{"type":"rich","version":"1.0","provider_name":"Transistor","provider_url":"https://transistor.fm","author_name":"Show Me The Evidence","title":"Dr. Richard Angelo: From Apprenticeship to Proficiency — Rethinking How We Train Surgeons","html":"","width":"100%","height":180,"duration":2901,"description":"Episode 4 — Dr. Richard Angelo\n\nGuest\nDr. Richard (Rick) Angelo — Arthroscopic surgeon based in Seattle; former President of the Arthroscopic Association of North America (AANA). Holds a PhD in proficiency-based progression training.\nHost\nTony (relationship with Rick spans ~15 years, originating from a chance meeting at a conference in Sweden)\nEpisode Overview\nA deep-dive conversation on the fundamental failures of traditional surgical training and how proficiency-based progression (PBP) training offers a scientifically rigorous alternative. The discussion centres on the landmark Copernicus Study — the first study in medicine to use proficiency demonstration as an outcome measure.\nKey Topics Covered\n1. Limitations of the Traditional Apprenticeship Model\n\nThe \"see one, do one, teach one\" model lacks objective assessment\nDespite decades of training and significant investment, AANA could not verify whether skill acquisition was actually occurring\nComplication rates and suboptimal outcomes weren't improving with existing training efforts\n2. The Founding Question\n\nRick, during his time in the AANA presidential line, asked: \"Is there a better way to train surgical skills?\"\nThis led to engagement with Tony's work on proficiency-based progression training\n3. Proficiency-Based Progression (PBP) Training — Core Principles\n\nDefine a clear target: what does quality performance of a procedure look like?\nDeconstruct tasks into discrete, trainable components\nDevelop objective, binary metrics (did it occur or not?) rather than global rating scales\nEstablish inter-rater reliability between assessors\nTrainees must demonstrate a benchmark at each stage before progressing (including cognitive pre-course material — 83% threshold)\nErrors and deviations from optimal performance are trained explicitly — not just steps\n4. The Bankart Repair — Why It Was Chosen\n\nCommon procedure with a broad, transferable skill set\nSuited to task deconstruction and partial task simulation\nChosen by Rick...","thumbnail_url":"https://img.transistorcdn.com/JPxx16guuIWtjNqUkS-VeCJVeP1R-gkQQ7xD4SsyqqM/rs:fill:0:0:1/w:400/h:400/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS9lZGMy/MjkyM2UxYTkzZmM5/ZjVkMmI4MzAzOTM0/YTIzYi5wbmc.webp","thumbnail_width":300,"thumbnail_height":300}