Real World Effectiveness of Implantable Cardioverter Defibrillators in Medicare Patients Soko...

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Real World Effectiveness of Implantable Cardioverter

Defibrillators in Medicare Patients

Soko Setoguchi, MD, DrPH

Duke Clinical Research Institute, Durham, NC

Project Contract Site

Brigham and Women Hospital, Boston, MA

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Disclosure• Conflicts of interest: None• Sources of funding: Contract No.HHSA290-2005-0016-I

–TO8 from the AHRQ as part of the Developing Evidence to Inform Decisions about Effectiveness (DEcIDE) program and Contract 500-2010-00001I TO6 and Contract 500-2010-00001I TO2 from the CMS.

• Dr. Setoguchi is supported by a mid-career development award grant K02-HS017731 from AHRQ.

• The presenter is responsible for the content. Statements in the presentation should not be construed as endorsement by the AHRQ, CMS or the US Department of Health and Human Services.

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Ongoing DEcIDE Task Order

• Title: Analysis of Data Associated with CMS Coverage with Evidence Development Initiatives– Real World Effectiveness of Carotid Artery Stenting

and Implantable Cardioverter Defibrillators in Medicare Patients

• Fund: interagency contract between AHRQ and CMS

• Contract site: Brigham and Women’s Hospital DEcIDE Center

3

Outline

• Introduction and current status of our CMS ICD project

• Presentation of results from a recently completed ICD study

Implantable Cardioverter Defibrillators (ICDs)

5

ICDs in Real World• Real world patients receiving ICDs

– Median age: 74 yrs– Non-cardiac comorbidities are common

• 36% Diabetes• 22% Chronic lung disease

– Insurance Type• 77% CMS

» American College of Cardiology National Cardiovascular Data Registry (ACC NCDR) Report

• Benefit of ICD is not established in: – elderly patients – those with comorbidities– real world practice setting

6

ICD Study: Aims• Aim 1: To demonstrate differences in the incidence rate of

death and cardiovascular hospitalizations between trial populations and Medicare patients undergoing ICD implantation.

• Aim 2: To explore the incidence of death and cardiovascular hospitalizations in subgroups of patients undergoing ICD implantation by gender, age category, and comorbidities.

• Aim 3: To identify subgroups of patients undergoing ICD implantation for whom 1) ICDs are not effective (expected survival < 18 months) and 2) ICDs are not cost-effective (expected survival < 5 years).

• Aim 4: To estimate the incidence of various potential short and long-term adverse events following ICD implantation.

• Aim 5: a) To directly compare ICD vs. medical management and b) to assess the impact of unmeasured confounding in a well-designed comparative effectiveness study.7

Key Features of the DEcIDE CMS ICD Study

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Bringing In Multiple Players

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Core Investigator TeamBWH DEcIDE Center Core Team• Soko Setoguchi Iwata, MD DrPH (PI, BWH/Duke) • John Seeger, PharmD, DrPH (Site PI)• Natasha (Chih-Ying ) Chen, PhD (Research Fellow)• Lauren Williams, BA (Research Assistant)• Helen Mogun, MS and Jun Liu, MD MPH (Programmers)Clinical Experts• Lynne Warner Stevenson, MD (Co-Investigator)• Garrick Stewart, MD, MPH (Co-Investigator)Method Experts• Sebastian Schneeweiss, MD ScD (BWH DEcIDE PI)• Robert Glynn, PhD ScD (Co-investigator)

*Deceased

Contracting/Supporting Groups/Individuals• Outcome Sciences Inc.

– Providing the national clinical registries for HF and myocardial infarction (MI)

– Nancy Dreyer, PhD• ACC NCDR

– Supplementing CMS ICD Registry with data from ACC NCDR ICD Registry

• Center for Outcomes Research and Evaluation (CORE), Yale-New Haven Hospital– Bridging BWH DEcIDE Center and ACC NCDR– Collaborating on the ICD complication aim

• Brown University – Melissa Clark, PhD, Brown University for the supplemental

survey study• Univ. of British Columbia

– Winson Cheung, MD MSc for the supplemental survey study

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TEP members• Jeptha Curtis, MD (Yale School of Medicine & Yale-New

Haven Hospital, New Haven, CT)• Sherri Dodd, MS (Medtronic Inc, Minneapolis, MN)• Kenneth Ellenbogen, MD (Virginia Commonwealth

