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In recent years, there has been an increase in studies that have sought to identify predictors of treatment outcome and to examine the efficacy of surgical and non-surgical treatments. In addition to the scientific advancement associated with these studies per se, the hospitals and clinics where the studies are conducted may gain indirect financial benefit from participating in such projects as a result of the prestige derived from corporate social responsibility, a reputational lever used to reward such institutions. It is known that there is a positive association between corporate social performance and corporate financial performance. However, in addition to this, the research findings and the research staff can constitute resources from which the provider can reap a more direct benefit, by means of their contribution to quality control and improvement. Poor quality is costly. Patient satisfaction increases the chances that the patient will be a promoter of the provider to friends and colleagues. As such, involvement of the research staff in the improvement of the quality of care can ultimately result in economic revenue for the provider. The most advanced methodologies for continuous quality improvement (e.g., six-sigma) are data-driven and use statistical tools similar to those utilized in the traditional research setting. Given that these methods rely on the application of the scientific process to quality improvement, researchers have the adequate skills and mind-set to embrace them and thereby contribute effectively to the quality team. The aim of this article is to demonstrate by means of real-life examples how to utilize the findings of outcome studies for quality management in a manner similar to that used in the business community. It also aims to stimulate research groups to better understand that, by adopting a different perspective, their studies can be an additional resource for the healthcare provider. The change in perspective should stimulate researchers to go beyond the traditional studies examining predictors of treatment outcome and to see things instead in terms of the "bigger picture", i.e., the improvement of the process outcome, the quality of the service.

Money matters: exploiting the data from outcomes research for quality improvement initiatives