Practical ExamplesPractical Examples

Presenter disclosure informationPresenter disclosure information

Bradley G HammillBradley G Hammill

Lesley H CurtisLesley H Curtis

Soko SetoguchiSoko Setoguchi

Practical ExamplesPractical Examples

FINANCIAL DISCLOSURE: FINANCIAL DISCLOSURE:

NoneNone

UNLABELED/UNAPPROVED USES DISCLOSURE:UNLABELED/UNAPPROVED USES DISCLOSURE:

NoneNone

Example: Linked sample comparisonExample: Linked sample comparison

Representativeness of a National Heart Failure Representativeness of a National Heart Failure Quality-of-Care Registry: Comparison of Quality-of-Care Registry: Comparison of OPTIMIZE-HF and Non-OPTIMIZE-HF Medicare OPTIMIZE-HF and Non-OPTIMIZE-HF Medicare PatientsPatients

Lesley H. Curtis, Melissa A. Greiner, Bradley G. Hammill, Lisa Lesley H. Curtis, Melissa A. Greiner, Bradley G. Hammill, Lisa D. DiMartino, Alisa M. Shea, Adrian F. Hernandez and Gregg D. DiMartino, Alisa M. Shea, Adrian F. Hernandez and Gregg C. FonarowC. Fonarow

Circ Cardiovasc Qual Outcomes 2009 2:377-384Circ Cardiovasc Qual Outcomes 2009 2:377-384

Study objective Study objective

Objective:Objective: Compare patient characteristics and Compare patient characteristics and health outcomes of Medicare beneficiaries enrolled health outcomes of Medicare beneficiaries enrolled in OPTIMIZE-HF with those not enrolled who were in OPTIMIZE-HF with those not enrolled who were hospitalized for heart failurehospitalized for heart failure

Also, compare OPTIMIZE-HF hospitals to other Also, compare OPTIMIZE-HF hospitals to other Medicare hospitals.Medicare hospitals.

Analysis issuesAnalysis issues

Decisions to makeDecisions to make Which records to includeWhich records to include Comparisons of interestComparisons of interest Comparison group selectionComparison group selection Characteristics to compareCharacteristics to compare

Which records to includeWhich records to include

Patients potentially represented multiple times in Patients potentially represented multiple times in each database each database

HospitalizationsHospitalizations Take them all or one per patient?Take them all or one per patient? If one per patient, take first or random?If one per patient, take first or random? Does it matter if patient has records in both Does it matter if patient has records in both

groups?groups?

Comparison of interestComparison of interest

Within Medicare: OPTIMIZE-HF v. non-OPTIMIZE-Within Medicare: OPTIMIZE-HF v. non-OPTIMIZE-HFHF Among all sites?Among all sites? Among OPTIMIZE-HF sites? Define Among OPTIMIZE-HF sites? Define

participation period?participation period?

Within OPTIMIZE-HF: Medicare v. non-MedicareWithin OPTIMIZE-HF: Medicare v. non-Medicare Among all sites?Among all sites? Among linked sites?Among linked sites? Age restricted?Age restricted?

Possible comparisonsPossible comparisons

OPTIMIZE-HFOPTIMIZE-HF MedicareMedicare

<65y<65y

Unlinked sitesUnlinked sites

LinkedLinked

OPTIMIZEOPTIMIZEsitessites

Non-OPTIMIZENon-OPTIMIZEsitessites

Comparison group selectionComparison group selection

OPTIMIZE-HF = “New or worsening HF”OPTIMIZE-HF = “New or worsening HF”

Medicare = ?Medicare = ? HF diagnosis in any position on claim?HF diagnosis in any position on claim? HF primary diagnosis only? What if OPTIMIZE-HF primary diagnosis only? What if OPTIMIZE-

HF record is not primary?HF record is not primary?

Characteristics to compareCharacteristics to compare

Within MedicareWithin Medicare Require prior claims eligibility (12m)?Require prior claims eligibility (12m)? Require follow-up period?Require follow-up period? Claims-based comorbidities? Outcomes?Claims-based comorbidities? Outcomes?

