Clinical Registries in Cardiac Surgery Peter S. Greene, MD CMIO, Johns Hopkins Medicine Diane Alejo Information Systems Manager Division of Cardiac Surgery September 15, 2010 ICTR Clinical Registry Workshop

Cardiac Surgery Database spans Clinical and administrative data tracking Supports IRB approved clinical research activities Allows longitudinal outcome follow-up STS Adult Cardiac Surgery Data / STS Congenital Data Heart and Heart- Lung Transplant Database UNOS Registry ISHLT / INTERMACS VAD Registry Collaborative Transplant Research Database Cardiac Surgery Data Management

History of Cardiac Surgery Database Blalock-Taussig Registry 15, Cardiac Registry - Medical Archive’s Operative Logs 7, Cardiac Surgery Database & Cardiac Transplant Database 18, Expanded Data Collection - Point of Care / Work Flow Integration 42, 615TotalOperations recorded in the Databases STS Adult Cardiac Surgery Database Participation > 13,000 Johns Hopkins Adult Cardiac Operations submitted to STS from

Clinical Documentation STS Leap Frog NQF PQRI Performance Improvement Payers Research Patient Care Billing Admin Reports DATA UNOS Resident Education Maintenance of Certification

DRG Codes STS Participation LeapFrog / PQRI National Quality Forum Performance Improvement Score Cards Maintenance of Certification Surgeon / Resident Portfolios APRDRG codes Payers, RFI / RFP’s ICD 9 codes CPT codes Administrative Reporting Billing / Resource Utilization Cardiac Database Consumers & Marketing Sources of Data and Reporting For Outcome Measurement & Research in Cardiac Surgery Clinical Data Clinical Registries Research Data REPORTS

1.Must have strong clinical leadership and pervasive buy-in 2.Must integrate with clinical workflow 3.Must provide net benefit to clinicians 4.Must stay within scope of readily known data 5.Must have a stable and capable clinical team 6.Must have a stable and capable data team 7.Must audit for completeness 8.Must give regular feedback 9.Must pre-stage submissions Some Lessons Learned

Outcome Data

Standardized information on cardiac & thoracic surgical procedures Data analyzed by separate, independent, objective data analysis center (DCRI) Opportunities to improve patient care # Participants # Records Harvest Adult Cardiac million4 times / year General Thoracic 81185,508 operations2 times / year Congenital ,628 operations 2 times / year STS National Database

STS Pilot Pay For Performance (P4P) Program Incentive payments for achievement of thresholds in performance measures A model of quality improvement with 3 types of measures: Structureal: IT, database participation, volume Process: IMA use, discharge beta blockers Outcomes: Mortality, Morbidity: CVA, renal failure Blended STS NCD and financial (UB-92) database NQF performance measures 2007 PQRI Initiative – CMS New 2007 STS Composite Scoring System STS National Database

DCRI – Data Warehouse and Analysis Center Data transmitted electronically National, Regional and “Like Institution” benchmarking Reports include site specific, risk adjusted, regional and national aggregate date including morbidity, mortality and LOS for CABG, Valves and CABG/Valve surgery Statistical Analysis – Risk Modeling- Logistic Regression, Hierarchical regression modeling STS National Database

STS Auditing Risk factor model variables NQF measures Op log procedures Operative deaths and morbidity STS National Database

STS Adult Database 992 STS Congenital Database 81 STS Thoracic Database 142 Total1215 STS National Database Participation

STS Composite Quality Score Distribution of Participant Site Ratings March 2008 Percent

STS Composite Quality Ratings * Participant is significantly lower than the STS mean * * Participant is not significantly different than the STS mean * * * Participant is significantly higher than the STS mean Jan – Dec 2009 JHHSTSRating Overall95.3 % Avoidance of Mortality 97.3 %97.9 % Avoidance of Morbidity 82.6 %84.5 % Use of IMA98.5 %94.5 % Medications 80.2 %76.0 %

Research Informatics Department of Surgery

PREMISES OF THIS PROPOSAL FOR A SURGERY DATA CENTER Almost every faculty member and research trainee has a need for accessing clinical data for research purposes There is insufficient revenue to support a centralized research database –There is a modest amount of research database activity in the department There is an extensive amount of clinical information within JHMI in an electronic format, but these exist in multiple sources There is an extensive amount of surgical patient data being collected and analyzed for non-research activities (e.g.: safety, accreditation, payers, training)

IDX SALAR Lung Cancer Database (M. Brock) STS Thoracic Database Transplant Information Systems Teleresults UNOS / CTRD Maryland Trauma Registry Anesthesia ADR Specialty Surgical Research Databases ORMIS Casemix CVIEW Cardiac Surgery Database STS Adult Cardiac / Congenital Surgery Core ISHLT VAD Registry Internal Data Sources and Internal Database Initiatives Clinical Data NSQIP Research Data EPR POE Tumor Registry Departmental Prototype Clinical Trial Databases

Idea – Explore Influence of Randomness

Idea – Quality Collaborative

Idea – Patient Registries From Dr. Adrian Puttgen Dept. Neurology, Critical Care v=WQ2PFoHptK8

1.Unique patient population 2.Unique patient tracking capability 3.Unique patient detail or comprehensiveness 4.Unique patient data integration 5.Regional quality programs 6.National quality programs Clinical Registry Opportunities