title: [Prognostic modelling and proactive intervention in psychosis: efficacy and cost-effectiveness].
abstract: Diagnoses have heterogeneous outcomes, varying from good to extremely poor. There is a need to single out an ultra-high-risk group of individuals who have illnesses that might well end unfavourably or who might later develop serious psychopathology.<br/> AIM: To devise a screening instrument that can identify a group of individuals who run a very high risk of developing a first-episode psychosis, and to create a type of intervention that can modify the course of the illness.<br/> METHOD: We developed a short screening instrument (PQ-16) and were able to ascertain its predictive value. We also tested an intervention that could influence risk factors and deal with emerging symptoms thereby achieving a better outcome for the patient.<br/> RESULTS: We developed a two-step detection instrument with a positive predictive value of 44%. The intervention, involving cognitive behavioural therapy for ultra-high-risk patients, was effective and led to a risk reduction of about 50%. Using the ultra-high-risk group of patients, we were able to model three prognostic profiles, each carrying a 4%, 13%, and 70% risk of subsequently developing psychosis. The intervention was cost-effective, reducing the financial burden on the health care services and on society as a whole.<br/> CONCLUSION: Prognostic modelling and proactive intervention can achieve improvements in health at lower costs.
authors: M
authors: M
authors: van der Gaag
authors: H
authors: H
authors: Ising
authors: J
authors: J
authors: Lokkerbol
authors: F
authors: F
authors: Smit
mesh_terms: D015928:Cognitive Behavioral Therapy / Q000191:economics / Q000592:standards; D003362:Cost-Benefit Analysis; D017048:Health Care Costs; D006801:Humans; D011379:Prognosis; D011569:Psychiatric Status Rating Scales / Q000592:standards*; D011618:Psychotic Disorders / Q000175:diagnosis / Q000191:economics* / Q000628:therapy*; D018570:Risk Assessment; D016896:Treatment Outcome