Can we use OPTIMIZE-HF variables at all?Can we use OPTIMIZE-HF variables at all?

Study setupStudy setup

Within Medicare comparison (all sites)Within Medicare comparison (all sites)

OPTIMIZE-HF / CMS-linked recordsOPTIMIZE-HF / CMS-linked records Keep first per patientKeep first per patient

Non-OPTIMIZE-HF recordsNon-OPTIMIZE-HF records Eliminate OPTIMIZE-HF ptsEliminate OPTIMIZE-HF pts Take first hospitalization per patient in 2003-4 Take first hospitalization per patient in 2003-4

with primary diagnosis of HFwith primary diagnosis of HF

Compare claims-based comorbidities, mortality, Compare claims-based comorbidities, mortality, and readmissionand readmission

FindingsFindings

Registry hospitals differed from non-registry Registry hospitals differed from non-registry hospitalshospitals Higher volume, more cardiac services available, Higher volume, more cardiac services available,

more likely to be teaching hospitalsmore likely to be teaching hospitals

Patient demographic characteristics and comorbid Patient demographic characteristics and comorbid conditions were similarconditions were similar

FindingsFindings

Observed outcomes, registry v. non-registryObserved outcomes, registry v. non-registry In-hospital mortality was not significantly different In-hospital mortality was not significantly different

(OPT=4.7% v Non-OPT=4.5%)(OPT=4.7% v Non-OPT=4.5%) 1-year mortality was slightly different1-year mortality was slightly different

(OPT=37.2% v Non-OPT=35.7%)(OPT=37.2% v Non-OPT=35.7%) 1-year readmission was slightly different1-year readmission was slightly different

(OPT=64.2% v Non-OPT=65.8%)(OPT=64.2% v Non-OPT=65.8%)

Example: Clinical effectivenessExample: Clinical effectiveness

Clinical Effectiveness of Implantable Clinical Effectiveness of Implantable Cardioverter-Defibrillators Among Medicare Cardioverter-Defibrillators Among Medicare Beneficiaries With Heart FailureBeneficiaries With Heart Failure

Adrian F. Hernandez, Gregg C. Fonarow, Bradley G. Hammill, Adrian F. Hernandez, Gregg C. Fonarow, Bradley G. Hammill, Sana M. Al-Khatib, Clyde W. Yancy, Christopher M. O'Connor, Sana M. Al-Khatib, Clyde W. Yancy, Christopher M. O'Connor, Kevin A. Schulman, Eric D. Peterson and Lesley H. CurtisKevin A. Schulman, Eric D. Peterson and Lesley H. Curtis

Circ Heart Fail 2010 3:7-13Circ Heart Fail 2010 3:7-13

Objective and analysis issuesObjective and analysis issues

Objective:Objective: Evaluate the long-term clinical Evaluate the long-term clinical effectiveness of ICD therapy in older patients with effectiveness of ICD therapy in older patients with heart failureheart failure

Analysis issuesAnalysis issues Treatment and control group inclusion/exclusion Treatment and control group inclusion/exclusion

criteriacriteria Exposure definitionExposure definition

Inclusion/exclusion criteriaInclusion/exclusion criteria

IndicatedIndicated

ContraindicatedContraindicated

Include elective admits?Include elective admits?

Age limit?Age limit?

Exposure definitionExposure definition

Discharged with an ICDDischarged with an ICD New only?New only? Present at admission?Present at admission?

ICD planned after dischargeICD planned after discharge

Study setupStudy setup

Exclude contraindicatedExclude contraindicated

Require EF Require EF 35%, exclude new onset HF 35%, exclude new onset HF

Exclude discharge to SNF, etc.Exclude discharge to SNF, etc.

