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Forecasting demand for health services is an important step in managerial decision making for all healthcare organizations. This task, which often is assumed by financial managers, first requires the compilation and examination of historical information. Although many quantitative forecasting methods exist, four common methods of forecasting are percent adjustment, 12-month moving average, trendline, and seasonalized forecast. These four methods are all based upon the organization's recent historical demand. Healthcare financial managers who want to project demand for healthcare services in their facility should understand the advantages and disadvantages of each method and then select the method that will best meet the organization's needs.
Forecasting demand for services represents the essential first step in setting a healthcare organization's future direction. As such, healthcare organizations need the best possible projections of the demand for their services.
Many quantitative forecasting methods exist. Whatever method is used, it should satisfy the following concerns:
* The necessary data should be readily available. Financial records typically represent the best source of historical data regarding utilization. The forecasting method should be able to use these data.
* Existing staff members equipped with readily available tools, such as spreadsheet software, should be able to perform the forecasting in-house.
* The forecasting method and its results should be understandable not only to financial management staff but also to those who use the results for decision making.
In addition to these concerns, a critical aspect of the forecasting process is recognizing that forecasts based on historical data represent only the starting point for demand forecasting. While in the short term, historical data provide for the best forecast, healthcare managers realize that the demand for healthcare services is dynamic. Therefore, managerial judgment must be used in terms of both internal variables (eg, changes in productivity and capacity) and external variables (eg, changes in demographics, healthcare demand patterns, technology, payment mechanisms, and competition).
Many healthcare organizations routinely make forecasts using very simple techniques, such as the percent-adjustment forecasting method. However, three other forecasting methods-12-month moving average trendline, and seasonalized forecast-can project demand on the basis of historical utilization with increasing accuracy and usefulness. Each of these techniques meets the tests of reasonableness outlined above: they use readily available data, they can be done in-house, and they...