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Resuscitation Outcomes Consortium (ROC) - Dr. Laurie Morrison

Epistry Subcommittee

  • Graham Nichol (DCC)
  • Cliff Calloway (Pittsburgh)
  • Jim Christenson (BC/OPALS)
  • Diane Atkins (Iowa)
  • Craig Newgard (Portland)
  • Ron Pirallo (Milwaukee)
  • Laurie Morrison (Toronto)
  • Joe Minei (Dallas)
  • Tom Terndrup (Alabama)
  • Tom Rhea (Seattle)
  • Dan Davis (San Diego

EMS OPS members

  • Jonathan Larsen (Seattle)
  • Jamie Frank (Toronto)
  • Michael Hartley (Iowa)
  • Shannon Stevens (Alabama)
Jennifer Long Data Management (Toronto)
Berit Bardarson (DCC)
Gena Sears (DCC)
George Sopko (NIH)
Tracey Hoke (NIH)
Study Chairs
Joe Ornato, John Holcomb
Chair Mike Weisfeldt
Resuscitation Outcomes Consortium (ROC)

Epistry Overview

  • Epidemiological Databank for ROC
  • Provide population based EMS and outcome data (field and in-hospital)
  • Baseline for all ROC interventional trials
  • Complementary to existing registries addressing the bias (missing data)
    • OHCA deaths (90% in field death rate),
    • EMS data
    • Non trauma centre outcomes


  • Shining a light makes a difference
  • In other words, a registry is an intervention that in and of itself can improve outcomes in participating sites

The Intervention

  • An internet based registry of standardized data pertaining to adults, infants and children with OHCA or life-threatening trauma for all ROC centers.

Inclusion Criteria

  • Individuals who experience out of hospital cardiac arrest in ROC communities evaluated by organized EMS personnel;
    • a) who receive external defibrillation administered by anyone, or
    • b) on whom EMS personnel perform chest compressions


  • Data upload using a web based interface or
  • Download from existing data sources initially,
  • Work to standardize uniform data collection at the level of the paramedic,
  • Implement data quality initiatives and evaluate,
  • Facilitate direct electronic transfer

Potential Contributions to ROC Outcomes

  • Collect inhospital outcomes common to all ROC trials on all registry patients
  • Provide population based outcome estimates for CA and Trauma
  • Measure the crude pooled estimate of resuscitation success for the consortium- track overtime

Potential Contributions to ROC Population

  • Share best practices across ROC centers
  • Provide web based EMS operational reports and data quality management
  • Provide population estimates of program interventions i.e. bystander CPR

Potential Contributions to ROC Studies

  • Provide pilot data to define existing standards of care, sample size calculations, duration for protocol development
  • Track and define the characteristics of missed patients or excluded patients to report on generalizability

Unique Contributions to ROC Productivity

  • Quality Administrative Datasets
    • Answer research questions not amenable to randomized controlled trials
    • Evaluate policy through regional surveillance
    • Generate RO1/RO3 & CIHR grants
    • Epidemiological and surveillance manuscripts

Why Epistry is important to CV surveillance

  • Most CA generate an EMS response
  • Most die in the field
  • Most Efficacious interventions occur early
  • Population based without EMS data lacks validity

ROC Population

  • Population 26 million
    • Hospitals >101
    • EMS Systems at least 70
  • Per Annum
    • 1.8 million EMS transports
    • Trauma 46,000 (95%)
    • Cardiac Arrest 18,000 (5.2%)

Literature Search

  • MEDLINE (31)
  • EMBase (6)
  • Health Star (5)
  • Journal of Medical Internet Research 2001 (1)
  • CINAHL (8)
  • Dissertation abstracts (6)

Favorite Reference

  • Cardiac Arrest and Cardiopulmonary Resuscitation Outcome Reports: Update and Simplification of the Utstein Templates for Resuscitation Registries. Circulation. 110(21):3385-3397, Nov 23, 2004

Complementary Data - Linkable Partners

  • National Registry Cardiopulmonary Resuscitation (AHA)
  • Canadian Cardiovascular Outcomes Research Team (CIHR, HSFC)
  • Critical Care Research Net
  • National Trauma Registries

Web Sites - helpful

Minimum Data Set and Dictionary

  • 72 Minimum Data Points
    • Data variable names
    • Data response codes
    • Data dictionary
      • Definitions
      • Source
      • Intent
      • Data entry
      • Judgment

Current Linkage

  • Site Specific Survey
    • In-hospital datasets
    • Existing registries
    • Hand abstracted
    • Privacy and ethical issues

Probabilistic Matching

  • EMS linking resulted in > 90% capture with Sensitivity of 90% and Specificity of 100%.
  • OHCA; S. Waien AEM 1997, Trauma: C. Newgard AEM 2005

Peer Review

  • ReSS: Highest rated ROC protocol
  • Submission to External Agencies - AHA
  • Planned submission to NIH RO1

Back to Workshop Agenda

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