EHR Data 101

Hands on, practical introduction to working with data from electronic health record (EHR) systems. Learn practical strategies to extract useful insights and knowledge from messy and fragmented EHR data.

Understand and utilize EHR data

Join us for four live sessions where we'll cover how EHR data is created, what it’s used for, and how to overcome common challenges and pitfalls to understand and utilize this type of data. Lectures, live guest speakers, and hands-on activities will give you pragmatic and actionable strategies to derive knowledge and insights from the data while building a strong contextual foundation.
Renan Campos
This course helped me think more critically about the strategy behind key projects, and I'm confident that the insights and practical takeaways will accelerate our progress. Phil's availability to answer questions and even take time to connect outside the sessions was incredibly valuable!
David Roberts
I took this course with my teammates to prepare for an upcoming project. Phil and the guest speakers had practical tips, a thorough bibliography, and colorful anecdotes to make the key lessons stick. I'm a huge fan of these targeted micro-courses
Alex Bohl
A belated thank you to Phil Ballentine, MSc for an engaging, highly informative EMR 101 course. I highly recommend this course to anyone considering EMR data for any use case, spanning quality measures, value-based care, real-world evidence. I hope that Nikhil Krishnan and Out-Of-Pocket run this course again soon!
Renan Campos
This course helped me think more critically about the strategy behind key projects, and I'm confident that the insights and practical takeaways will accelerate our progress. Phil's availability to answer questions and even take time to connect outside the sessions was incredibly valuable!
David Roberts
I took this course with my teammates to prepare for an upcoming project. Phil and the guest speakers had practical tips, a thorough bibliography, and colorful anecdotes to make the key lessons stick. I'm a huge fan of these targeted micro-courses
Alex Bohl
A belated thank you to Phil Ballentine, MSc for an engaging, highly informative EMR 101 course. I highly recommend this course to anyone considering EMR data for any use case, spanning quality measures, value-based care, real-world evidence. I hope that Nikhil Krishnan and Out-Of-Pocket run this course again soon!
Renan Campos
This course helped me think more critically about the strategy behind key projects, and I'm confident that the insights and practical takeaways will accelerate our progress. Phil's availability to answer questions and even take time to connect outside the sessions was incredibly valuable!
David Roberts
I took this course with my teammates to prepare for an upcoming project. Phil and the guest speakers had practical tips, a thorough bibliography, and colorful anecdotes to make the key lessons stick. I'm a huge fan of these targeted micro-courses
Alex Bohl
A belated thank you to Phil Ballentine, MSc for an engaging, highly informative EMR 101 course. I highly recommend this course to anyone considering EMR data for any use case, spanning quality measures, value-based care, real-world evidence. I hope that Nikhil Krishnan and Out-Of-Pocket run this course again soon!

Things You'll Get From This Course

Context on EHR Systems

Acquire a strong foundation for understanding what EHRs do well, what they’re focused on, and why the data they produce can be difficult to use
1

Common Pitfalls and ‘Tar Pits’

Hear from expert practitioners on the challenges that complicate analytics work on EHR data and strategies to mitigate them.
2

Live Guest Speakers

Live appearances from guest speakers with diverse and nuanced perspectives on working with EHR data.
3

Curated Readings and Recorded Content

video content from more practitioners in the field and a curated group of readings that provide additional context.
4

Meet Your Instructor, Phil Ballentine

Phil Ballentine is a clinical data engineer with ~10 years of experience working with EHRs and making use of messy EHR data and currently leads data engineering at Atropos Health, the developer of the first physician consultation service powered by publication-grade real-world evidence derived from EHR data and claims. After working for three years as an Epic implementer transitioning Partners HealthCare (now Mass General Brigham) to Epic, Phil has worked in healthcare data integration and focusing on EHR data since 2017, including at athenahealth, OM1 Inc, and Health Catalyst. Phil holds a MSc in Health Informatics and Analytics from the Tufts University School of Medicine and created and teaches a graduate course at Northeastern University on healthcare data.

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Course Syllabus & Schedule

Module 1

Day 1

Introduction to EHR Data

(1/28, 7-830 PM EST)

We will provide an overview of Electronic Health Record (EHR) systems and discuss their strengths and weaknesses in collecting various data elements for primary and secondary use. This will include common ‘meta-problems’ and EHR data tar pits, which are frequently encountered issues with EHR data and paths that seem promising but usually lead to nowhere.

Module 2

Day 2

Deep Dives I: Core Domains

(1/30, 7-830 PM EST)

This section will address common challenges in utilizing demographic, procedure, and diagnosis data within EHRs, including the differentiation between ordered and performed procedures, and different types of diagnosis records.

Module 3

Day 3

Deep Dives II: Labs, Meds, and More

(2/04, 7-830 PM EST)

This session, we’ll tackle laboratory result data, focusing on the challenges of mapping laboratory results to standard codes (LOINC), as well as medication and immunization data within EHRs. We’ll cover different coding systems, challenges frequently encountered and ways to tackle them, such as mapping free-text medication names to a standard terminology, and commonly used attributes of medications and vitals.

Module 4

Day 4

EHR Data Usage and Some Solutions

(2/06, 7-830 PM EST)

We will examine methods for de-identifying EHR data and discuss their consequences for analytics. Afterward, we will outline strategies for enhancing EHR data analysis, including the adoption of standard tooling and practices for data cleanup. We’ll also tackle how LLMs / generative AI can help us clean and normalize EHR data.

Module 5

Day 5

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Module 6

Day 6

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Module 7

Day 7

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Module 8

Day 8

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Module 9

Day 9

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Module 10

Day 10

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Frequently Asked Questions

Who is this course for?

Anyone looking to understand EHR data and the challenges of working with and extracting maximum value from it. This includes founders, data scientists, data engineers, data analysts, CTOs, engineering managers, product managers, investors, and strategy leads. 

Past attendees have included:

  • Data Engineers and Data Analysts at major healthcare data analytics companies
  • Technical staff at a large institutional research project branching into using EHR data
  • Analytics Managers at leading value-based care companies
  • Several founders and CTOs of Seed and Series A healthcare technology startups
  • Investment analysts at major PE firms

How much is it?

$1,800, which includes access to the recorded content and slides in perpetuity (~5 hours of class plus additional time with guest speakers)

Do I have to be at every session?

No.

Is there a lot of work?

No, the work outside of the course session is optional.