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Maximizing Comparative Effectiveness Research The DECIDE CV Consortia

Slide presentation from the AHRQ 2009 conference.


On September 14, 2009, Eric Peterson made this presentation at the 2009 Annual Conference. Select to access the PowerPoint® presentation (1.3 MB).

Slide 1

Maximizing Comparative Effectiveness Research The DECIDE CV Consortia

Eric D. Peterson, MD, MPH
Professor of Medicine
Vice Chair for Quality, Duke DOM
Associate Director, Duke Clinical Research Institute (DCRI)

David Magid, MD, MPH
Director of Research, Colorado Permanente Medical Group
Associate Professor, University of Colorado

Slide 2

Comparative Effectiveness Research

"There is a wealth of data available from large databases that enable us to research important clinical questions,"
"Robust methodology exists for comparing different therapies through observational database analysis."

Wilensky G Health Affairs Nov 2006:w572-w588

Slide 3

Elements Stimulating Comparative Effectiveness Research

An graph of the "Total Federal Spending for Medicare and Medicaid Under DIfferent Assumptions About Excell Cost Growrh, 1966 to 2050" is shown.

As part of ARRA: $1.1 billion set aside for comparative effectiveness research (CER)

Slide 4

IOM CER Priorities 2009

  • Health Care Delivery Systems
  • Racial and Ethical Disparities
  • Functional Limitations and Disabilities
  • Cardiovascular and Perioheral Vascular Disease

Slide 5

Leading Causes of Death in US

An image of a graph showing the leading causes of death in the US is shown.

  1. Heart disease
  2. Cancer
  3. Cerebrovascular disease
  4. Chronic lower respiratory disease
  5. Unintentional injuries

Slide 6

Lack of Evidence in Guidelines: Recommendation Based on RCT Data

  • AF: 11.7%
  • Heart failure: 26.4%
  • PAD: 15.3%
  • STEMI: 13.5%
  • Perioperative: 12.0%
  • Secondary prevention: 22.9%
  • Stable angina: 6.4%
  • SV arrhythmias: 6.1%
  • UA/NSTEMI: 23.6%
  • Valvular disease: 0.3%
  • VA/SCD: 9.7%
  • PCI: 11.0%
  • CABG: 19.0%
  • Pacemaker: 3.5%
  • Radionuclide imaging: 4.8%
Tricoci P et al JAMA 2009

Slide 7

Cycle of Evidence Development and Dissemination

An image of the Cycle of Evidence development and dissemination is shown. The image contains:

  • Concept
  • Clinical Evidence
  • Guidelines
  • Performance Indicators
  • Measurement+ Feedback
  • QI Initiatives
  • Outcomes
  • Large CV Registries

Adapted from Califf RM, Peterson ED
et al. JACC 2002;40:1895-901

Slide 8

Role of Clinical Registries for Evidence Development:

E. Stead: Using the Past to Guide the Future

"Chronic diseases can be studied, but not by the methods of the past. If one wishes to create useful data . computer technology must be exploited."—Eugene Stead, MD

  • Led to the concept of "computerized textbook of medicine"
  • Formed foundation of the Duke Databank for CV Diseases
  • Spurred a generation of clinical and quantitative researchers

Slide 9

Types of Multicenter Registries

  • Claims: eg. CMS
    • Advantages: Comprehensive, longitudinal, cover in + out-pt services
    • Disadvantages: Limited clinical data, age 65+
  • Managed Care/EHR: eg. Kaiser/VA
    • Advantages: longitudinal, meds, labs, other clinical info
    • Disadvantages: select pts, miss out of coverage care
  • Clinical Registries: eg. ACC/STS/AHA
    • Advantages: targeted in-depth clinical data
    • Disadvantages: selective participation, traditionally in-patient focus

Slide 10

CV Provider Led Clinical Registries

  • Society of Thoracic Surgery: 900+ centers
    • Coronary artery bypass surgery
    • Valve surgery
    • Congenital heart surgery
    • Thoracic surgery
  • National Cardiovascular Data Registry: 1600+ Hospitals
    • Cath/Percutaneous coronary intervention
    • Implantable cardiac defibrillators (ICD)
    • Acute coronary syndromes (ACS)
    • Carotid stenting
    • Ambulatory CV disease (launching)
  • AHA-Get With The Guideline Program: 1500+ hospitals
    • Coronary artery disease (CAD)
    • Heart failure
    • Stroke
    • Ambulatory module (launching)

Slide 11

These CV Clinical Registries are.

