Developing a decision tool to identify patients with personality disorders in need of highly specialized care

  • M. Goorden (Erasmus School of Health Policy and Management (ESHPM) (Contributor)
  • E.M.C. Willemsen (PsyQ, Department of Personality Disorders) (Contributor)
  • C.A.M. Bouwmans-Frijters (Erasmus University Rotterdam) (Contributor)
  • Jan van Busschbach (Contributor)
  • Marc J. Noom (Contributor)
  • der Feltz-Cornelis C.M. van der Feltz-Cornelis (Mind and Health Academic Psychiatry Department, Tilburg University) (Contributor)
  • Carin de Groot (Contributor)
  • Leona Hakkaart - van Roijen (Contributor)

Dataset

Description

Abstract Background Current guidelines recommend referral to highly specialized care for patients with severe personality disorders. However, criteria for allocation to highly specialized care are not clearly defined. The aim of the present study was to develop a decision tool that can support clinicians to identify patients with a personality disorder in need of highly specialized care. Methods Steps taken to develop a decision tool were a literature search, concept mapping, a meeting with experts and a validation study. Results The concept mapping method resulted in six criteria for the decision tool. The model used in concept mapping provided a good fit (stress value = 0.30) and reasonable reliability (ρ = 0.49). The bridging values were low, indicating homogeneity. The decision tool was subsequently validated by enrolling 368 patients from seven centers. A multilevel model with a Receiver Operating Characteristic Curve (ROC) was applied. In this way, an easily implementable decision tool with relatively high sensitivity (0.74) and specificity (0.69) was developed. Conclusions A decision tool to identify patients with personality disorders for highly specialized care was developed using advanced methods to combine the input of experts with currently available scientific knowledge. The tool appeared to be able to accurately identify this group of patients. Clinicians can use this decision tool to identify patients who are in need of highly specialized treatment.
Date made available2017

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