Interpreting Profiling Data in Behavioral Health Care for a Continuous Quality Improvement Cycle

Abstract

Six examples, drawn from the experience of a number of behavioral health care programs since 1994, illustrate how outcome data can be used to guide and test changes that will effect improvements over current practices. Example 1: Problem identification is one of the most obvious and immediate applications of outcome data relative to a quality improvement process. Data were presented at a meeting of the hospital medical staff; the data showed that one clinician had significantly poorer outcomes in treating bipolar patients. A review of the medical records for bipolar patients treated by this clinician indicated that this clinician was changing medications too rapidly, a problem that was quickly and easily corrected-with improved outcomes. Example 6: Data revealed that patients who were treated in accordance with the critical pathway showed a greater degree of improvement, even though these patients entered treatment with a 10% greater level of symptom intensity. Each example provides a sample of variability in outcomes and therefore an opportunity to study the reasons for the variability and institute changes.