Exclude elective admits for lack of untreated Exclude elective admits for lack of untreated comparison groupcomparison group

Exclude very old for lack of treated comparison Exclude very old for lack of treated comparison groupgroup

New user design, exclude present at admissionNew user design, exclude present at admission

Do not treat planned ICD as treatedDo not treat planned ICD as treated

FindingsFindings

Mortality was significantly lower among patients Mortality was significantly lower among patients who received an ICD compared with those who did who received an ICD compared with those who did not not

(38.1% v 52.3% at 3 years)(38.1% v 52.3% at 3 years)

Adjusted hazard ratio of mortality over 3 years for Adjusted hazard ratio of mortality over 3 years for patients receiving an ICD waspatients receiving an ICD was

0.71 (95% CI, 0.56 to 0.91)0.71 (95% CI, 0.56 to 0.91)

Example: Clinical effectivenessExample: Clinical effectiveness

Improvements in long-term mortality after Improvements in long-term mortality after myocardial infarction and increased use of myocardial infarction and increased use of cardiovascular drugs after discharge: a 10-year cardiovascular drugs after discharge: a 10-year trend analysistrend analysis

Soko Setoguchi, Robert J Glynn, Jerry Avorn, Murray A Soko Setoguchi, Robert J Glynn, Jerry Avorn, Murray A Mittleman, Raisa Levin, Wolfgang C WinkelmayerMittleman, Raisa Levin, Wolfgang C Winkelmayer

J Am Coll Cariolol. 2008 51:1255-7J Am Coll Cariolol. 2008 51:1255-7

Objective and analysis issuesObjective and analysis issues

Objective:Objective: Assess the relationship between Assess the relationship between increasing use of cardiovascular medications and increasing use of cardiovascular medications and trends in long-term prognosis after myocardial trends in long-term prognosis after myocardial infarction (MI) in the elderly infarction (MI) in the elderly

Design/analytic issuesDesign/analytic issues Defining ‘CV drug use’Defining ‘CV drug use’ Start of follow-upStart of follow-up

Avoid immortal person time biasAvoid immortal person time bias

Potential explanations of improving survival over timePotential explanations of improving survival over time

Potential Mediators of Changing Survival after MI

Trend in Post-discharge Management•Initiation and maintenance of drug therapy (aspirin*, BB, ACEI/ARB and statins)

•Life-style modification*

Effect on Survival

Calendar Year

Trend in Characteristic of MI Patients•Age, gender, and race•Diagnosis of MI* (Use and level of troponin for diagnosis)•Characteristics for MI*(location, infarct size, affected vessels)•Complication of MI•Comorbidity

Trend in In-hospital Management•Thrombolytic therapy•Antiplatelet agents and other drugs*•Coronary angioplasty•Surgery

Potential Mediators of Changing Survival after MI

Trend in Post-discharge Management•Initiation and maintenance of drug therapy (aspirin*, BB, ACEI/ARB and statins)

•Life-style modification*

Effect on Survival

Calendar Year

Trend in Characteristic of MI Patients•Age, gender, and race•Diagnosis of MI* (Use and level of troponin for diagnosis)•Characteristics for MI*(location, infarct size, affected vessels)•Complication of MI•Comorbidity

Trend in In-hospital Management•Thrombolytic therapy•Antiplatelet agents and other drugs*•Coronary angioplasty•Surgery

Defining CV drug useDefining CV drug use

Started recommend meds during hospitalizationStarted recommend meds during hospitalization

Filled prescription after dischargeFilled prescription after discharge What timing?What timing?

Continued to take the medications for a certain Continued to take the medications for a certain periodperiod What if some patients took it every day vs. What if some patients took it every day vs.

others skipped them once in a while? others skipped them once in a while?

Defining CV drug useDefining CV drug use

Dictate hypothesis clearly would helpDictate hypothesis clearly would help Increasing initiation of recommended CV meds Increasing initiation of recommended CV meds

during acute hospitalizationduring acute hospitalization improved prognosis improved prognosis in elderly patients after MIin elderly patients after MI

Increasing initiation of recommended CV meds Increasing initiation of recommended CV meds in outpatient settingin outpatient setting …… ……

Increasing ‘continued use’ of recommended CV Increasing ‘continued use’ of recommended CV meds in outpatient settingmeds in outpatient setting …….. ……..

