Preventing Venous Thromboembolism in an inpatient setting

1. Preventing Venous Thromboembolism in an inpatient setting Chad Hodge Mark RimbergasAmy Rubin

2. Problem-Introduction • Identify High Risk Area • Make It Easy to do Right Thing at Right Time • Standardized, Structured, and Reliable Approach Venous Thromboembolism (VTE) Prevention

3. definition • Two conditions • Life-threatening • Very Preventable

4. prevalence • 200,000 people per year develop venous thrombi with 50,000 going on to develop a pulmonary embolism (PE) • 1 in 10 of the 2 million patients per year that develop PE will die • Incidence is 80 cases/100,000 patients

5. Clinical Relevance: Risk Factor

6. Stratification & Treatment • Stratification levels • High, Moderate and Low • Treatment • Early and frequent ambulation • Pharmacologic • Mechanical

7. Contraindications • Pharmacologic • Absolute • Active hemorrhage, severe trauma to head or spinal cord with hemorrhage in last 4 weeks • Relative • Intracranial hemorrhage within last year, craniotomy or intraocular surgery within 2 weeks, gastrointestinal, genitourinary hemorrhage within last month, thrombocytopenia or coagulopathy, end stage liver disease, active intracranial lesions/neoplasm, hypertensive urgency/emergency and post-operative bleeding concerns • Mechanical • Known DVT, previous immobility, severe arterial insufficiency

8. Administrative relevance • Cost • Regulatory • National Quality Forum (NQF) • Centers for Medicare and Medicaid Services (CMS) • Clinical Measures • Never Events • EHR Incentive Program • Meaningful Use Clinical Quality Measures

9. Existing tools • Showed Impact/Improvement however… • Not comprehensive enough • Not proactive • Not fully incorporated into workflow

10. Clinical goals • Automation of risk stratification • Streamlined and automated process for: • Recommendation of prophylaxis based on stratification • Mechanical prophylaxis order for placement and/or • Pharmacologic prophylaxis order • Associated safety processes • Incorporated into workflow

11. Clinical Goals To Prevent Venous Thromboembolism and associated complications!

12. Administrative goals • Cost Reduction • Meet regulatory and quality assurance requirements • National Quality Forum (NQF) • Centers for Medicare and Medicaid Services (CMS) • Clinical Measures • Never Events • EHR Incentive Program • Meaningful Use Clinical Quality Measures

13. Model – CDS Rule

14. Model - Trigger

15. Model – Contraindications • Active hemorrhage (Boolean) • Severe trauma to head or spinal cord with hemorrhage in the last 4 weeks (Boolean) • Intracranial hemorrhage within last year (Boolean) • Craniotomy within 2 weeks (Boolean) • Intraocular surgery within 2 weeks (Boolean) • End stage liver disease (Boolean) • Thrombocytopenia (<50k) of prothrombin time > 18 seconds) (Boolean) • Hypertensive emergency (Boolean) • Allergic to warfarin (Boolean, and severity) • Allergic to un-fractionated heparin (UFH) (Boolean, severity) • Allergic to low molecular weight heparin (LMWH) (Boolean, severity) • Has skin lesions on left leg (Boolean) • Has skin lesions on right leg (Boolean)

16. Model - Response • Alert trigger time (date/time) • Alert ignored / cancelled (Boolean) • Risk group pre-selected on alert by CDSS (enumeration: Low, Med, High) • Pharmacological intervention selected (enumeration: UFH, LMWH, warfarin) • Pharmacological intervention dosage (unsigned integer) • Early and frequent Ambulation • Pharmacological intervention rate in hours (unsigned integer) • Mechanical intervention selected (enumeration: (sequential compression device, leg hose) • Mechanical intervention area: (enumeration: left leg, right leg, both)

17. Model – Knowledge Repository • CDS rule to be coded using standard terminology and stored in KR. • Semantic shift • Better criteria for rule • New / different coding schemes. • Layering • Department specific contraindications (OB/GYN) • Analytics / Reports

18. System - Components • End User Interface • EMR • Analysis and Data Mining Module • Knowledge Base Interface • Knowledge Base Module • Active Integrated NLP-CDS inference engine

19. System – Architecture

20. System – Input /Alert Output

21. System - Standards • HL7: Will be used for the exchange, integration, sharing, and retrieval of electronic health data. • XML: Will be used document storage and data integration. • CDA: Forspecifyingencoding, structure, and semantics of clinical documents for exchange. • LOINC: For identifying medical laboratory observations. • SNOMED: To help index, store, retrieve, and aggregate the data. • CCOW: To enable the disparate applications in our organization to synchronize in real-time. • HIPPA: To ensure patient confidentiality when patients are transferred to other healthcare providers and hospitals. • ICD-9: To classify diseases, injuries, and cause of death.

22. System - Interfaces • Interface Engine • Interfacing with internal systems • Interfacing with external systems

23. Evaluation • Implementation • Settings and Test Environment • Utilizing Plan, Do, Study and Act (PDSA) • Challenges

24. The End • Questions?