Analytical Solutions to Common Healthcare Problems
This course is part of Health Information Literacy for Data Analytics.
This course cannot be purchased separately - to access the complete learning experience, graded assignments, and earn certificates, you'll need to enroll in the full Health Information Literacy for Data Analytics Specialization program. You can audit this specific course for free to explore the content, which includes access to course materials and lectures. This allows you to learn at your own pace without any financial commitment.
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What you'll learn
Develop clinical identification algorithms for healthcare data analysis
Implement risk adjustment methodologies for fair provider comparisons
Create data structures for solving complex medical problems
Master ETL processes for healthcare data integration
Apply analytical methods for fraud detection
Develop effective data dictionaries for healthcare analytics
Skills you'll gain
This course includes:
4.5 Hours PreRecorded video
4 assignments
Access on Mobile, Tablet, Desktop
FullTime access
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There are 4 modules in this course
This comprehensive course focuses on applying analytical solutions to common healthcare problems. Students learn to organize healthcare data, implement risk adjustment methodologies, and develop clinical identification algorithms. The curriculum covers essential topics including provider profiling, patient safety metrics, fraud detection, and super-utilizer analysis. Through hands-on projects, learners master ETL processes, data harmonization, and creating effective data dictionaries. The course emphasizes practical applications in healthcare quality improvement and resource optimization.
Solving the Business Problems
Module 1 · 2 Hours to complete
Algorithms and "Groupers"
Module 2 · 2 Hours to complete
ETL (Extract, Transform, and Load)
Module 3 · 2 Hours to complete
From Data to Knowledge
Module 4 · 3 Hours to complete
Fee Structure
Individual course purchase is not available - to enroll in this course with a certificate, you need to purchase the complete Professional Certificate Course. For enrollment and detailed fee structure, visit the following: Health Information Literacy for Data Analytics
Instructor
Expert in Health Informatics and Cultural Research
Brian Paciotti received a PhD in Human Ecology from the University of California, Davis. His dissertation utilized ethnographic methods and experimental economic games to explore cooperative behavior among Tanzanian ethnic groups. Following an incident where the Tanzanian government accused him of being a CIA spy, he left the country and shifted his focus to analyzing U.S. homicide data.
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Frequently asked questions
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