Comparison of empirically-derived and rationally-derived methods for identifying patients at risk for treatment failure
Version of Record online: 8 MAY 2002
Copyright © 2002 John Wiley & Sons, Ltd.
Clinical Psychology & Psychotherapy
Volume 9, Issue 3, pages 149–164, May/June 2002
How to Cite
Lambert, M. J., Whipple, J. L., Bishop, M. J., Vermeersch, D. A., Gray, G. V. and Finch, A. E. (2002), Comparison of empirically-derived and rationally-derived methods for identifying patients at risk for treatment failure. Clin. Psychol. Psychother., 9: 149–164. doi: 10.1002/cpp.333
- Issue online: 17 MAY 2002
- Version of Record online: 8 MAY 2002
- Brigham Young University, UT, USA.
Several systems have been developed to monitor and feedback information about a patient's responses to psychotherapy as a method of enhancing patient outcome. Feedback is generated from decision rules based on a patient's expected level of progress. Those patients who do not make expected levels of progress or whose progress in therapy is less than adequate are referred to as signal–alarm cases. Research has shown that feedback based on rationally-derived identification procedures increased the duration of treatment and improved outcomes for patients identified as potential treatment failures (signal–alarms). This paper compared two identification methods: a rationally-derived method based on clinical judgments about poor progress, and an empirical method based on statistically-derived expected recovery curves. The concordance of these two methods was examined with regards to detecting signal–alarm cases. Results suggested that the empirically-derived method was more accurate in identifying patients who actually deteriorated. It was able to identify 100% of the cases that had deteriorated at termination, with 85% being identified by the time they had had three treatment sessions. However, the rationally-derived method was faster at identifying signal cases and more likely to identify the most seriously disturbed cases as potential treatment failures. Future directions for research in quality management were identified. Copyright © 2002 John Wiley & Sons, Ltd.