Pragmatic implementation of the Clinical Global Impression Scale of Severity as a tool for measurement-based care in a first-episode psychosis program.

Introduction: Measurement-based care (MBC) is an evidence-based practice wherein clinical decisions are informed by patient data collected throughout treatment. MBC has yielded superior patient outcomes compared to standard care. However, the implementation of MBC in the day-to-day practice, particularly in psychotic disorders, poses several challenges. This study evaluates the clinician-rated Clinical Global Impressions Scale of Severity (CGI-S), for MBC implementation at a first-episode psychosis program.
Methods: The CGI-S was evaluated in the context of routine care on fidelity to practice, inter-rater reliability among psychiatrists and concurrent validity with scales measuring different domains of psychopathology (SAPS, SANS, GAF, BPRS, PANSS-6).
Results: A high fidelity to practice (67%) and inter-rater reliability was found (r _wg  = 0.92). CGI-S correlations were significant and strongest with BPRS (r = 0.55; p < 0.01), GAF (r = 0.53; p < 0.01), SAPS (r = 0.52, p < 0.01), and PANSS-6 (r = 0.41; p < 0.05) scores. However, correlations with SANS and PANSS-6 Negative sub-scale were weak.
Conclusion: Findings suggest the CGI may be used to overcome important barriers towards MBC implementation within the context of first episode psychosis. However, as suggested by data, further improvements in capturing negative symptoms by rating clinicians are needed.
Twitter: A novel strategy for measurement-based care to optimize treatment for individuals with first episode psychosis and related psychotic disorders.
(Copyright © 2022. Published by Elsevier B.V.)