Understanding the Impact of Economic Evidence on Clinical Decision Making: A Discrete Choice Experiment in Cardiology  

Oleh:

Torbica, Aleksandra ; Fattore, Giovanni

Jenis: Article from Journal - ilmiah internasional
Dalam koleksi: Social Science & Medicine (www.elsevier.com/locate/sosscimed) vol. 70 no. 10 (May 2010), page 1536-1543.
Topik: Italy; Discrete Choice Experiment; Clinical Decision Making; Cost-effectiveness Analysis; Cardiology

Ketersediaan

Perpustakaan Pusat (Semanggi) Nomor Panggil: SS53 Non-tandon: 1 (dapat dipinjam: 0) Tandon: tidak ada

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The present study aims to evaluate the impact of cost-effectiveness information on clinical decision making using discrete choice experiment (DCE) methodology. Data were collected through a self-completed questionnaire administered to Italian cardiologists in June 2007 (n = 129 respondents, 1143 observations). The questionnaire asked clinicians to make choices between paired scenarios, across which three key dimensions were identified and varied: (1) quality of clinical evidence, (2) size of health gain (reduction of relative and absolute risk), and (3) economic impact (incremental cost-effectiveness ratio). A random effects probit model was used to estimate clinicians' preferences for the different dimensions, while the heterogeneity of preferences was tested in a model with interaction terms. Dominance tests were used to assess the consistency of responses. The results indicate that Italian cardiologists regard economic impact (cost-effectiveness) as an important factor in their decision making. Economic evidence is valued more highly among clinicians with a higher self-assessed level of knowledge regarding economic evaluation techniques, as well as among younger professionals (age<45). While relevant study limitations should be acknowledged, our results suggest that DCEs can be used to elicit clinicians' decision-making criteria and to inform the allocation of resources for future research in a logical manner. Italian cardiologists appear to take cost-effectiveness information into account when deciding whether to use new treatments.

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