of NYCAS cohort

– 5 and 10 year stroke and death rates– Subgroup differences in outcomes– RCTs: Age 67, few comorbidities– NYCAS: mean age 75, many comorbidities

• Web-based decision aid to improve decision making in asymptomatic carotid disease

“Oh, if only it were so simple”