1. National EMS Database Greg Mears, MD FACEP Principal Investigator North Carolina EMS Medical Director University of North Carolina-Chapel Hill

2. The Project: National EMS Information System Long Term Goals  Electronic EMS Data  Standard EMS Dataset  Data Systems  Local  State  National EMS Database  Data Drives EMS  System  Personnel  Clinical Care

3. The Team  NASEMSD  Project Management  Regional Meetings  Operational Support  Greg Mears, MD  Principle Investigator  NEDARC  Clay Mann, PhD, Co-Investigator  Mike Dean, MD, Co-Investigator  Technical Assistance  State Data-Managers

4. The Money  NHTSA  EMS Division (Primary)  HRSA  Trauma and EMS  EMS-C  American Heart Association  Support for EMS Software Development

5. The Consensus Professional Organizations  AAA  AAMS  ACEP  ACS-COT (NTDB)  AHA (NRCPR)  EMSOP  IAFC  IAFF  NAEMD  NAEMSP  NASEMSD  NENA Federal Partners  CDC  FEMA  HRSA-EMSC  HRSA-EMSC/NEDARC  HRSA-EMSC/NRC  HRSA-ORHP  HRSA-Trauma/EMS  NHTSA

6. The National EMS Information System National State Local System

7. The Data Sources

8. The Truth about NEMSIS Macroscopic  Public education and drive policy  Identify national trends  Drive education  Prioritize needs and funding  Benchmarking  Solidify EMS in the Healthcare family Microscopic  Outcomes  EMS Research hypothesis  Promote research Reality  Business structure and management  Improve reliability and efficiency  Reduce errors  Determine effectiveness of systems and patient care

9. The Need  EMS Education  Curriculums  Local Education  EMS Outcomes  Something other than death  System evaluation  EMS Research  Generate hypothesis  Evaluate Cost effectiveness  Identify problems and target issues  EMS Reimbursement  National fee schedule and reimbursement rates

10. GAO Emergency Medical Services Reported Needs Are Wide- Ranging, With a Growing Focus on Lack of Data

11. GAO Results….. The extent and impact of the reported needs is difficult to ascertain, however, because there is little standard and quantifiable information that can be used across systems. Most of the available information about the effect of unmet needs is localized and anecdotal.

12. Local Pulse  Data collection is important  Medical record keeping  Local data analysis  Decision making  Do not detract from patient care  Short time frame of documentation

13. Local: Where we are  Very little information on local EMS data collection  Most systems are paper based but are discussing or transitioning to electronic  Many systems use paper and scan into databases or do manual entry

14. Local: Where we are  Few systems are compliant with the NHTSA dataset definitions  Several models for data collection, but no uniformity or consistency across systems  In general, there is an absence of data to drive reimbursement and policy decisions

15. Local: Where we want to be  Electronic data collection  Uniform dataset with definitions  Patient care  Technician  System  Workflow oriented  No dual entry  Data comes from the source  CAD  Medical Devices  The health care components are linked  Hospital  Dispatch  Public Health  Public Safety  Quality Improvement  Benchmarking  Community based  Information is passed to the State office of EMS for finance and policy decisions

16. Local: How to get there  Technical Assistance  Model administrative and/or statutory language  Standards for data collection and definitions  Attach to EMS Education Agenda and local training programs  National job description for EMS providers  Medical and communication device transmission standards  National Performance Standards

17. State Pulse  There is no data for:  Resource planning  Budget justification  System-wide evaluation  Injury prevention programs  Target support and assistance

18. State: Where we want to be  State EMS database on every EMS patient encounter  Electronic data transmission  Privacy and confidentiality protection  System and patient  Statutory authority

19. State: Where we want to be  System wide Quality Improvement  Benchmarking of compliance and public health indicators  Disaster Management  Bioterrorism Surveillance  Support and Assistance Resources  Annual Report for policy makers  Provide data to the National EMS Database

20. State: How to get there  Identify resources for a state EMS database  Technical Assistance  Model templates and database schema’s  Model quality improvement reports  Support to the state EMS office  Uniform Dataset and definitions  Peer Review Model Legislation  Promote Research

