A program of research aimed at improving the quality of psychological interventions is described. Data from over 10,000 patients were analyzed to understand the association between number of treatment sessions and clinically significant improvement. In addition to a potential dose-response relationship, typical recovery curves were generated for patients at varying levels of disturbance and were used to identify patients whose progress was less than expected ("signal" cases). The consequences of passing this information along to therapists were reported. Analyses of dose-response data showed that 50% of patients required 21 sessions of treatment before they met criteria for clinically significant improvement. Seventy-five percent of patients were predicted to improve only after receiving more than 40 treatment sessions in conjunction with other routine contacts, including medication in some cases. Identification of signal cases (potential treatment failures) shows promise as a decision support tool, although further research is needed to elucidate the nature of helpful feedback. Outgrowths of this research include its possible contribution to social policy decisions, reductions in the need for case management, use in supervision, and possible effects on theories of change.
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 statisticallyderived 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.
Brief Therapy CenterA method of assessing outcome after psychotherapy in private practice or clinics is described. Use of this system is illustrated by reference to the progress and rate of recovery of 27 patients seen by a private practice clinician in comparison with base rates from a prior study. The results suggested more rapid recovery in the patients treated by an experienced clinician committed to a brief, solutionfocused psychotherapy. The methodology reported, based on weekly assessment of patient progress and the use of clinical significance markers, has implications for routine clinical practice as well as for managed health care practices and social policy decisions.Clinicians have remained rather skeptical about the relevance and value of psychotherapy process and outcome research, looking elsewhere for guidance in directing their clinical practice (Talley, Strupp, & Butler, 1994). Although there is a rich database supporting the efficacy of many psychotherapies (summarized by Lambert & Bergin, 1994), health delivery providers in general, and psychotherapists in particular, are being challenged to document the outcome of the treatments they provide to given patients. Much of this documentation is focused on demonstrating that more expensive, time-intensive treatments produce better outcomes than less expensive interventions. Andrews (1995) has argued that the push for outcome research is a worldwide phenomenon independent of any specific payment system. It appears that psychotherapists will be involved in outcome assessment either by choice or by default. Professional psychologists are seemingly well suited to the task of being practitioner-scientists and using outcome assessment to the advantage of their patients.Outcome assessment has a long history, dating back to the 1930s (see Lambert, 1983, for a review). Early efforts at outcome assessment represented by small, well-controlled studies were driven by psychological theories and scientific considera-
The results of the development of expected recovery curves for an empirically driven patient profiling system are presented. Patients undergoing a course of psychotherapy (N = 11 492) repeatedly took the Outcome Questionnaire-45 (OQ-45). Scores across all patients were combined into an aggregate dataset for use in generating expected recovery curves based on severity of symptoms at intake. SAS PROC MIXED was used to create a mixed linear model of recovery curves based on OQ-45 scores across sessions and the log transformation of session number. Mean estimates were established for each session from one to 20. Tolerance intervals were then created around each estimated mean score. Expected recovery curves were combined with tolerance intervals to create an early warning system capable of identifying patients whose slow progress suggests that they might be expected to have a negative therapy outcome (terminate treatment prior to obtaining a clinically significant benefit). Current efforts to establish a systematic quality improvement procedure using these curves are discussed. Charts of expected recovery values are plotted, and a straightforward system of patient profiling, early identification of treatment failures, and feedback to clinicians is described.
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