Technology for Teaching and Learning Regional Anesthesia
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By the end of this session, learners will be able to discuss: 1. The "learning curve" for regional anesthesia; 2. Technology for teaching and learning; and 3. Technology for assessment.
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Technology for Teaching and Learning Regional Anesthesia
- 1. @@EMARIANOMD Technology for Teaching and Learning Regional Anesthesia Edward R. Mariano, M.D., M.A.S. Professor of Anesthesiology, Perioperative & Pain Medicine Stanford University School of Medicine Chief, Anesthesiology and Perioperative Care Veterans Affairs Palo Alto Health Care System
- 2. @EMARIANOMD Financial Disclosures • Halyard Health, B Braun – Unrestricted educational program funding paid to my institution The contents of the following presentation are solely the responsibility of the speaker without input from any of the above companies.
- 3. @EMARIANOMD Overview • The “learning curve” • Technology for teaching and learning • Technology for assessment
- 4. @EMARIANOMD Overview • The “learning curve” • Technology for teaching and learning • Technology for assessment
- 5. @EMARIANOMD How Hard Can It Be? NYSORA.COM -
- 6. @EMARIANOMD The “10,000 Hours Rule”
- 7. @EMARIANOMD Deliberate Practice Ericsson. Acad Emerg Med 2008;15:988
- 8. @EMARIANOMD Regional Anesthesia “Learning Curve” Reg Anesth. 1996;21:182
- 9. @EMARIANOMD Learning Curve for UGRA RAPM 2004;29:544
- 10. @EMARIANOMD Novice Behavior • 520 ultrasound-guided nerve block captured on video and reviewed – 7 errors: needle not visualized, inadequate equipment preparation, poor ergonomics, target malpositioning on screen, unintentional probe movement, awkward hand position on needle, and excessive visual focus on hands • By the 60th block, still 2.8 errors per block Sites, et al. RAPM 2007;32:107
- 11. @EMARIANOMD Barrington, et al. RAPM 2012;37:334
- 12. @EMARIANOMD Udani & Mariano, et al. RAPM 2016;41:151 Avg 7 (2–22 min) for the control group vs. 48 (29–65 min) for the DP group (p<0.001). No other differences!
- 13. @EMARIANOMD Predictors of Learning UGRA Shafqat, et al. Anesth 2015;123:1188
- 14. @EMARIANOMD Predictors of Learning UGRA Shafqat, et al. Anesth 2015;123:1188 Maybe we are not all the same!
- 15. @EMARIANOMD Overview • The “learning curve” • Technology for teaching and learning • Technology for assessment
- 16. @EMARIANOMD Udani & Mariano, et al. Local Reg Anesth 2015;8:33
- 17. @EMARIANOMD What Is “Simulation”? 79 articles involving simulation were reviewed: 1. Simulation-based educational interventions (14) 2. Novel simulator design (18) 3. Use of a simulated environment as an experimental setting (11) 4. Other/outside scope of review (36) Udani & Mariano, et al. Local Reg Anesth 2015;8:33
- 18. @EMARIANOMD Udani & Mariano, et al. Local Reg Anesth 2015;8:33 Studies of Simulation Interventions
- 19. @EMARIANOMD Udani & Mariano, et al. Local Reg Anesth 2015;8:33 Studies of Simulator Design
- 20. @EMARIANOMD Udani & Mariano, et al. Local Reg Anesth 2015;8:33 Inorganic Simulator
- 21. @EMARIANOMD Udani & Mariano, et al. Local Reg Anesth 2015;8:33 Organic Simulator
- 22. @EMARIANOMD “Hybrid” Simulator Udani & Mariano, et al. Local Reg Anesth 2015;8:33
- 23. @EMARIANOMD Ramlogan R, et al. RAPM 2017;42: 217 http://www.pie.med.utoronto.ca/VSpine/index.htm
- 24. @EMARIANOMD Udani & Mariano, et al. Local Reg Anesth 2015;8:33 Studies Using a Simulation Setting
- 26. @EMARIANOMD Lectures, Scanning Iterative Practice, Simulation 8 Hour Program Mariano, et al. JUM 2015;34:1883
- 27. @EMARIANOMD Mariano, et al. JUM 2015;34:1883
- 28. @EMARIANOMD Echogenic Technology Mariano, et al. JUM 2014;33:905 Moy & Mariano, et al. JUM 2017 epub
- 29. @EMARIANOMD Needle Guidance Systems McVicar, et al. RAPM 2015;40:150
- 30. @EMARIANOMD Overview • The “learning curve” • Technology for teaching and learning • Technology for assessment
- 31. @EMARIANOMD Simulation (Dr. David Gaba) #CAS_SCA2017 June 24, 2017
- 32. @EMARIANOMD Video Recording and Review
- 33. @EMARIANOMD Assessment Category Description Points Procedural Time (min) Starting when US probe touches skin and ending when placement needle is removed 2 (≤5 min) 1 (6-10 min) 0 (>10 min) Needle Passes (#) Withdrawal of the placement needle >1 cm with readvancement 2 (1) 1 (2) 0 (>2) Procedural Performance Needle visualization during advancement 2 (All the time) 1 (Part of the time) 0 (None of the time) Equipment preparation (e.g., probe selection, machine settings) 2 (Excellent) 1 (Good) 0 (Poor) Target positioning (eg, able to see target and feasible needle trajectory) 2 (All the time) 1 (Part of the time) 0 (None of the time) Probe stability (eg, no unintentional movement) 2 (All the time) 1 (Part of the time) 0 (None of the time) Needle manipulation (eg, comfortable