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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.
Register For This CourseGet on the Waitlist
Next Cohort Starts
8/13 - 8/22
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Available On Demand
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“I think Phil was a great instructor- he obviously knows his stuff and he had a lot of really great content that he prepared and reviewed with us. I really appreciated how much time he spent answering questions and bringing in guest speakers for Q&A was a really awesome way to structure the class”
“I appreciated the high-level course content coupled with the guest speakers and ability to have Q&A in each session. Phil's subject matter expertise and practical examples from EHR integration challenges were helpful and illustrative.”
“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!”
“Course is excellent btw. Regretting my masters”
“Very valuable, especially for someone who is starting from claims.”
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!
“I think Phil was a great instructor- he obviously knows his stuff and he had a lot of really great content that he prepared and reviewed with us. I really appreciated how much time he spent answering questions and bringing in guest speakers for Q&A was a really awesome way to structure the class”
“I appreciated the high-level course content coupled with the guest speakers and ability to have Q&A in each session. Phil's subject matter expertise and practical examples from EHR integration challenges were helpful and illustrative.”
“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!”
“Course is excellent btw. Regretting my masters”
“Very valuable, especially for someone who is starting from claims.”
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
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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.
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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.
Course Syllabus & Schedule
Module 1
Day 1
Introduction to EHR Data
(8/13, 7-830 PM EST, Tuesday, August 13th, 2024)
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
(8/15, 7-830 PM EST, Thursday, August 15th, 2024)
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
(8/20, 7-830 PM EST, Tuesday, August 20th, 2024)
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
(8/22, 7-830 PM EST, Thursday, August 22nd, 2024)
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.