Richard J. Schuster, MD, FACP Associate Professor of Clinical Medicine Wright State University School of Medicine Medical Director Sycamore Primary Care Center Dayton, Ohio		Marianne L. Weber, AIA, NCARB Vice President E. Lynn App Architects, Inc. Englewood, Ohio

In today's consumer-driven healthcare market, proactive consumers are demanding convenience as well as quality. How an organization delivers service is becoming as important as the clinical quality (Anderson 1991). As healthcare organizations come to accept this reality, it is becoming apparent that they must arm themselves with improved skills and resources in order to meet these demands. "Mouthing slogans like 'the consumer is king' is easy, but revamping your business to make it customer centered takes more than platitudes . . . " (Appleby 1996). One area of knowledge and skill that is proving useful with regard to quality of service and design is that of management science.

Management science is a field that melds portions of business, economics, statistics, mathematics, and other disciplines in a pragmatic effort to help managers make optimal decisions (Lapin 1994). Whenever an evaluation of hard data can be helpful in reaching a decision, quantitative methods are used to assist managers in selecting the best alternative course of action that will help them in the pursuit of such organizational goals as cost-effectiveness, quality service delivery, and profit.

While good managers are often able to intuitively make reasonable decisions, intuition alone is not always sufficient for selling an "idea" to one's organization. It usually takes established precedents or hard data to influence those with authority. Applying the appropriate quantitative analytical tool to a given problem can produce the hard data needed to influence decision making.

What Are Quantitative Methods?
For healthcare managers and designers, two particular quantitative methods, queuing theory and simulation, have applications that can direct decision outcomes so as to maximize customer satisfaction and produce the optimum design, both of which directly impact profitability.

Queuing theory is one of the earliest quantitative methods, originating in a 1909 paper by A. K. Erlang, a Danish telephone engineer. The objective is to determine how to provide service to customers in such a way that an efficient operation is achieved. Retail businesses have historically utilized queuing theory successfully to determine how best to design delivery of service methods that will decrease waiting times and in turn improve customer satisfaction. An analysis of significant data can determine various characteristics of the queuing system such as mean waiting time, components of the waiting time, and the mean length of the waiting line. This information can be simply acquired and easily analyzed with readily available spreadsheet software, and then used to construct a cost analysis or determine how to achieve a targeted level of satisfactory customer service. (Lapin 1994)

Simulation is a quantitative procedure that describes a process; a series of organized trial-and-error experiments are then conducted to predict the behavior of the process in operation. Simulation helps to predict the issues resulting from the variation that occurs day to day in the process due to random chance. These simulations seek to duplicate reality as closely as possible within practical limits. Consequently, those issues identified can be addressed during planning activities with decisions being based on realistic data. Given that simulations are often conducted via the computer, a number of alternative operating policies can easily be modeled such that the optimum situation can be identified (Lapin 1994).