OBJECTIVES: The aim of this study is to explain factors influential to the diffusion of computed tomography (CTs) and magnetic resonance imaging (MRIs). METHODS: Variables were identified from a review of the literature on the diffusion of health technologies. A formal process was applied to build a conceptual model of the mechanism that drives technology diffusion. Variables for the analysis were classified as predisposing, enabling, or reinforcing factors, in keeping with a model commonly used to explain the diffusion of health behaviors. Multiple regression analysis was conducted using year 2000 OECD data. RESULTS: The results of this study showed that total health expenditure per capita (p < .01, both CTs and MRIs) and flexible payment methods to hospitals (p < .05, both CTs and MRIs) were significantly associated with the diffusion of CTs and MRIs (adjusted R2 = 0.477, 0.656, respectively). CONCLUSIONS: This study presents a systematically developed model of the mechanism governing technology diffusion. Important findings from the study show that purchasing power, represented by total health expenditure per capita and economic incentives to hospitals in the form of flexible payment methods, were positively correlated with diffusion. Another important achievement of our model is that it accounts for all thirty OECD member countries without excluding any as outliers. This study shows that variation across countries in the diffusion of medical technology can be explained well by a logical model with multiple variables, the results of which hold profound implications for health policy regarding the adoption of innovations.
OBJECTIVES: The aim of this study is to explain factors influential to the diffusion of computed tomography (CTs) and magnetic resonance imaging (MRIs). METHODS: Variables were identified from a review of the literature on the diffusion of health technologies. A formal process was applied to build a conceptual model of the mechanism that drives technology diffusion. Variables for the analysis were classified as predisposing, enabling, or reinforcing factors, in keeping with a model commonly used to explain the diffusion of health behaviors. Multiple regression analysis was conducted using year 2000 OECD data. RESULTS: The results of this study showed that total health expenditure per capita (p < .01, both CTs and MRIs) and flexible payment methods to hospitals (p < .05, both CTs and MRIs) were significantly associated with the diffusion of CTs and MRIs (adjusted R2 = 0.477, 0.656, respectively). CONCLUSIONS: This study presents a systematically developed model of the mechanism governing technology diffusion. Important findings from the study show that purchasing power, represented by total health expenditure per capita and economic incentives to hospitals in the form of flexible payment methods, were positively correlated with diffusion. Another important achievement of our model is that it accounts for all thirty OECD member countries without excluding any as outliers. This study shows that variation across countries in the diffusion of medical technology can be explained well by a logical model with multiple variables, the results of which hold profound implications for health policy regarding the adoption of innovations.
Authors: Hossein Ebrahimipour; Seyedeh Zahra Mirfeizi; Ali Vafaee Najar; Amir Reza Kachooei; Amir Shahriar Ariamanesh; Reza Ganji; Habibollah Esmaeeli; Hedayat Salari; Marjan Vejdani Journal: Arch Bone Jt Surg Date: 2014-03-15
Authors: Ragnar Westerling; Marcus Westin; Martin McKee; Rasmus Hoffmann; Iris Plug; Grégoire Rey; Eric Jougla; Katrin Lang; Kersti Pärna; José L Alfonso; Johan P Mackenbach Journal: J Eval Clin Pract Date: 2014-04-22 Impact factor: 2.431
Authors: Rosanna Tarricone; Giovanni Aguzzi; Francesco Musi; Laura Fariselli; Andrea Casasco Journal: Neuropsychiatr Dis Treat Date: 2008-06 Impact factor: 2.570