Target:
- Utilize the basic principles of descriptive epidemiology to a targeted application for health care delivery settings.
Timberline Health, an integrated delivery system serving residents in five counties in eastern Washington, is considering new opportunities to increase community awareness of the organization’s outpatient health services. As the new business development manager of hearing health services, Jack Andrews is responsible for evaluating the feasibility of marketing activities for the hearing service line and must allocate resources to promotional activities that forecast positive return on investment. One option under consideration is to sponsor the health and wellness pavilion at the Spokane County Fair. Research from comparable markets has shown
that wellness fairs are not only effective at educating communities about potential risk factors for health problems, including hearing loss, but also increasing consumer awareness of new or existing health services provided by local health organizations. These activities are essential to Timberline Health’s mission within the community.
Since little is known about the hearing status of residents in the market area, Jack enlists the services of his organization’s epidemiologist, Dr. Ruth Litchfield, to help him evaluate the potential return on investment for this marketing campaign. Dr. Litchfield incorporates several factors into her analysis. She reviews public health data on hearing loss, occupational and age distribution data for local residents, as well as a query of Timberline Health’s patient databases. Based on this research, she estimates the prevalence of hearing loss in the five-county service area at 18 percent, slightly higher than the national average (NIH, 2010). Jack receives information from the fair’s sales and marketing department to help in his calculations. Specifically, sponsorship consists of an investment of $50,000 for the design and production of promotional materials and rental of pavilion space for the duration of the twelve day fair. Data from the previous three years shows on average 250,000 people attend the fair, of which 1% visit the wellness pavilion and participate in health screening services.
If Timberline Health is to offer mobile hearing screening, the organization must invest in new portable audiology equipment. Jack receives a quotation from his supplier and estimates the total investment in new audiometers and audiometric booths at $16,000. Timberline Health will use existing diagnostic equipment to test people who have failed the initial screening (i.e. test positive for hearing loss), so it is unnecessary to invest in additional equipment for the hearing centers. Vendor specifications for the screening and diagnostic equipment are indicated in Table 1.
Table 1
Vendor equipment specifications
| Equipment | Sensitivity | Specificity |
| Portable audiology equipment for free screening | 88% | 95% |
| Clinic-based audiology equipment for follow-up diagnostic testing | 99% | 99% |
Furthermore, Jack calculates that he must provide coverage for three 6-hour shifts per day and each shift must have three audiologists to meet demand for screening tests. He anticipates hiring nine people to provide coverage for the duration of the fair. The hourly rate for audiologists is
$37.50.
People who fail the initial screening at the fair are referred to an audiologist for a diagnostic test. Jack assumes in his calculations that all people who are referred for diagnostic testing follow up with an audiologist in one of Timberline Health’s hearing centers. Initial screening tests at the fair are free; however, Timberline Health charges $57.00 for a diagnostic hearing test, which costs the organization $24.00. Using past sales data and industry metrics, Jack forecasts that of
the total number of people diagnosed with hearing loss at hearing centers only 20% will purchase hearing aids (NIH, 2010). He reviews sales and margin data from the prior year to identify the product mix for his calculations as indicated in Table 2.
Table 2
Sales and margin data
| Hearing Aids | Unit Price | 2015 Sales | Margin |
| Low-end | $1,000 | $400,000 | 24% |
| Mid-range | $2,500 | $1,250,000 | 46% |
| High-end | $4,000 | $400,000 | 60% |
Reference
National Institutes of Health (NIH) (2010, October 1). Fact Sheet: Hearing aids. Retrieved from
U.S. Department of Health and Human Services: National Institutes of Health:
Write a Memorandum (no more than 2 pages) addressed to your faculty on the Subject of: Statistical Data representation in the Timberline Health case study
1. Construct a 2-by2 contingency table to determine the total number of people who fail the screening test and will be referred for diagnostic testing in the hearing centers.
2. Construct a 2-by-2 contingency table to determine the total number of people who fail the diagnostic test, which represents the target market for hearing aid sales.
***For each table: list what data (and calculations) you used for the table
3. Explain the significance of Sensitivity and Specificity of Portable audiology equipment and Clinic-based audiology equipment.
4. Explain why Sensitivity and Specificity for the Clinic-based audiology equipment for follow-up diagnostic testing is higher than for
Portable audiology equipment for a free screening.
**When appropriate, refer to credible resources following APA format.
Note:
There is an underlying assumption in this case that the screening and diagnostic tests are independent, such that the first test does not affect the results of the second test even though this is generally not true with a series of tests. The resulting cohort of people who test positive for hearing loss represents the target market or total number of prospects for hearing aid sales from the proposed marketing campaign
As a guideline, a 2-by-2 contingency table is constructed in Table TN-1:
Table TN-1
Contingency table construction
Test result Disease (D) No Disease (NoD) Total
| Positive Negative | (a) True Positive | (b) False Positive | (a + b) (c + d) |
| (c) False Negative | (d) True Negative |
Total (a+c) (b+d) (a+b+c+d)
(prevalence) (1 – prevalence)
