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Mannequins, Simulators and E-learning in Medicine

Mannequins, Simulators and E-learning in Medicine. Sem Lampotang, PhD Professor of Anesthesiology Center for Simulation, Advanced Learning and Technology Department of Anesthesiology Medical Update University of Mauritius July 25, 2007. Disclosure.

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Mannequins, Simulators and E-learning in Medicine

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  1. Mannequins, Simulators and E-learning in Medicine Sem Lampotang, PhD Professor of Anesthesiology Center for Simulation, Advanced Learning and Technology Department of Anesthesiology Medical Update University of Mauritius July 25, 2007

  2. Disclosure • Co-inventor of the Human Patient Simulator • Developer of the simulations on the Virtual Anesthesia Machine web site http://vam.anest.ufl.edu/wip.html

  3. Acknowledgements • Thomas H. Maren Foundation - USA • Anesthesia Patient Safety Foundation - USA • Novo Nordisk - Denmark • IBM Thomas J. Watson Research Center - USA • GE Healthcare / Ohmeda - USA • GaleMed – Taiwan • Prodol/AirTraq - Spain • Enturia - USA • Molecular Products – United Kingdom • Karl Storz - Germany • The VAM team

  4. Outline • Simulation in Healthcare • Mannequin simulators • Web simulation and e-learning

  5. Deaths from medical error • Institute of Medicine’s 1999 report “To err is human” estimates that medical error causes between 44,000 to 98,000 deaths each year in the United States • Equivalent on the low end to 2 jumbo jets full of passengers crashing every week!

  6. Six Sigma Sigma Values +/ - 1 = 68.26% Point of Inflection +/ - 2 = 95.44% +/ - 3 = 99.73% p(d) p(d) s 1 6 5 4 3 2 1 1 2 3 4 5 6 LSL USL M A 6 Sigma Process includes 6 standard deviations between 6 sigma accuracy = 3.4 defects per million the mean and the spec limit Reliable Performance is Elusive…. Troglitazone LFT monitoring IRS Tax Advice ACE-I for EF <40% and yearly HbA1C for DM B blockers after AMI 1,000,000 Restaurant bill mistakes 100,000 10,000 Airline baggage handling Negligence in hospitals ABX for Viral URI 1,000 100 10 Defects per Million Anesthesia deaths Airline safety 1 0 1 2 3 4 5 6 Sigma Level 6

  7. Rene Alamberti, Ann Intern Med. 2005;142:756

  8. Criteria for justifying the expense of simulation (in any field) • Errors are expensive • Reality is dangerous • Events are rare

  9. Why simulation? • Learning in clinical medicine has traditionally followed an apprenticeship model: “see one, do one, teach one” • Rate of discovery and creation of new knowledge keeps on accelerating, including in healthcare – apprenticeship model no longer tenable • Learning by doing • Hands-on learning

  10. Mannequin Simulators • Consumes O2, produces CO2 • Clinical signs • Monitored physiological signs • Mathematical models of pharmacokinetics/pharmacodynamics • Cardiopulmonary model • Can simulate different disease states

  11. Gainesville Anesthesia Simulator

  12. Human Patient Simulator

  13. Respiratory System

  14. Respiratory System

  15. Respiratory System O2 CO2 N2 N2O

  16. Invasive and non-invasive blood pressure

  17. Electrocardiogram

  18. Multi-compartment model • Left atrium • Left ventricle • Intrathoracic artery • Extrathoracic artery • Vessel rich group tissue • Muscle group tissue • Fat group tissue • Extrathoracic vein • Intrathoracic vein • Right atrium • Right Ventricle • Pulmonary artery • Ventilated lung tissue • Shunted lung tissue • Pulmonary vein

  19. Nervous System

  20. Nervous System

  21. Urinary System

  22. Drug Recognition

  23. Drug Recognition

  24. Installations worldwide • http://www.meti.com • HPS Installations

  25. Some problems spanning the entire healthcare system… • Industry education • Education of regulatory body personnel • User education and training • Patient education issues • Patientsafety issues involving healthcare systems

  26. Transparent Reality (TR) Simulation • Invented at UF • “Transparent reality simulation” coined at UF • Identified as 4 – 5 years away from general adoption by Educause Horizon Report 2006

  27. Some problems … • Industry education • Basic science and R&D • Engineering/production/pre-market approval (Mannequin Simulator-Based Usability studies) • Marketing/Sales force training • Education of regulatory body personnel (FDA)

  28. Some problems … • User education and training • Reality is opaque and complex and can get in the way of learning • Incompatible international standards • Medical error • Human error 3 times more common than equipment failure for anesthesia machines (Closed claims study) • Failure to check, failure to detect, failure to teach • “Black hole” users/ Difficult users • Are clinicians really using the training material? • How much are they really getting? What do they find hard? • Credentialing • Can clinicians really use a given product safely? • Equitable access to essential patient safety materials

  29. Some problems … • Patient education issues • Patient compliance • Non-compliance major reason for organ transplant rejection

  30. Some problems … • Patient safety issues; Systems issues • Defining the problem • Identifying the problem • Quantifying the problem • Investigating causal factors and possible solutions • A FMEA (Failure Mode Effects Analysis) exercise has to take into account the entire system including user training, competency, vigilance and fatigue

  31. UF Virtual Anesthesia Machine Web Site http://vam.anest.ufl.edu/wip.html The UF VAM web site will be used as a concrete example of the different forms of web applications that address some of the previously identified problems.

  32. Transparent reality simulation

  33. Blackbox opaque simulation

  34. TR Provides Better Learning 3 Transparent VAM 2.5 Opaque VAM 2 Quality Score (max. 4.0) 1.5 1 0.5 0 Component Identity Component Function System Dynamics

  35. Some problems … • Patient education issues • Patient compliance • Non-compliance major reason for organ transplant rejection

  36. Some problems … • Patient safety issues; Systems issues • Defining the problem (anesthesia machine pre-use check survey) • Identifying the problem • Quantifying the problem • Investigating causal factors and solutions • Survey results • 20% check before every case, 50% only first case of the day, what about remaining 30%?

  37. Does this really work? • The web provides democratic “peer review” where everyone votes with their mouse. • #1 on Google for “anesthesia machine” • #1 on Google for “airway device” • #1 on Google for “fospropofol simulation” • #1 on many more terms and search engines • Webalizer stats • AwStats stats

  38. Equitable access to essential patient safety materials

  39. Questions? • Email: sem@anest.ufl.edu • Simulation portfolio URL: http://vam.anest.ufl.edu/wip.html

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