Defining CV drug useDefining CV drug use

Things to consider in addition to choosing sound Things to consider in addition to choosing sound hypothesishypothesis Availability of informationAvailability of information

No inpatient drug use availableNo inpatient drug use availableAspirin use is not fully capturedAspirin use is not fully captured

Sample sizeSample sizeLose more patients as you assess Lose more patients as you assess

drug use over longer period drug use over longer period

When to start the follow-up for an outcome?When to start the follow-up for an outcome?

Immortal person time biasImmortal person time bias Increasing initiation of recommended CV meds Increasing initiation of recommended CV meds

during acute hospitalizationduring acute hospitalization improved prognosis improved prognosis in elderly patients after MIin elderly patients after MI

Immortal person-time biasImmortal person-time bias

Comparing survival of responders vs. non-Comparing survival of responders vs. non-responders to a chemotherapyresponders to a chemotherapy

Usual methodUsual method Categorize patients into responders vs. non-Categorize patients into responders vs. non-

responders based on tumor responseresponders based on tumor response Compare survival from the start of the treatment Compare survival from the start of the treatment Length of survival affect the responseLength of survival affect the response

Anderson J Clin Onc 1983

Immortal person-time bias exampleImmortal person-time bias example

11stst response evaluated at 2 months after response evaluated at 2 months after chemotherapychemotherapy

All patients who died before the 1All patients who died before the 1stst evaluation evaluation categorized as ‘non-responders’ categorized as ‘non-responders’

Survival was from the time of chemo to 1 year.Survival was from the time of chemo to 1 year. 2 month ‘guarantee’ time for all responders2 month ‘guarantee’ time for all responders

Anderson J Clin Onc 1983

Immortal person-time biasImmortal person-time bias

Suissa PDS 2007

Landmark method (analysis)Landmark method (analysis)

Landmark Method (Analysis)Landmark Method (Analysis) ‘‘Select some fixed time after initiation of therapy Select some fixed time after initiation of therapy

as a landmark for conducting analysis’ as a landmark for conducting analysis’ = starting follow-up after completion of = starting follow-up after completion of

exposure assessmentexposure assessment LimitationsLimitations

Results may differ depending on which Results may differ depending on which landmark is chosenlandmark is chosenLoss of power Loss of power Cannot observe the entire hazard Cannot observe the entire hazard

functionfunction

Anderson J Clin Onc 1983

Study setupStudy setup

All patients admitted to a hospital with MI (1995 -2004) using All patients admitted to a hospital with MI (1995 -2004) using algorithm previously shown to have high accuracy (PPV of algorithm previously shown to have high accuracy (PPV of 94%)94%)

All study patients survived at least 30 days after discharge All study patients survived at least 30 days after discharge from the index MI hospitalizationfrom the index MI hospitalization

Long-term survival was observed from the 31st day after Long-term survival was observed from the 31st day after discharge to the date of deathdischarge to the date of death

Assessed Assessed Trend in mortalityTrend in mortality Trend in CV drug use (filled prescription within 30 days Trend in CV drug use (filled prescription within 30 days

after discharge)after discharge) Trend in PCI during MI hospitalizationTrend in PCI during MI hospitalization

Assessed contribution of increasing CV drug use by Assessed contribution of increasing CV drug use by sequentially including terms for the multivariate modelsequentially including terms for the multivariate model

Time trends of treatment for MITime trends of treatment for MI

Of 21,484 MI patients, 12,142 died Of 21,484 MI patients, 12,142 died during an average follow-up of during an average follow-up of 3.5 years. 3.5 years.

