Clinical decision making and mental health service use in people with severe mental illness across Europe

Autor: Cosh, Suzanne, Zentner, Nadja, Ay, Esra-Sultan, Loos, Sabine, Slade, Mike, De Rosa, Corrado, Luciano, Mario, Berecz, Roland, Glaub, Theodora, Krogsgaard Bording, Malene, Kawohl, Wolfram, Puschner, Bernd
Jazyk: angličtina
Rok vydání: 2017
Předmět:
ISSN: 1075-2730
1557-9700
Popis: Objective: This study aims to explore relationships between preferred and experienced clinical decision making with service use, and associated costs, by people with severe mental illness.Methods: Prospective observational study of mental healthcare in six European countries: Germany, UK, Italy Hungary, Denmark and Switzerland. Patients (N = 588) and treating clinicians (N = 213) reported preferred and experienced decision making at baseline using the Clinical Decision Making Style Scale (CDMS) and the Clinical Decision Involvement and Satisfaction Scale (CDIS). Retrospective service use was assessed with the Client Socio-Demographic and Service Receipt Inventory (CSSRI-EU) at baseline and 12-month follow-up. Negative binomial regression analyses examined the effects of CDMS and CDIS on service use and inpatient costs at baseline and multilevel models examined these relationships over time.Results: At baseline, staff and patient preferences for active decision making and low patient satisfaction with experienced decisions were associated with longer hospital admissions and higher costs. Patient preferences for active decision making predicted increases in hospital admissions (b = .236, p =.043) over 12 months and cost increases were predicted by low patient satisfaction (b = 4803, p =.005). Decision making was unrelated to medication, outpatient, or community service use.Conclusions: Decision making is related to inpatient service use and associated costs by people with severe mental illness. A preference for shared decision making may reduce healthcare costs via a reduction in inpatient admissions. Patient satisfaction with decisions is a crucial predictor of healthcare costs; therefore, clinicians should maximize patient satisfaction with decision making.
Databáze: OpenAIRE
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