  • Large and growing more representative
    • Of US patients, providers, settings
  • Detailed...with rich clinical data
    • presenting features, treatments, acute outcomes
  • Use standardized data elements
    • With and among registries
  • Are high quality
    • Complete, accurate
    • Audited

Slide 12

CV Registries across the Care Spectrum

  • HF/Stroke AMI/Care
    • Primary Prevention
    • Admitting Event
      • Admit
  • D/C
    • In pt Care
  • Post-Event: Cardiac rehabilitation Secondary Prevention


Slide 13

Clinical Registries as Engines for Evidence Development

  • In-hospital Registry
  • Cross sectional studies
  • In-hospital Registry
  • Claims Data
  • Longitudinal studies
  • In-hospital Registry
  • Device/Drug Information
  • Longitudinal Outcomes
  • Comparative Effectiveness
  • In-hospital Registry
  • Biomarker Gentics Samples
  • Longitudinal Outcomes
  • Translational Discovery

Slide 14

Duke DEcIDE and FDA CV Work (to Date)

  • TMR Evaluation (2003)
    • STS
  • DES vs BMS Comparative Effectiveness (2008)
    • ACC NCDR +CMS part A
  • DES vs BMS Subgroups + Imaging (2009)
    • ACC NCDR +CMS part A +B
  • Aortic Valves (2009)
    • STS + CMS part A

Slide 15

Diffusion of TMR into Clinical Practice

Description 1998 1999 2000
% Sites performing TMR 8.7 17 34.4
% Total TMR procedures 0.08 0.21 0.7
% TMR+CABG procedures 0.06 0.15 0.56
% TMR only 0.02 0.06 0.14

Peterson E. JACC 2003;42:1611-6.

Slide 16

NCDR DES vs BMS Longitudinal Analysis Methods

  • Objective: To examine comparative effectiveness and safety of DES vs BMS in a national PCI cohort
  • Population: All NCDR PCI pts 1/04-12/06
  • Follow up: Linkage to CMS inpatient claims data using indirect identifiers; 76% matched
  • Final cohort: 262,700 pts
    • 83% DES; 46% Cypher, 55% Taxus
  • Analysis: Inverse propensity weighted model
    • 102 covariates; Cox PH to verify mortality

Douglas P JACC. 2009 May 5;53(18):1629-41.

Slide 17

ACC 2009 LBCT: NCDR DES vs BMS 30-Month Event Rates

  Death MI Revasc Bleeding Stroke
BMS 16.5 8.9 23.5 3.6 2.7
DES 13.5 7.5 23.4 3.4 3.1

HR = 0.91
HR = 0.96
HR = 0.75
HR = 0.76
HR = 0.91
Rate / 100 patients

Slide 18


  • Consortium of 15 Health Plans
  • Collectively provide community-based healthcare to ~11 million persons
  • Broad age, gender, and racial/ethnic diversity across sites
  • High patient retention rates

Slide 19

HMORN Centers

A map of the United States is shown also listing the HMORN Centers.

Slide 20

HMORN Health Plans

  • Established Research Centers
  • Diverse delivery settings (e.g. inpatient, outpatient) and care models
  • Provide longitudinal care (including prevention, diagnosis, and treatment)
  • Linked lab, pharmacy, ambulatory care and hospital data
  • 14/15 sites have implemented an electronic medical record (EMR)

Slide 21

Registry Data Standardization Virtual Data Warehouse (VDW)

  • Common data dictionary
  • Data arrayed using identical names, formats, and specifications
  • SAS program written at one site can be run at other sites
  • Increases efficiency of multi-site studies
  • NOT a Data Coordinating Center or Centralized Data Warehouse

Slide 22

HMORN VDW Registry Standardized Data Tables

  • Patient Identification—Unique patient ID
  • Membership—Enrollment status
  • Demographics—Age, gender, race/ethnicity
  • Laboratory— Lab tests and results
  • Medications—Name, dose, route, date, # pills
  • Ambulatory—Diagnoses, tests, and procedures
  • Hospital—Diagnoses and procedures
  • Benefits—co-payments, co-insurance, deductibles
  • Vital Signs—BP, HR, BMI
  • Mortality

