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Development and Psychometric Evaluation of the Transdiagnostic Decision Tool: Matched Care for Patients with a Mental Disorder in Need of Highly Specialised Care

Abstract

Background: Early identification of patients with mental health problems in need of highly specialised care could enhance the timely provision of appropriate care and improve the clinical and cost-effectiveness of treatment strategies. Recent research on the development and psychometric evaluation of diagnosis-specific decision-support algorithms suggested that the treatment allocation of patients to highly specialised mental healthcare settings may be guided by a core set of transdiagnostic patient factors.

Aims: To develop and psychometrically evaluate a transdiagnostic decision tool to facilitate the uniform assessment of highly specialised mental healthcare need in heterogeneous patient groups.

Method: The Transdiagnostic Decision Tool was developed based on an analysis of transdiagnostic items of earlier developed diagnosis-specific decision tools. The Transdiagnostic Decision Tool was psychometrically evaluated in 505 patients with a somatic symptom disorder or post-traumatic stress disorder. Feasibility, interrater reliability, convergent validity and criterion validity were assessed. In order to evaluate convergent validity, the five-level EuroQol five-dimensional questionnaire (EQ-5D-5L) and the ICEpop CAPability measure for Adults (ICECAP-A) were administered.

Results: The six-item clinician-administered Transdiagnostic Decision Tool demonstrated excellent feasibility and acceptable interrater reliability. Spearman's rank correlations between the Transdiagnostic Decision Tool and ICECAP-A (-0.335), EQ-5D-5L index (-0.386) and EQ-5D-visual analogue scale (-0.348) supported convergent validity. The area under the curve was 0.81 and a cut-off value of ≥3 was found to represent the optimal cut-off value.

Conclusions: The Transdiagnostic Decision Tool demonstrated solid psychometric properties and showed promise as a measure for the early detection of patients in need of highly specialised mental healthcare.

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