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Published on: May 15, 2020
Measurement Based Care in a first episode psychosis program: Development of an algorithm of care based on the
Michelle Khau1, Karim Tabbane2, David Bloom3
1Integrated Program of Neuroscience, McGill University, Montreal, Qc, Canada; Douglas Mental Health University Institute, Verdun, Qc, Canada.
Introduction:
Adherence to therapeutic guidelines in psychiatry is anchored and facilitated by rating scales. However, they are rarely used in routine care, particularly for psychotic disorders. Consequently, adherence to treatment guidelines are not ideal and patient outcomes are often sub-optimal. In this study, we used the clinician-rated Clinical Global Impressions Scale (CGI) to implement a measurement-based care (MBC) approach and derive indices of quality of care at a first episode psychosis (FEP) program.
Methods:
At the individual level, an algorithm was created using CGI scores and their changes over time to define the concept of Patient Requiring Clinical Attention (PRCA) that encompasses several categories (e.g. episode of severity, treatment inertia, or treatment resistance). At the service level, CGI scores were used to derive several indices of quality of care: severity of illness and its change over time, conformity to the use of low doses of antipsychotic medications, and clozapine offer index.
Results:
135 Patients were included in this study of whom 19 patients were identified as PRCA. Of these, 12 (63%) received timely medication, and 7 (37%) were suspected cases of therapeutic inertia. Additionally, 15 patients met criteria for treatment resistance of whom 7 were offered clozapine (47%). At the service level, the average CGI improved by 2 points from baseline to month 1 and average doses of antipsychotic medications prescribed were in line with prescription guidelines for FEP patients.
Conclusion:
The proposed CGI-based treatment algorithm and service evaluation strategy can help to optimize quality care and services for patients.
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