University Pauley Heart Center, Richmond, VA)• Marcel E. Salive, MD, MPH (National Institute on Aging

at National Institutes of Health, Bethesda, MD)• Lynett Voshage Stahl (Boston Scientific Corporation,

Arden Hills, MN)

Putting Multiple Data Sources Together

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Brigham DEcIDE Center

*HF/MI Registry: Clinical Registry from Outcome DEcIDE Center for heart failure and myocardial infarction

5) CMS sends Medicare files (100% Denominator & MedPAR) to BWH DEcIDE Center

3) CMS ICD registry with identifiers

11) Creation of Research Database using Medicare files and linkage information

1) Dataset of entire study cohort (65+) and linkage information*

HF/MI registry

Medicare Files

ResearchDatabase

HF/MI registry

ACC- NCDR registry

2) A portion of the NCDR ICD registry including identifiers, reason for admission, prior heart failure hospitalization, QRS duration, Creatinine, B-type natriuretic peptide, and systolic blood pressure

6) BWH DEcIDE Center receives Medicare Files (STAGE 1)

CMS ICD registry

Medicare Files

Medicare Files

Medicare Files

8) CMS receives partial linkage information (STAGE 2)

10) BWH DEcIDE Center receives Medicare Files (STAGE 2)

9) Extract Medicare Part A, B, and D files using partial linkage information

7) Partial linkage information: SSN

Linkage Information(STAGE 2)

Linkage Information(STAGE 2)

CMS ICD registry

ACC- NCDR registry

4) ACC-NCDR variables added to CMS ICD registry

Ou

tcom

e ID#

CM

S ID

#

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Multiple Studies are Underway to Inform…..

• Long-term outcomes (benefit and complications) after ICD implantation

• Who benefit or don’t benefit from ICDs• Methodological challenges and potential

solutions in assessing effectiveness of ICDs using large databases

• Clinical effectiveness of ICDs and magnitude of potential bias in observational studies

……..in Medicare patients

Survival after ICD Implantation in Medicare Patients with Heavy

Burden of Heart Failure

Natasha Chen, Lynne Warner Stevenson, John D Seeger, Lauren Williams, Jessica J

Jalbert, Andrew Rothman, Garrick C Stewart, Soko Setoguchi

Background and Purposes• Little is known about long-term survival

after primary ICD implantation in Medicare patients–especially in those with heavy burden of

HF and other comorbidities• To describe survival following primary ICD

implantation and assess the impact of the burden of HF on survival

Data Sources

• Centers for Medicare & Medicaid Services ICD registry

• Medicare Provider Analysis and Review (MedPAR) – Years 2005 - 2008– Linked by a previously described method

using multiple non-unique identifiers• Date of birth, date of admission, gender, hospital

ID

Index time1st ICD implantation

CensoringICD removalLoss of eligibility12/31/2008

Recipients in CMS-ICD registry+

MedPAR files(Year 2005-2008)

Recipients met indications for primary ICD-EF ≤ 35%-No cardiac arrest/sustained VT

Recipients of prophylactic ICD- ≥ 1yr eligibility- Age ≥ 66 yrs

OutcomesAll-cause mortality

Study Design

HF Burden and Analysis• Chronic burden of HF

– Number of HF hospitalizations in the previous year

• Acute burden of HF– Days from admission to implant during

HF/ICD hospitalization• Kaplan-Meier survival estimates for crude

mortality• Cox proportional hazard regression

models for adjusted hazard ratios (HRs).

Characteristics for Medicare ICD patients (N=66,974)

Median Age (IQR)Male White

75 yrs (71-80)73%88%

Median EF (IQR) 25% (20-30)

HF Duration New HF 0-3 months 3-9 months >9 months

12%14%13%61%

NYHA class I II III IV

6%31%58%5%

Ischemic HF 79%

Outcomes in Overall Medicare Primary ICD Patients (N=66,974)

Death (N) 11,876In-hospital death (N) 327In-hospital death risk (95% CI) 0.49% (0.45-0.55)Average follow-up (range) 1.4 years (0 -4)Mortality risk (95% CI) 1-year 12% (12-13) 2-year 22% (22-23) 3-year 31% (30-32)

Mortality after ICD Implant (N=66,974)