21. National Pulse  Asystole

22. National: Where we are  EMS Agenda for the Future  Monographs, Trade journals  Surveys

23. National: Where we want to be  National EMS Database  NASEMSD lead the charge  Revision of the NHTSA Dataset  Multidisciplinary approach

24. What will we do with it?  Public education and drive policy  Identify national trends  Benchmarking  Reduce errors  Business structure and management  EMS Research hypothesis  Promote research  Outcomes  Solidify EMS in the Healthcare family  Drive education  Prioritize needs and funding  Determine effectiveness of systems and patient care

25. NEMSIS Project  Dataset  XML  Business Model  Pilot Project  Outreach/PR  Software Development

26. The Progress Completed  NHTSA Version 2 Dataset  EMS  Demographic  XSD Standard  Business Model In Progress  Pilot National EMS Database  Mississippi  North Carolina  4 others  Business Logic  Record  Component  Data Element  Database Validity  EMS Data Collection Software

27. Data Dictionary  Name  Definition  Variable Definitions  Single or Multiple Entry  Relationship to other Data Elements  Null Values  National EMS Database Element  Data Element Use  Medical Record  Quality Management  Report Types Possible  Collected by Whom  Relationship to Other Datasets  NHTSA Version 1  NFIRS  Utstein

28. Data Dictionary: XML  Data Type  Integer, String, Date/Time, Number  Relationship  One to One  Many to One  Required in XML  Minimal Entry Constraint  Maximal Entry Constraint  Formatting

29. Pilot Project  Demonstration National EMS Database  States Participating  Minnesota  Mississippi  North Carolina  Others as possible  Timeline  May, 2005 Key Components  National Dataset  XML  Physical Database for Storage  Web Based Reporting to the public

30. The State of the States

31. 2003 Rural EMS Survey Collection of Statewide EMS Data StatesTerritori es No and Nothing is Planned2 (4%)2 (33%) No, But a System is Being Planned6 (12%)0 No, But a System is Being Developed9 (18%)3 (50%) Yes, <50% of EMS Events are Being Collected5 (10%)0 Yes, >50% of EMS Events are Being Collected20 (40%)0 Yes, 100% of EMS Events are Being Collected8 (16%)1 (17%) Total States Reporting on EMS Data50 (100%)6 (100%)

32. 2003 Rural EMS Survey Submission of EMS Data to the State StatesTerritories No, No Plan to Require Data3 (6%)4 (67%) No, Plan to Require Data in the Future12 (24%)1 (17%) Yes, Data is Required through Regulation or Law 35 (70%)1 (17%) Total States Reporting on EMS Data Submission 50 (100%)6 (100%)

33. 2003 Rural EMS Survey Authority to Collect Patient Identifiers StatesTerritorie s Yes38 (76%)3 (50%) No10 (20%)2 (33%) Unknown2 (4%)1 (17%) Total States Reporting on EMS Data Identifiers 50 (100%)6 (100%)

34. 2003 Rural EMS Survey Peer Review Protection StatesTerritories Yes23 (46%)0 No21 (42%)2 (33%) Unknown6 (12%)4 (67%) Total States Reporting on Peer Review Protection 50 (100%)6 (100%)

35. 2003 Rural EMS Survey 2002 EMS Patient Transports StatesTerritories Minimum EMS Patient Transports/state27,4634,000 Maximum EMS Patient Transports/state1,502,00084,000 Average EMS Patient Transports/state331,15354,595 Median EMS Patient Transports/state130,00075,785 Total EMS Patient Transports6,954,211163,785 Total States Reporting EMS Patient Transports 21 (42%)3 (50%)

36. NEMSIS 2005 - 2006  Limited Implementation of the National EMS Database  Establishment of a NEMSIS Resource and Technical Assistance Center  Documentation  Compliance  Data Validity  Measurement of progress across states  Increased use support and software developer interaction  Software  Database schema  XML test cases  Data entry software  Scripted reports  Other?