A trend towards increasing age and A trend towards increasing age and greater prevalence of greater prevalence of comorbidities such as comorbidities such as hypertension, peripheral vascular hypertension, peripheral vascular diseases, cerebrovascular diseases, cerebrovascular diseases, diabetes, and chronic diseases, diabetes, and chronic kidney disease was observed kidney disease was observed

The use of percutaneous coronary The use of percutaneous coronary interventions increased over time, interventions increased over time, whereas use of thrombolytic whereas use of thrombolytic therapy decreased (Top)therapy decreased (Top)

Use of all study drugs also increased Use of all study drugs also increased over time. (Bottom)over time. (Bottom)

0

5

10

15

20

25

30

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

Calendar Year

% P

atei

tns

with

Pro

cedr

ues

PCI

Surgery

Thrombolysis

0

10

20

30

40

50

60

70

80

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

Calendar Year

% P

atie

nts

wtih

Dru

gs

Statin

Beta blockers

ACEI/ARB

Non-aspirinantiplatelet

Potential explanations of improving survival over timePotential explanations of improving survival over time

Potential Mediators of Changing Survival after MI

Trend in Post-discharge Management•Initiation and maintenance of drug therapy (aspirin*, BB, ACEI/ARB and statins)

•Life-style modification*

Effect on Survival

Calendar Year

Trend in Characteristic of MI Patients•Age, gender, and race•Diagnosis of MI* (Use and level of troponin for diagnosis)•Characteristics for MI*(location, infarct size, affected vessels)•Complication of MI•Comorbidity

Trend in In-hospital Management•Thrombolytic therapy•Antiplatelet agents and other drugs*•Coronary angioplasty•Surgery

Potential Mediators of Changing Survival after MI

Trend in Post-discharge Management•Initiation and maintenance of drug therapy (aspirin*, BB, ACEI/ARB and statins)

•Life-style modification*

Effect on Survival

Calendar Year

Trend in Characteristic of MI Patients•Age, gender, and race•Diagnosis of MI* (Use and level of troponin for diagnosis)•Characteristics for MI*(location, infarct size, affected vessels)•Complication of MI•Comorbidity

Trend in In-hospital Management•Thrombolytic therapy•Antiplatelet agents and other drugs*•Coronary angioplasty•Surgery

0.4

0.6

0.8

1.0

1.2

1995 1996 1997 1998 1999 2000 2001 2002 2003 2004

Calendar Year

Haz

ar R

atio

for

Cal

enda

r Y

ear

Not Adjusted for CV drug use/coronary intervention

Improving trend of long-term prognosis for MI

Improving trend of long-term prognosis for MI disappeared Improving trend of long-term prognosis for MI disappeared after adjusting for the recommended cardiovascular drug after adjusting for the recommended cardiovascular drug useuse

0.4

0.6

0.8

1.0

1.2

1995 1996 1997 1998 1999 2000 2001 2002 2003 2004

Calendar Year

Haz

ar R

atio

for

Cal

enda

r Y

ear

Not Adjusted for CV drug use/coronary intervention

Adjusted for CV drug use

Use of CV procedures did not eliminate the calendar year effect completely

0.4

0.6

0.8

1.0

1.2

1995 1996 1997 1998 1999 2000 2001 2002 2003 2004

Calendar Year

Haz

ar R

atio

for

Cal

enda

r Y

ear

Not Adjusted for CV drug use/coronary interventionAdjusted for CV drug useAdjusted for CV procedure use

Lessons learnedLessons learned

The criteria for diagnosing MI have changed over the The criteria for diagnosing MI have changed over the decade studieddecade studied likely resulting in an increasing fraction of patients likely resulting in an increasing fraction of patients

having non-ST elevation MI (NSTEMI). having non-ST elevation MI (NSTEMI). Unlikely to explain the findings completely.Unlikely to explain the findings completely.

No information on aspirin use and life style modification. No information on aspirin use and life style modification. Studies suggest that use of aspirin is relatively Studies suggest that use of aspirin is relatively

stable after 1995 stable after 1995 unclear whether lifestyle has changed over time in unclear whether lifestyle has changed over time in

the elderly populationthe elderly population

Further investigation is necessary to elucidate the Further investigation is necessary to elucidate the relative and individual contributions of these factors.relative and individual contributions of these factors.