Case Study

Determining the Effective Market

Southern Health Systems (SHS), a fictional organization, established a satellite hospital in a growing suburban area ten years ago. Since then, the hospital has become relatively successful. It has attracted adequate medical staff and gradually increased its occupancy rate. At the time it opened, SHS was not authorized to offer labor and delivery services. Now, however, a significant market for maternity services has emerged, as the population has reached a critical mass and many young families have moved into the community.
In 2019, the SHS marketing staff was instructed to assess the situation and determine the current and future potential for maternity services in the market area. Because the state requires a certificate of need to add any service, the organization needed data to make a case for adding obstetrics beds. The SHS market analysts recognized the need to identify the potential for maternity services but also to specify the effective demand.
As in any marketing research project, the analysts began by delineating the service area likely to be served by the proposed obstetrics program. Once they were satisfied that a defensible service area had been specified, the analysts profiled its population. They determined the size and characteristics of the current population and developed projections that reflected anticipated changes in size and demographic characteristics.
According to the data available, the service area had approximately 42,000 residents. Estimates purchased from a demographic data vendor projected a population of 50,000 in ten years. The SHS analysts thought this figure represented the maximum population capacity of the area because virtually all available residential land would be built up by that time. The current demographic characteristics of the population were determined and projected ten years forward. The analysts focused on data on the population’s age structure (especially the number of women in their childbearing years), marital status (unmarried suburban residents typically do not have children), and racial and ethnic composition. This last attribute was considered important given the disparities in birth rates among racial and ethnic groups in the area. The psychographic (or lifestyle) characteristics of the population were also analyzed on the grounds that people in different lifestyle clusters exhibit different attitudes toward childbearing.
The analysts also researched the insurance coverage situation of the market area. Because this information was not readily available, they had to conduct primary research. A sample survey of the area’s households revealed that 75 percent of the population was covered by some form of commercial insurance. Small portions were covered by Medicare, Medicaid, or military insurance, and a negligible number of residents were uninsured. The high level of insurance coverage was a positive finding.
Satisfied that the number of women of childbearing age was adequate (23 percent of the population compared with 19 percent countywide) and that a significant proportion of households were married couples with or without children (55 percent compared with 35 percent countywide), the analysts calculated current and anticipated levels of fertility for the population. Because detailed data were not available on the area population’s fertility patterns, known figures for a similar population were applied.
The analysts calculated a proxy estimate of the birth rate for this population (15 per 1,000 people), which turned out to be well above the county rate of 10 per 1,000. This estimate was not surprising, given that this population skewed toward women of childbearing age. The general fertility rate also was calculated to determine the fertility rate for women of childbearing age (i.e., those aged 15–44), which turned out to be lower than that for the county overall (58 per 1,000 women aged 15–44 compared with 65 per 1,000). This calculation (rather than the crude birth rate) provided a more realistic estimate of the level of fertility for this population because it adjusted for the size of the childbearing-age population.
On the basis of these figures, the analysts estimated that the population would yield almost 700 births annually by the tenth year. Thus, 700 births became the base figure for calculating the effective market for obstetrics services. This figure was subsequently adjusted for factors that were likely to affect demand for SHS’s proposed maternity services. One of the demographic factors considered was the projected growth in the number of African Americans in the service area. Given the higher fertility rate for the African American population, the anticipated number of births 10 years out was adjusted to 750. However, psychographic data indicated that the career orientation of many of the area’s women was likely to lower the potential number of births. Thus, the anticipated number of births was adjusted back down to 725.
A major consideration was the drag on potential demand represented by competition from other providers of obstetrics services. After all, this service would be new, and with the exception of existing patients of SHS facilities who might transfer their business to the satellite facility, SHS would have to cultivate a new set of obstetrics customers. Realistically, many, if not most, of the women of childbearing age in the community were likely to have existing relationships with obstetricians and gynecologists (OB-GYNs). These patients would have to be convinced to change to an OB-GYN affiliated with the new facility, or SHS would have to convince their OB-GYNs to join the staff of the new facility. Further, many potential customers would be constrained in their use of facilities by the health plans that cover their obstetrics care. Lastly, some of these potential maternity customers had already delivered children at another facility (or had otherwise positive experiences with a competing hospital) and would not be inclined to change hospitals without a good reason.
The analysts believed the combined effect of these three factors (i.e., existing provider relationships, insurance steering, and previous experience) would reduce the potential market share to approximately 50 percent of the total in the short term and that SHS would grow its market share to 60 percent over 10 years. In the best-case scenario, the analysts believed that a market share of 75 percent 80 percent was the most they could hope for, so a 60 percent share in 10 years was considered a reasonable estimate.
On the basis of adjustments necessitated by these facts, the analysts estimated that SHS would capture approximately 285 births during its first year of operation and approximately 420 births annually by the tenth year. Given that a minimum of 200 annual births was required to justify the cost of establishing the facility, the analysts concluded that the effective demand was adequate to support the proposed maternity service.

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1. Why did the market analysts have to assess the size of the market before going forward with the development of a new obstetrics service?

2. Why could the analysts not simply use the total population as the basis for determining the demand for obstetrics services?

3. To what extent might the lifestyle orientation of women in the market area influence their attitudes toward childbearing?

4. How important are the presence of other obstetrics service providers and the existing relationships between market area women and OB/ GYNs in determining the effective demand for obstetrics services?

5. What challenges do marketers face in introducing a new service to a market area, particularly a service as personal as obstetrics care?

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