Scott B Patten1. 1. Department of Community Health Sciences, Department of Psychiatry, University of Calgary, 3330 Hospital Drive NW, Calgary, AB, T2N 4N1, Canada. patten@ucalgary.ca
Abstract
BACKGROUND: In the absence of strategies for primary prevention, public health initiatives for major depression have generally focused on secondary and tertiary strategies such as case-finding, public and professional education and disease management. Much emphasis has been placed on low reported rates of antidepressant utilization. In principle, increased rates of treatment utilization should lead to improved mental health status at the population level. However, methods for relating antidepressant utilization to population health status have not been described. METHODS: An incidence-prevalence model was developed using data from a Canadian national survey, supplemented by parameter estimates from literature reviews. The lifetime sick-day proportion (LSP) was used to approximate point prevalence. RESULTS: Mathematical simulations using this model produced reasonable approximations of point prevalence for major depression. The model suggests that an improved rate of treatment utilization may not, in itself, lead to substantially reduced prevalence. Reducing the rate of relapse in those with highly recurrent disorders, which can be accomplished by long-term antidepressant treatment, is predicted to have a more substantial impact on population health status. CONCLUSIONS: The model presented here offers a framework for describing the impact of antidepressant treatment on population health status. Mathematical models may assist with decision-making and priority setting in the public health sphere, as illustrated by the model presented here, which challenges some commonly held assumptions.
BACKGROUND: In the absence of strategies for primary prevention, public health initiatives for major depression have generally focused on secondary and tertiary strategies such as case-finding, public and professional education and disease management. Much emphasis has been placed on low reported rates of antidepressant utilization. In principle, increased rates of treatment utilization should lead to improved mental health status at the population level. However, methods for relating antidepressant utilization to population health status have not been described. METHODS: An incidence-prevalence model was developed using data from a Canadian national survey, supplemented by parameter estimates from literature reviews. The lifetime sick-day proportion (LSP) was used to approximate point prevalence. RESULTS: Mathematical simulations using this model produced reasonable approximations of point prevalence for major depression. The model suggests that an improved rate of treatment utilization may not, in itself, lead to substantially reduced prevalence. Reducing the rate of relapse in those with highly recurrent disorders, which can be accomplished by long-term antidepressant treatment, is predicted to have a more substantial impact on population health status. CONCLUSIONS: The model presented here offers a framework for describing the impact of antidepressant treatment on population health status. Mathematical models may assist with decision-making and priority setting in the public health sphere, as illustrated by the model presented here, which challenges some commonly held assumptions.
Authors: Michel Joffres; Alejandra Jaramillo; James Dickinson; Gabriela Lewin; Kevin Pottie; Elizabeth Shaw; Sarah Connor Gorber; Marcello Tonelli Journal: CMAJ Date: 2013-05-13 Impact factor: 8.262
Authors: Michael S Martin; George A Wells; Anne G Crocker; Beth K Potter; Ian Colman Journal: Int J Methods Psychiatr Res Date: 2017-12-28 Impact factor: 4.035
Authors: Brett D Thombs; James C Coyne; Pim Cuijpers; Peter de Jonge; Simon Gilbody; John P A Ioannidis; Blair T Johnson; Scott B Patten; Erick H Turner; Roy C Ziegelstein Journal: CMAJ Date: 2011-09-19 Impact factor: 8.262