grip on needle and catheter) 2 (All the time) 1 (Part of the time) 0 (None of the time) Visual focus (eg, appropriately focused on machine and not hands during procedure) 2 (All the time) 1 (Part of the time) 0 (None of the time) Confirmation of proper injectate spread 2 (Excellent) 1 (Good) 0 (Poor) Confirmation of proper catheter tip position 2 (Excellent) 1 (Good) 0 (Poor) Ergonomic Factors Positioning of ultrasound machine 2 (Excellent) 1 (Good) 0 (Poor) No thoracolumbar flexion (≥45) 2 (All the time) 1 (Part of the time) 0 (None of the time) No head/neck rotation (≥45) 2 (All the time) 1 (Part of the time) 0 (None of the time) No lateral shoulder tilt (≥30) 2 (All the time) 1 (Part of the time) 0 (None of the time) No crossing sterile field to non-dominant side 2 (All the time) 1 (Part of the time) 0 (None of the time) Mariano, et al. JUM 2015;34:1883
- 34. @EMARIANOMD DOPS Wragg, et al. Clin Med 2003;3:131 Watson, et al. Anaesth 2014;69:604 Chuan, et al. Anaesth Int Care 2016;44:2
- 35. @EMARIANOMD DOPS Wragg, et al. Clin Med 2003;3:131 Watson, et al. Anaesth 2014;69:604 Chuan, et al. Anaesth Int Care 2016;44:2
- 36. @EMARIANOMD Global Rating Scale Cheung, et al. RAPM 2012;37: 329 Wong, et al. RAPM 2014;39:399
- 37. @EMARIANOMD Hand Motion Analysis Chin, et al. RAPM 2011;36:213
- 38. @EMARIANOMD Eye Tracking Harrison & Mariano, et al. J Anesth 2015;30:530 The Expert 94 sec 1.85 fixations/sec The Novice 257 sec 0.86 fixations/sec
- 39. @EMARIANOMD J Anesth 2015;30:530 How Does Expertise Look? Can We Quantify It?
- 40. @EMARIANOMD Borg & Mariano, et al. In press.
- 41. @EMARIANOMD Summary We discussed: • The “learning curve” • Technology for teaching and learning • Technology for assessment
- 42. @EMARIANOMD “Regional anesthesia is a vital skill for any anesthesiologist and ultrasound-guided techniques have enhanced our ability to achieve effective and consistent blocks. It is important that we ensure our graduating residents have the requisite skills to perform basic regional techniques in a safe and effective manner in order to disseminate the benefits of regional anesthesia to the broader surgical population.” McCartney & Mariano. RAPM 2016;41:663.
Editor's Notes
- This is likely the reason I was invited to give this talk. We recently published a literature review in Local and Regional Anesthesia. A special thank you to my co-authors, Eddie Kim, Steve Howard, and Ed Mariano. If you are on twitter the key resources from this talk have been tweeted from my account.
- In our review, we identified 79 articles focused on simulation and regional anesthesia. We categorized each article into the following categories. Simulation-based educational interventions, where simulation was used to teach. Novel simulator design where various simulators for regional anesthesia were designed and tested. Use of a simulated environment as an experimental setting, where a simulated environment was used to test a device or novel technique. And finally a category the was outside the scope of our review and teaching in any sense.
- You will probably not be able to read this, but even the three studies that included a control group had small sample sizes of between 10-20 per group. Most found significant improvements in performance for the group taught using simulation. As mentioned all the other studies of educational interventions using simulation either did not have a control group or did not test a comparable group for an impact. Thus the incremental benefit of simulation in these studies was not investigated.
- We categorized 18 articles into novel simulator design. I believe regional anesthesiologists have many similarities to MacGyver – there are very handy and creative and maybe thrifty. Simulators can be inorganic or organic. Inorganic phantom simulators are common but in my opinion lack realistic tactile sensation and haptic feedback. They also do not allow for injection of liquid solutions. They are useful for teaching procedural steps, dexterity and needle guidance.
- In contrast, organic phantoms – in this image meat with inserted bovine tendon produce realistic sonoanatomy and do allow for injection and even catheter insertion. However they are not reusable. Since it is difficult to present every simulator for regional anesthesia we define novel as new and previously undescribed product employing innovative technology to represent the realistic scenario of performing a regional anesthesia procedure. We further categorized them into four forms: a physical model, virtual reality model, robot-assisted model, and environmental modification.
- Finally, we categorized articles which used simulation to evaluate a new medical device or established technique. For example, assessing the effectiveness of the air-test for catheter tip location. Also assessing the management of LAST using a checklist