Overview
What this challenge is about.
Design an Electronic Health Record Data-Quality Audit. Advanced challenge in analysis. Analyzing real datasets and building models that drive decisions, earn...
The Brief
What you'll do, and what you'll demonstrate.
Audit 14M de-identified EHR records across completeness, consistency, plausibility, and temporal correctness, and publish a severity-ranked report with remediation guidance.
This is not a data exercise. It is the work an analyst does when stakeholders need answers from messy data. That distinction matters to every hiring manager who has seen candidates describe statistical methods and none who have extracted insight from messy, real-world data.
When you finish, you will have something most graduates do not: a real-world deliverable, verified by Ewance, that you can show to a hiring manager and say "I did this. Here is the proof."
Earning criteria — what you'll demonstrate
- Design data-quality checks across multiple dimensions on real EHR data
- Map free-text clinical fields against SNOMED CT codings
- Communicate data-quality findings to a non-engineering audience
- Make scientific audits reproducible without leaking patient identifiers
Program Fit
Where this fits in your program.
Sharpens the same skills your degree expects you to demonstrate.
Computational Biology and Health Informatics
Master · General Studies
Strong alignment
This challenge maps to Computational Biology and Health Informatics at the Master level. It sharpens the same practical skills your coursework expects — but in a real industry context with actual constraints and deliverables.
Skills
Skills you'll demonstrate.
Each one shows up on your verified credential.
- Health Informatics
Apply health informatics to solve real industry problems and demonstrate production-level capability.
- Data Quality
Apply data quality to solve real industry problems and demonstrate production-level capability.
- Snomed Ct
Apply snomed ct to solve real industry problems and demonstrate production-level capability.
- Exploratory Data Analysis
Apply exploratory data analysis to solve real industry problems and demonstrate production-level capability.
- Python
Write clean, efficient Python for data processing, automation, and backend services.
- Reproducibility
Apply reproducibility to solve real industry problems and demonstrate production-level capability.
Careers
Career paths this challenge builds toward
Completing this challenge demonstrates skills that transfer directly to these roles:
Product Manager
Product managers in HealthTech who understand EHR data-quality realities ship realistic roadmaps instead of demos that break on day-one production data.
This challenge sharpens
- health-informatics
- data-quality
- snomed-ct