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Acheiving Consistency Through Quality Outcomes Measurement

Outcomes management marries information technology and scientific evidence to produce a rational framework for medical decisionmaking.

It's difficult to break the outcomes management process down into a list of specific components because these factors can vary from disease to disease and setting to setting. Common features of most programs include:

At present, few if any outcomes management groups have the information technology needed to assimilate all these data sets into an expert system that facilitates unified, coherent analysis. There are simply too many variables involved, and the task of assigning appropriate values to all of them--clinical measurements, satisfaction, quality of life, direct and indirect economic costs--is daunting in itself. In addition, meaningful outcomes analysis requires adjustment of data to reflect severity of illness at baseline; for example, an older, poorer or generally less healthy than average population is bound to have fewer desirable outcomes than a younger population with few poor health habits.

The first step toward achieving consistency is to identify the most salient across-the-board measures for quality outcomes. For instance, while length of stay may be an important outcome to some payers, it's a minor consideration to many practicing doctors. The real issues, which are harder to quantify, are whether patients feel better and regain function or continue to need episodic care for preventable problems.

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