This episode of RAPM Focus introduces something new—an episode generated completely by artificial intelligence, specifically Google Notebook. As part of RAPM’s commitment to exploring innovative ways to deliver content, RAPM is trialing this approach and would love to hear your feedback.

This AI-generated episode is centered around an original research paper first published in RAPM in November 2024, “Standardizing nomenclature in regional anesthesia: an ASRA-ESRA Delphi consensus study of upper and lower limb nerve blocks.”

This podcast episode highlights the power of clear communication in medicine, and the ways in which nomenclature brings order to the world of medical terminology. Specifically, the inconsistent naming of nerve blocks can lead to confusion and chaos that result in real consequences.

Different doctors and researchers using different names for the same techniques leads to difficulties in comparing results and sharing knowledge. “Standardizing nomenclature in regional anesthesia: an ASRA-ESRA Delphi consensus study of upper and lower limb nerve blocks” dives into how convoluted the names of nerve blocks have become. This leads to a recipe for miscommunication—not ideal in the world of pain management. By standardizing the nomenclature of nerve blocks, patient safety is increased for those undergoing surgeries involving nerve blocks.

The study lays out a clear system for naming nerve blocks in order to standardize the language of nerve blocks. This system showcases the importance of nomenclature in not just nerve blocks, but in pain management and medicine as a whole.

*The purpose of this podcast is to educate and to inform. The content of this podcast does not constitute medical advice, and it is not intended to function as a substitute for a health care practitioner’s judgement, patient care, or treatment. The views expressed by contributors are those of the speakers. BMJ does not endorse any views or recommendations discussed or expressed on this podcast. Listeners should also be aware that professionals in the field may have different opinions. By listening to this podcast, listeners agree not to use its content as the basis for their own medical treatment or for the medical treatment of others.

Find RAPM on X @RAPMOnline, Facebook @Regional Anesthesia & Pain Medicine, and Instagram @RAPM_Online.

In this episode of RAPM Focus, Editor-in-Chief Brian Sites, MD, is thrilled to welcome Kesavan Sadacharam, MD, and Allison Fernandez, MD, following the April 2024 publication of their original research paper, “Multisite prospective study of perioperative pain management practices for anterior cruciate ligament reconstruction in adolescents: Society for Pediatric Anesthesia Improvement Network (SPAIN) Project Report.”

Unwarranted variation in health care refers to differences in health care delivery that cannot be attributed to patient illness, medical evidence, or patient preferences. Instead, these variations arise from differing local medical practices, resource availability, and physician decision-making processes. Unwarranted variations can lead to sub-optimal patient outcomes, with some patients receiving unnecessary or harmful treatments while others may not receive beneficial interventions.

Two individuals are behind a multi-center collaborative initiative that looks at the utilization of regional anesthesia and pain medicine techniques for ACL reconstruction.

Dr. Allison Fernandez is an associate professor at Johns Hopkins All Children’s Hospital, practicing pediatric anesthesia, and pediatric acute and chronic pain management. Dr. Fernandez started a video series, Women of Impact in Anesthesia, empowering women in medicine.

Dr. Kesavan Sadacharam is a pediatric anesthesiologist and associate professor at Nemours Children’s Health, located in Wilmington, DE. He is currently the director of regional anesthesia and practices both acute and chronic pain management.

*The purpose of this podcast is to educate and to inform. The content of this podcast does not constitute medical advice, and it is not intended to function as a substitute for a healthcare practitioner’s judgement, patient care, or treatment. The views expressed by contributors are those of the speakers. BMJ does not endorse any views or recommendations discussed or expressed on this podcast. Listeners should also be aware that professionals in the field may have different opinions. By listening to this podcast, listeners agree not to use its content as the basis for their own medical treatment or for the medical treatment of others.

Podcast and music produced by Dan Langa. Find us on X @RAPMOnline, Facebook @Regional Anesthesia & Pain Medicine, and Instagram @RAPM_Online.

In this episode of RAPM Focus, Editor-in-Chief Brian Sites, MD, is thrilled to welcome Laura Graham, PhD, MPH, and Sesh Mudumbai, MD, MS, following the April 2024 publication of their brief technical report, “Use of natural language processing method to identify regional anesthesia from clinical notes.”

One definition of medicine is the science and practice of the diagnosis treatment in prevention of disease. Science itself involves diagnoses and relies on the process of assessing data to determine cause and effect in therapies. However, in the busy world of clinical productivity and limited resources, the science of medicine is often overlooked.

Physicians struggle to extract meaningful data from electronic medical records, despite their great potential. This is often due to the prioritization of funding for billing and compliance, which leads to challenges in accessing meaningful data. Additionally, barriers such as data license agreements and institutional review board considerations further complicate matters. This is why Dr. Sites is excited about new technologies, such as artificial intelligence that can assist physicians in the practice in the science of medicine.

Dr. Laura Graham is an epidemiologist with VA’s Health Economics Resource Center at the VA Palo Alto Health Care System and an associate faculty with the Stanford-Surgery, Policy, Improvement Research, and Education Center at the Stanford University School of Medicine. Her research interests include causal inference methods and improving clinical processes of care for surgery. Dr. Sesh Mudumbai is an associate professor in the Department of Anesthesiology, Perioperative, and Pain Medicine at Stanford University School of Medicine and a staff anesthesiologist at the VA Palo Alto Health Care System. His research interests include using and developing informatics tools to improve opioid management and perioperative outcomes.

*The purpose of this podcast is to educate and to inform. The content of this podcast does not constitute medical advice, and it is not intended to function as a substitute for a healthcare practitioner’s judgement, patient care, or treatment. The views expressed by contributors are those of the speakers. BMJ does not endorse any views or recommendations discussed or expressed on this podcast. Listeners should also be aware that professionals in the field may have different opinions. By listening to this podcast, listeners agree not to use its content as the basis for their own medical treatment or for the medical treatment of others.

Podcast and music produced by Dan Langa. Find us on X @RAPMOnline, Facebook @Regional Anesthesia & Pain Medicine, and Instagram @RAPM_Online.