1. COMPUTER DRIVEN DECISION MAKING IN EMS Mohamud Daya MD, MS Professor of Emergency Medicine Oregon Health & Science University

2. Challenge  Knowledge growing exponentially  Ability to keep up limited by human processing power  Aging population

3. Example: Calcium Channel Antagonists  1984  Nifedipine  Diltiazem  Verapamil  2016  Amlodipine  Diltiazem  Felodipine  Isradipine  Nicardipine  Nifedipine  Nisoldipine  Verapamil  Nimodipine

4. Emergency Medical Services  Practice of medicine in the out-of-hospital setting  Need to make accurate decisions in a time constrained environment in an increasingly complex world  Aging population increasing call volume  Hospitals expensive  Community based health care model (Patient Centered_  Growth of mobile integrated health care in EMS (beyond transport)  Technology advances (EMR, Cloud, WiFi)

5. Potential Solutions  Enhance used of computerized algorithms to drive clinical decisions  Harness computer’s ability to store information, rapidly retrieve and process to guide care  Cloud for rapid information retrieval

6. Initial Project – HP Shock Advisory Algorithm Development

7. Shock Advisory Algorithms  Part of all AED’s  Public Access and EMT Defibrillation  3 second looks x 2-3  Analysis time  continued evolution

8. Cardiac Arrest – CPR Feedback

9. VENTILATIONS (impedance) PADS ACCELERATION (“gravity”) DIRECT IMPEDANCE FORCE (“gravity”)

10. Impedance Signal Algorithms  Rate  ROSC

12. 12 lead ECG Algorithms

13. 2006

14. 2015

15. CLINICAL DECISION RULES

16. CDR Examples  HEART Score  Ottawa Ankle Rules  NEXUS  Canadian C-Spine Rule  PERC score  Cincinnati Stroke Scale  LAPSS  LVO scores  RACE  LAG  LAMSS  C-STAT ED – Management/TestingEMS – Triage

18. GLOBAL INFECTIOUS DISEASE AND EPIDEMIOLOGY NETWORK (GIDEON)

19. https://youtu.be/SVRnzILyBOI

20. EMR, THE CLOUD AND WIRELESS CONNECTIVITY

21. QUESTIONS?