Case Study: “The Greenwood Asthma Spike—Understanding Measures of Disease and Epidemiologic Methods”
Aligned to Chapters 6 & 7
Scenario
The community of Greenwood County (population 142,000) has seen a reported rise in asthma-related emergency department (ED) visits over the last 18 months. Two healthcare systems—St. Helena Medical Center and Greenwood Regional Hospital—serve the area and have contributed encounter data to the county public health department.
You are part of a joint analytic team assigned to determine whether the apparent increase represents:
- A true rise in asthma incidence
- A reporting artifact
- A change in healthcare-seeking behavior
- A result of environmental shifts
- Or a combination of these factors
Available Data
Past Year:
- 2,842 asthma-related ED visits
- Of these visits, 1,118 are repeat visits within the same year
- County population: 142,000
- Estimated number of individuals with physician-diagnosed asthma: 15,400
- Number of newly diagnosed asthma cases recorded this year: 410
Environmental data:
- Air quality index (AQI) exceeded 100 on 37 days (previous year: 14 days)
- Two schools report increased mold concerns following water damage
- New industrial activity began in the east corridor 20 months ago
Healthcare data:
- Improved EHR documentation implemented at both hospitals
- Two urgent care centers closed, shifting non-urgent cases to EDs
- School nurse reports indicate rising inhaler use among middle school students
Student Tasks (4–5 pages)
1. Calculate Key Measures of Disease (Ch. 6)
Using the provided data:
- Calculate incidence of asthma in Greenwood County.
- Calculate prevalence of asthma.
- Explain the difference in interpretation of incidence vs. prevalence in this scenario.
- Determine whether ED visit counts reflect disease burden accurately.
2. Evaluate Potential Biases and Errors (Ch. 7)
Discuss how the following may influence observed trends:
- Improved EHR documentation
- Closure of urgent care centers
- Repeat visits inflating counts
- Potential misclassification
Explain how each could bias either incidence or prevalence.
3. Interpret Environmental and Demographic Clues
Analyze whether environmental patterns (AQI, mold exposure, industrial activity) could represent:
- A true increase in incidence
- A non-causal correlation
- A confounder
- An effect modifier
4. Develop an Analytic Epidemiology Plan
Propose a study design (cohort, case-control, cross-sectional) to test the hypothesis that air quality changes are contributing to the increase in asthma cases.
Explain:
- Why you chose that study design
- What data you would collect
- How you would measure exposure
- How you would reduce confounding
5. Identify the Next Steps for Public Health Action
Recommend three immediate actions the county health department should take based on your findings and interpretation.
