NHLBI Workshop
Data Needs for Cardiovascular Events, Management, and Outcomes
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)
Experts
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
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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
Vision
- 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
Through
- 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
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