UCLA

Measurement feedback systems (MFSs) can help improve clinical outcomes by enhancing clinical decision-making. Unfortunately, limited information exists to guide the use and interpretation of data from MFSs. This study examined the amount of data that would provide a reasonable and reliable prediction of a client's rate of symptomatology in order to help inform clinical decision-making processes. Results showed that use of more data predicted greater levels of accuracy. However, there were diminishing returns on the ability for additional data to improve predictive accuracy. Findings inform efforts to develop guidelines on the interpretation of data from MFSs.