Clinical Research Informatics
Introduces informatics principles for clinical research, covering protocol design, regulatory compliance, patient recruitment, and health data security, storage, and analysis.
Summary
Recent recorded grades — Spring 2022: 4.00 GPA, 100.0% A/AB (n=11 letter grades); Spring 2024: 4.00 GPA, 100.0% A/AB (n=13 letter grades); Spring 2026: 3.91 GPA, 100.0% A/AB (n=11 letter grades).
What you’ll be able to do
Recognize the various types and sources of health data, and the key issues involved in processing health data including security, privacy, noise, and missingness
Conduct observational studies using data that are centered around answering research questions
Implement basic programming and data manipulation using R, and be familiar with a variety of techniques such as descriptive analysis, regression methods, prediction models, phenotyping, and natural language processing
Apply common tools for managing, accessing and mapping health data, including data standards, controlled vocabularies, and ontologies
Source: UW Guide
Grade history
↗All recorded terms · compare terms & instructors
Prerequisites
Course mapGraduate/professional standing
- Graduate/professional standing
This is a best-effort interpretation; check the catalog requirements above.
Prerequisite text tree
- Graduate/professional standing
Professors
Spring 2027No instructors recorded for this selection.
Historical instructors & teaching patterns
Recorded history may be incomplete and does not establish a future schedule.
Calendar & sections
Spring 2027Schedule loads here as you scroll.
| Section | Mode | Enrolled / capacity | Waitlist |
|---|
Times are Central. Select a meeting for details; export includes recorded dates for the selected sections.
Meeting source records
No records available.
Student experience
the class
Recent recorded grades — Spring 2022: 4.00 GPA, 100.0% A/AB (n=11 letter grades); Spring 2024: 4.00 GPA, 100.0% A/AB (n=13 letter grades); Spring 2026: 3.91 GPA, 100.0% A/AB (n=11 letter grades).
difficulty & workload
No workload feedback recorded.
Topics
- Clinical protocol design, regulatory compliance, and patient recruitment
- Health data collection, security, storage, transfer, processing, and analysis
- R programming, statistical methods, prediction models, phenotyping, and NLP
- Health data standards, controlled vocabularies, and ontologies
Skills
- Protocol design, regulatory compliance, patient recruitment, and protocol management
- Basic programming and data manipulation in R, including descriptive analysis, regression, prediction models, phenotyping, and NLP
- Managing, accessing, and mapping health data using standards, controlled vocabularies, and ontologies
- Identifying health data types/sources and addressing security, privacy, noise, and missingness in processing
Grades
Latest available · Spring 2026— not enough history to project Spring 2027.
Grade distribution · % of letter grades
Grades over time
Through Spring 2026
More grade details Grade mix, volume & source data
Not enough comparable courses for Spring 2027 in UW–Madison.
Sources & history
Catalog & offerings
Descriptions, prerequisites, and recorded course offerings.
Catalog observation history
Observations at scan time; dates do not imply when a catalog change took effect.
Selected offering source records
No offering records for the selected term.
Raw records
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Student reviews
Original comments behind the course and instructor summaries.
Read original reviews
No records available.
Grade history
Recorded grade distributions by term, section, and instructor.
Explore recorded gradesRecorded 2026-10-14
Model outputs & technical records
LLM outputs across runs
Full model traces
Recorded model configuration, reasoning, and tool conversations.
Model & dataset provenance
{
"model": "Qwen/Qwen3.8-27B",
"model_revision": "1d4bf0f2ff6012fd82039f2fa52739d0dd7c60c0",
"task_version": "17",
"output_id": "ed79755245c50223f7fab5eced7278b6113bfec8e3489e354f9aaf4eceb3f47b",
"requirements_status": "valid",
"dataset_revision": "fc1811fa52e581ea57a35c0cf3343f8740a8ffbf",
"observed_at": "2026-10-14 17:50:09.728220+00:00"
}