Consider a company that manages a network of hospitals across several counties in one state. Household incomes and the cost of living are higher in urban than rural areas. The company, however, has set the same prices for pharmaceuticals and services in all of its hospitals. It has also paid the same salaries for doctors, nurses, and other professional staff throughout the state. Assumptions: We assume that both, prices and salaries are set according to the cost of living of the region they are set for.
This in mind and since prices and salaries of the hospital are equal in rural and urban areas, we assume that the management of the hospital network set prices and salaries according to the average of the living cost of rural and urban areas (= state average cost of living).
Independent of how sophisticated the averaging of cost of living was, the average will always be higher than the cost of living in rural areas and lower than the cost of living in urban areas. The supply of medical treatment, that is the capacity of a hospital, is inelastic as well as the number of positions necessary to supply the treatment.
The number of hospitals does not change. medical treatment refers to both, pharmaceuticals and services, and there combination. Deduction: The cost of living can be taken as price index, indeed is directly proportional to price. Question (a) Management has noticed that there are long waiting lists for treatment at its urban hospitals. Can you explain this problem? Supply and demand for medical treatment is shown in Fig. 1. The capacity of the hospital is fixed, that is the supply is inelastic.
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As already pointed out under the assumptions, the price for medical treatment in urban hospitals set by the management is according to the average cost of living of the state. Since we further assumed that the salaries of urban area population are according to the actual cost of living, we can also assume that the customer is willing to pay according to the higher cost of living in urban areas, hence, the price of medical treatment set by management is lower than the customer is willing to pay and leads to higher demand by the customers (see full demand curve in Fig. ).
Since the hospital capacity is fixed, the higher demand causes a waiting list as shown in Fig. 1. An opposite effect could probably be seen in rural areas, where the price for medical treatment is high compared to the cost of living and could therefore lead to a lower demand as anticipated by the management. Fig. 1: Supply and demand for medical treatment in urban hospitals.