3 Year MortalityMedicare ICD Patients 31% SCD HeFT 16%MADIT II 22%

Characteristics by Number of Hospitalizations

# of Prior HF Hosp0

N=52,9631

N=10,2472

N=2,501≥3

N=1,263

N (% total population) 79% 15% 4% 1%

Age (IQR)Male White

75 (71-80)75%89%

76 (71-80)67%85%

76 (71-81)63%79%

76 (71-80)60%74%

EF(%) (IQR) ≤20%

25(20-30)31%

25(20-30)43%

25(20-30)43%

23(20-30)48%

HF Duration >9 months 59% 66% 69% 74%

NYHA class I II III IV

7%33%56%4%

2%23%67%7%

2%19%69%10%

1%15%70%16%

Mortality by # of HF Hospitalizations in the Past Year

Risk of Mortality in Patients with >=1 HF Hospitalizations During 1 Year Prior to Implant vs.

Those with No Prior Hospitalizations in the Past Year

# of prior HF hosp in the past year

0 hosp

N=52,963

1 hosp

N=10,247

2 hosp

N=2,501

≥3 hosp

N=1,263

Mortality 1-yr mortality 2-yr mortality 3-yr mortality

10% (10-11)19%(19-20)27%(27-28)

17%(16-18)30%(29-31)40%(38-43)

24%(23-26)37%(35-40)52%(46-57)

33%(30-36)51%(48-55)63%(57-68)

Hazard ratio(HR) Unadjusted Age,sex,race

adjusted

--

1.7 (1.6-1.7)1.6 (1.6-1.7)

2.2 (2.1-2.4)2.2 (2.0-2.3)

3.4 (3.2-3.8)3.3 (3.0-3.6)

Characteristics by Number of Days from Admission to Implantation

# of days from adm to implant

0 daysN=39,576

1 dayN=5,636

2-7 daysN=16,959

8-14 daysN=4,803

% total population 59% 8% 25% 7%

Age, median (IQR) Age ≥ 80y Male White

75 (70-80)25%74%91%

76(71-80)28%76%89%

76 (71-81)30%71%84%

76 (71-81)30%71%81%

EF ≤ 20% 30% 36% 40% 45%

HF Duration New HF 0-3 months >3 months

13%10%77%

13%14%73%

11%20%69%

8%26%66%

NYHA class I II III IV

6%34%57%3%

6%30%59%5%

5%26%60%9%

3%22%62%13%

Mortality by # Days from Admission to Procedure

Risk of Mortality in Patients with >=1 Days Prior to Implant vs. Those with Implant on Admission Day

# days from admission to procedure

0 days

N=39,576

1 day

N=5,636

2-7 days

N=16,959

8-14 days

N=4,803

Mortality 1-yr mortality 2-yr mortality 3-yr mortality

8%(8-8)16%(16-17)25%(24-25)

12% (11-13)22% (21-23)32% (29-35)

18% (18-19)30% (29-31)41% (39-42)

29% (28-31)43% (41-44)53% (50-57)

Hazard ratio(HR) Unadjusted Age,sex,race

adjusted

--

1.4 (1.3-1.5)1.4 (1.3-1.5)

2.1 (2.0-2.2)2.0 (1.9-2.1)

3.4 (3.2-3.6)3.2 (3.1-3.4)

Conclusion• In 3 years, nearly one third of patients

receiving a primary ICD implantation were died in this Medicare population

• 3-year Mortality increased to 1/2 among patients with at least 2 HF hospitalizations or 7 days between admission and implantation

Implications

• Indications and potential benefits should be carefully weighed when considering primary ICD implantation for Medicare patients with greater HF burden

Acknowledgement

Agency for Healthcare Research and Quality • Elise Berliner, PhDCenters for Medicare and Medicaid• Rosemarie Hakim, PhD

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Excluded 4,032 with missing EF 4,498 with EF > 35% 24,227 with repeated ICD 27,810 for secondary prevention 14,739 with prior cardiac arrest 17,158 with history of sustained VT 5,725 with < 1 yr continuous eligibility 5,248 with age < 66 years old 2,045 with no device type information

66,974 patients eligible

190,778 records with complete linkage variables

Excluded26,106 (12%) records with incomplete information on linkage variables: admission dates, provider ID, date of birth, and gender

122,562 ICD records linked to MedPAR records

216,884 ICD implantations in those aged >= 65 yrs between 2005 and 2008

Implantable Cardioverter Defibrillator (ICD)

