Today, host Rachel Stemerman sits down with two authors of a groundbreaking paper: Ira Harmon and Jennifer Fishe. Their research tackles a significant challenge in emergency medical services: accurately identifying prehospital pediatric asthma exacerbations from complex EMS data.

Asthma exacerbations are a common reason for pediatric EMS encounters. Accurately identifying these encounters is crucial for research and quality improvement in prehospital care. However, the nature of asthma symptoms and EMS data makes this difficult.

In this episode, Ira and Jennifer will discuss their study, which focused on developing computable phenotypes (CPs) – reusable computer queries that identify specific clinical events using electronic data. They evaluated existing rule-based CPs and developed new ones, including machine learning-based models, using a large dataset of pediatric EMS encounters.

Tune in to learn more about this innovative approach to leveraging EMS data for better pediatric care.

As always THANK YOU for listening.

Hawnwan Philip Moy MD (@pecpodcast)

Scott Goldberg MD, MPH (@EMS_Boston)

Jeremiah Escajeda MD, MPH (@jerescajeda)

Joelle Donofrio-Odmann DO (@PEMems)

Maia Dorsett MD PhD (@maiadorsett)

Lekshmi Kumar MD, MPH(@Gradymed1)

Greg Muller DO (@DrMuller_DO)

Ariana Weber MD (@aweberMD4)

Rebecca Cash PhD (@CashRebeccaE)

Michael Kim MD (@michaeljukim)

Rachel Stemerman PhD (@steminformatics)

Nikolai Arendovich MD

Episode 151 Deep Dive: Decoding Pediatric Asthma in EMS Data

Prehospital Emergency Care Podcast

Episode 151 Deep Dive: Decoding Pediatric Asthma in EMS Data