Slide 23

AHRQ Sponsored CV Research Projects—HMORN

  • Comparative Effectiveness Research
    • 2nd-line Anti-hypertensive therapy
    • �-blockers in patients with heart failure
  • Benefit/Harms of Medications in Routine Practice
    • Clopidogrel duration vs MI, Death, and Bleeding
    • Interaction of Clopidogrel and PPIs
  • Outcomes of Medical Devices in Routine Practice
    • Use of DES in off-label indications
    • Safety and Effectiveness of of ICDs

Slide 24

CER of BB vs ACE as 2nd-line Anti-Hypertensive Agents

  • BP Control usually requires >1 med
  • Optimal 2nd-line agent for pts whose BP is not controlled on a thiazide is unknown
  • Objective: To compare the effectiveness of ACE-inhibitors (ACE) vs. beta-blockers (BB) for HTN patients who are started on a thiazide but whose BP is inadequately controlled on a thiazide alone

Slide 25

HMORN HTN Registry Unique Characteristics

  • Size—Over 1 million patients
  • Exposure Assessment—properly identified and excluded patients receiving ACE or BB for reasons other than HTN
  • Ability to control for baseline BP (higher in patient receiving BB as 2nd-line therapy
  • Control for confounding bias using both diagnostic and lab data (e.g. renal function)
  • Assess BP control
  • Assess progression to renal disease

Slide 26

BP control at 1 year (adjusted model results)

  • Control Rates
    • ACE 70.5%
    • �-blocker 69.0% (p=0.09 for comparison)
  • Results consistent in subgroup analysis by site, gender and year

Slide 27

Hypertension Sequelae: Cox proportional hazards models

Outcome # events Hazard ratio
ACE vs. BB
95% CI
MI 96 1.05 (0.69-1.58)
Stroke 101 1.01 (0.68, 1.52)
(stage 3)
1,446 1.02 (0.91, 1.13)

* Additionally adjusted for eGFR.

Slide 28

DEcIDE CV Consortium Vision

  • Created as part of the Effective Health Care program with the Duke University and the HMO Research Network DEcIDE Centers
  • Bring expertise in multiple scientific areas to provide comparative effectiveness research
  • Develop a framework that aligns interests from the clinical community, governmental agencies, payers, professional societies

Slide 29

CV Consortium—Guiding Principals

  • Conduct and disseminate high-quality CV research with potential to improve health outcomes and care delivery
  • Engage with Stakeholders group in setting research priorities
  • Work collaboratively to leverage our joint data resources and expertise
  • Actively and transparently communicate with external audiences to allow accountability

Slide 30

2008 Kick-off Meeting

  • CVC Stakeholder Committee had this initial meeting in October 14, 2008
    • Project Investigators: HMORN, Duke
    • Governmental Agencies: AHRQ, FDA, NIH, CMS
    • Professional Socities: ACC, AHA, STS
    • Other Observers: Major payors
  • Topics: Coronary stenting, antiplatelet therapy and aortic valve disease

Slide 31

Future of CV Consortium

  • Define and Prioritize Topic Areas
    • Many existing and emerging CV therapies and diagnostic technologies, including:
      • Heart Failure
      • Coronary Artery Disease
      • Sudden Cardiac Death
      • Valvular Heart Disease
      • Atrial Fibrillation
      • Hypertension and other risk factor control
      • Peripheral Vascular Disease
      • Stroke

Slide 32

Future of CV Consortium

  • Broaden Stakeholders
    • American College of Physicians
    • American Association of Family Physicians
    • Patients
  • Strengthen Collaborations
    • DEcIDE Network
    • Professional Societies
    • Other Non-governmental agencies

Slide 33

Proposed CV Consortium Organization

  • Executive-Operations Committee (AHRQ, Duke, HMORN)
  • Steering Committee (Clinical and Methodologists)
    • Data and Methods
    • Stakeholders (CMS, FDA, NIH, Professional Societies)
    • Project Working Groups

Slide 34

At the End of the Day.

  • The CV DEcIDE Consortium and Collaboration can:
  • Capture high quality clinical data efficiently
  • Be used for scientific discovery
    • Track patients' longitudinal care
    • Track drugs/devises
    • Be linked to biological/imaging data
  • Complement/support traditional and practical RCTs
  • Helps drive new evidence into routine practice

Slide 35

Thank you


Current as of December 2009
Internet Citation: Maximizing Comparative Effectiveness Research The DECIDE CV Consortia. December 2009. Agency for Healthcare Research and Quality, Rockville, MD.


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