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Extract, Map, and Analyze Clinical Data

Transform raw clinical data into actionable insights that improve patient care. This course equips healthcare data analysts with foundational skills to navigate complex healthcare data systems effectively. This Short Course was created to help data analysis professionals accomplish systematic clinical data extraction and mapping that directly supports patient outcome improvements. By completing this course, you'll be able to confidently select appropriate data elements from healthcare dictionaries, execute reliable data extraction procedures, and create clear documentation that ensures data integrity throughout your analytical pipeline. By the end of this course, you will be able to: • Identify required data elements from healthcare data dictionaries for specific clinical questions • Apply standardized procedures to extract data exports from Epic Clarity and similar clinical systems • Analyze and document source-to-target mappings with complete transparency This course is unique because it combines hands-on practice with real Epic Clarity workflows and provides practical templates used in actual healthcare analytics environments. To be successful in this project, you should have a background in basic data concepts and familiarity with healthcare terminology.
Duration 3 Months
Institution Coursera
Format Online

Eligibility Criteria

school

Academic Foundation

A recognized Bachelor’s degree or high school equivalent required for admission into Coursera.

language

Language Proficiency

English proficiency required. IELTS, TOEFL, or standard medium-of-instruction certificates accepted.

Detailed Fees Breakdown

Base Tuition Fee $190
Total Est. Investment $190

Scholarships and early-bird waivers may apply. Contact admissions for exact institutional fees.

Academic Trajectory

Program Outcome

Graduates of the Extract, Map, and Analyze Clinical Data program at Coursera are equipped with global perspectives, ready to excel in international markets and top-tier career opportunities.

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