Nov Meetup: Exploring Healthcare Data

About this event

Join PyData Boston on a deep dive into the use of healthcare data!

Do not arrive before 6:30pm! 📅 Schedule: 6:30–7:00 — Networking (doors open) 7:00–7:10 — Introduction 7:10–7:55 — Preet Mehta - Data Design Practices for EHR Data 7:55–8:30 - Break 8:30-9:15 - Dany Sigha - The Shape of the Break: What drives payment gaps in Medicare 9:30 — End

* **IMPORTANT*** You MUST fill out the registration form accurately in order to get access to the venue. No guests/drop-ins, all unregistered folks WILL be turned away

Preet Mehta Title: Data Design Practices for EHR Data Description: Healthcare data is messy by nature: patients, encounters, observations, and claims arrive from multiple EHR systems, each with its own schemas, coding practices (ICD, CPT, NDC), and data quirks. Before any model or dashboard can be trusted, the underlying data has to earn that trust. In this talk, I will walk through practical data design patterns for healthcare data: using the bronze/silver/gold medallion pattern as a trust framework, standardizing records from multiple EMRs into a single patient view, building metadata-driven pipelines that scale, and handling schema evolution, privacy, and auditability along the way. Bio: Preet Mehta is a Manager of Healthcare Analytics at EXL Service, with 10 years in data engineering and 6 years in healthcare data. He leads a team building a unified data platform and machine learning models for large US healthcare firms.

Dany Sigha Title: The Shape of the Break: What drives payment gaps in Medicare Description: Using 2023 CMS data on 37,000+ Massachusetts providers, this talk walks through a statistical deep-dive into what drives payment gaps between Medicare allowed amounts and actual payments. We explore how provider specialty, dual-eligibility rates, and provider volume shape payment outcomes, with some counterintuitive findings. Bio: Dany Sigha is a software engineer based in Boston, currently completing his M.S. in Software Engineering Systems at Northeastern University. His work spans backend engineering, AI-driven applications, and data analysis

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