• Ventricular arrhythmia is common among heart failure (HF) patients– 50-80% non-sustained

ventricular tachycardia (VT)– 5% sustained VT or ventricular

fibrillation (VF) (fatal)• Presence of HF increases

the sudden death rate 5.5-fold in both men and women (Framingham heart study)

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Implantable Cardioverter Defibrillator (ICD)

• ICDs have shown to be beneficial as a primary prevention of sudden cardiac death (SCD) among HF patients with systolic dysfunction in trials (primary prevention of SCD)

• National Coverage Decision (NCD) in Jan 2005– CMS expanded the

coverage for ICD implantation for primary prevention

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Identify from registry Identify from CMS files

Age at index date (66-70, 71-75, 76-80, 81-85, 85+ yrs)Gender HF duration (0/0-3/3-9 mo)Ejection fraction (<30, 30-35%)NYHA class (I, II, III, IV)QRS interval (<120, ≥120 msec)Device type (Single/dual chamber)Estimated GFR (<15, 15-29, 30-59, 60-89, >90 mL/min/1.73m2) BNP(<130, 131-230, 231-480, >480 pg/mL)SBP (<80, 80-100, 101-130, 131-150, >150mmHg)Sodium (<135, 135-145, >145 mEq/L)Elective/non-elective procedure

Race (Whites/Blacks/Hispanics/others)Diabetes (Y/N)Chronic kidney disease (Y/N)Atrial fibrillation (Y/N)Beta-blocker use* (Y/N)ACEI/ARB use* (Y/N)Aldosterone receptor antagonists use* (Y/N)

Identify from registry and CMS files

Prior HF hospitalizations (0, 1, 2, 3, 4, ≥5)HF cause (Ischemic/non-ischemic)

Important Covariates

Outcome Definitions

Outcomes Definitions

Death Death identified from CMS Vital status file

All-causeHospitalization

1st hospitalization (identified from Part A file) after the discharge date of ICD implantation, not counting visit for ICD evaluation

HF 1st hospitalization with ICD-9-CM code (Dx) 428.xx as the primary discharge diagnosis

MI 1st hospitalization with Dx 410.xx as the primary discharge diagnosis and with length of stay > 3 days (unless patients died) and < 180 days.

Cardiac events 1st hospitalization with the following codes as the primary discharge diagnosis: 428.xx, 410.xx413.x (Angina pectoris) 420.0, 420.9x (Acute pericarditis) 421.x (Acute and sub-acute endocarditis) 423.x (Other disease of pericardium) 424.2 (Tricuspid valve disorders specified as nonrhumatic 426.x (Conduction disorder) 427.xx(Cardiac dysrythmia)

Characteristics by Number of Hospitalization.

0 1 2 ≥3

QRS ≥ 120 msec 32,949(62) 6,817(67) 1,651(66) 852(67)

Ischemic cause HF 42,168(80) 7,995(78) 2,020(81) 1,049(83)

Unsustained VT 12,382(23) 2,273(22) 590(24) 309(24)

Mean prior Hospitalization for any cause

≥ 5 0.6(1)506(1)

2(1.3)498(5)

3.2(1.4)402(16)

5.5(2.6)983(41)

Mean LOS of implantationAdmission to implantation

3.9(5.2)1.9(3.6)

4.2(5.5)2(3.5)

5(6)2.5(4.4)

5.9(6.2)3.0(4.2)

Mean Charlson Score not counting cardiac conditions

0.6(1.2) 1.8(1.6) 2.5(1.7) 3.1(1.8)

0 days 1 day 2-7 days 8-14 days

QRS ≥120 msec 25,363(64) 3,752(67) 10,365(61) 2,789(58)

Ischemic cause HF 31,111(79) 4,452(79) 13,662(81) 4,007(83)

Unsustained VT 6,384(16) 1,436(26) 5,578(33) 2,156(45)

Mean prior Hospitalization for any cause ≥ 5

0.9(1.3)919(2)

1.1(1.5)202(4)

1.1(1.6)738(4)

1.4(1.8)267(6)

Mean LOS of implantationImplantation to discharge

1.4(1.7)1.4(1.7)

3.1(2.7)2.1(2.7)

6.9(3.7)2.8(3.2)

16.4(5.7)4.4(5)

Mean Charlson Score not counting cardiac conditions

0.8(1.3) 1(1.4) 1.1(1.6) 1.3(1.7)