Health Disparities Research: Histories, Practices, and Methods

Examines social and historical roots of health disparities and current methodologies, focusing on landmark NIH research, grant proposal writing, and drafting NIH Aims pages.

offering recorded2 credits
Recorded instructors · Spring 2027 Dana Landress3.8/5

Summary

What you’ll be able to do

  • Identify, analyze, and interpret historical structures underwriting health disparities across the 20th century United States and explain their significance to contemporary health outcomes.

  • Explain the origin and development of health disparities research frameworks and conceptualizations; and provide key examples of landmark studies that have successfully utilized these research frameworks.

  • Identify and analyze relevant literature pertaining to health disparities research and conceptualize potential research ideas that meaningfully engage with this literature.

  • Develop 2-3 health disparities research questions, grounded in rigorous health disparities research-specific methods, analytics, and practices; and articulate these questions in both written and oral formats.

  • Develop collaborative research and grant writing skills through sustained consultation with faculty instructors and peer grant writing workshops to culminate in a draft grant proposal aims page with post-submission faculty feedback.

  • Position research question within relevant field literature to an audience of course peers, instructors, and visiting SMPH guest lecturers to solicit preliminary feedback on grant proposal aims page.

  • Facilitate future collaborative research endeavors through presentation opportunities in collaboration with faculty instructors and the Center for Health Disparities Research (CHDR).

Source: UW Guide

Grade history

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Prerequisites

Course map

Declared in Medicine MD or Population Health Sciences PhD

  • Declared in Medicine MD or Population Health Sciences PhD
MEDHIST 724

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  • Declared in Medicine MD or Population Health Sciences PhD

Professors

Spring 2027
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About this rating

Raw average: 5.00/5 from 2 quality ratings. The adjusted rating blends this with the UW review average (3.66/5), weighted as 20 additional ratings. Smaller samples stay closer to that average. Each captured review is counted once in the prior; this does not correct who chooses to leave a review.

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Historical instructors & teaching patterns

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Calendar & sections

Spring 2027

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SectionModeEnrolled / capacityWaitlist
SEM 001Online Only0 / 00

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Student experience

the class

Examination of the social and historical roots of health disparities, including histories, practices, and current methodologies informing contemporary health disparities research. Participate in or explore content such as reviewing case studies pertaining to landmark research with priority populations identified by the National Institutes of Health (NIH); engage with leading scholars from across the School of Medicine and Public Health; grant proposal writing, presentation of student-led research; prepare drafts of NIH Aims page.

difficulty & workload

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Topics

  • Social and historical roots of health disparities in the 20th-century US
  • Landmark NIH research and health disparities frameworks
  • Grant proposal writing and NIH Aims page development

Skills

  • Grant proposal writing and drafting NIH Aims pages
  • Analyzing landmark studies and health disparities research frameworks
  • Formulating and articulating health disparities research questions

Grades

Instructor

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Sources & history

UW–Madison

Catalog & offerings

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MEDHIST 724 · Spring 2027

Health Disparities Research: Histories, Practices, and Methods

Recorded 2026-10-29
Raw records
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    "course_id": "MEDHIST 724",
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    "term_id": "1274",
    "source_course_id": "027170",
    "source_subject_id": "452",
    "title": "Health Disparities Research: Histories, Practices, and Methods",
    "credits_min": 2,
    "credits_max": 2,
    "typically_offered": "Not Applicable"
  }
]
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Model outputs & technical records
Qwen/Qwen3.8-27B
LLM outputs across runs
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Model & dataset provenance
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