Centre for Health Informatics, Australian Institute of Health Innovation, University of New South Wales, Sydney, NSW, Australia.
BMC Health Serv Res. 2012 Aug 10;12:248. doi: 10.1186/1472-6963-12-248.
The adoption of new medicines is influenced by a complex set of social processes that have been widely examined in terms of individual prescribers' information-seeking and decision-making behaviour. However, quantitative, population-wide analyses of how long it takes for new healthcare practices to become part of mainstream practice are rare.
We applied a Bass diffusion model to monthly prescription volumes of 103 often-prescribed drugs in Australia (monthly time series data totalling 803 million prescriptions between 1992 and 2010), to determine the distribution of adoption rates. Our aim was to test the utility of applying the Bass diffusion model to national-scale prescribing volumes.
The Bass diffusion model was fitted to the adoption of a broad cross-section of drugs using national monthly prescription volumes from Australia (median R2 = 0.97, interquartile range 0.95 to 0.99). The median time to adoption was 8.2 years (IQR 4.9 to 12.1). The model distinguished two classes of prescribing patterns - those where adoption appeared to be driven mostly by external forces (19 drugs) and those driven mostly by social contagion (84 drugs). Those driven more prominently by internal forces were found to have shorter adoption times (p = 0.02 in a non-parametric analysis of variance by ranks).
The Bass diffusion model may be used to retrospectively represent the patterns of adoption exhibited in prescription volumes in Australia, and distinguishes between adoption driven primarily by external forces such as regulation, or internal forces such as social contagion. The eight-year delay between the introduction of a new medicine and the adoption of the prescribing practice suggests the presence of system inertia in Australian prescribing practices.
新药的采用受到一系列复杂的社会过程的影响,这些过程已经在个体处方者的信息搜索和决策行为方面得到了广泛的研究。然而,定量的、全人群的分析表明,新的医疗实践需要多长时间才能成为主流实践的情况却很少见。
我们应用 Bass 扩散模型分析了澳大利亚 103 种常用药物的每月处方量(1992 年至 2010 年间共 8.03 亿张处方的月度时间序列数据),以确定采用率的分布。我们的目的是检验 Bass 扩散模型在全国范围内的处方量上的应用效果。
使用澳大利亚全国范围内的每月处方量,Bass 扩散模型拟合了广泛的药物采用情况(中位数 R2 为 0.97,四分位距为 0.95 至 0.99)。采用的中位数时间为 8.2 年(四分位距为 4.9 至 12.1)。该模型区分了两种处方模式——一种是外部力量似乎主要驱动的模式(19 种药物),另一种是社会传播主要驱动的模式(84 种药物)。那些主要受到内部力量驱动的药物发现其采用时间更短(非参数方差分析秩检验,p=0.02)。
Bass 扩散模型可用于回顾性地表示澳大利亚处方量中表现出的采用模式,并区分主要由外部力量(如监管)驱动的采用,或由内部力量(如社会传播)驱动的采用。新药物引入与处方实践采用之间存在 8 年的延迟,这表明澳大利亚处方实践中存在系统惯性。