Centre for Applied Health Economics, Griffith University, Logan Campus, Meadowbrook, QLD, Australia.
J Med Econ. 2011;14(6):698-704. doi: 10.3111/13696998.2011.614304. Epub 2011 Sep 5.
This study uses data from a prospective randomized controlled trial to estimate predictors of pharmaceutical expenditure in diabetes (DM) or cardiovascular disease (CVD) patients. Identifying drivers of pharmaceutical use and the extent to which they are modifiable may inform cost-effective policy-making.
The trial followed 260 patients aged >18 years (mean 68) from three general practices for 12 months. Patients had type 2 diabetes (90 patients) or cardiovascular disease (170 patients). Costs for pharmaceuticals prescribed on the Pharmaceutical Benefits Scheme (PBS) were obtained retrospectively at 12 months. Sociodemographic data and health-related quality-of-life (QoL) were recorded from questionnaires. Clinical measures (including body mass index (BMI), blood pressure, high and low density lipoprotein (LDL), and HbA1c) were also collected.
Mean pharmaceutical costs for DM patients (AU$4119) was greater than CVD patients (AU$2424). The largest contributor to costs in both groups was pharmaceuticals used for management of conditions other than CVD or DM. QoL (EQ5D) and BMI were significant predictors of costs in both groups. A history of cardiac events, HbA1c, age, and unemployment were significant predictors of costs in the DM group. A diagnosis of heart failure, frequency of hospital admissions, and LDL levels were significant predictors of costs in the CVD group. Roughly one third of total variation of costs can be explained by the regressors in both models.
Generalizability will be limited as data was derived from a trial and the study was not powered for this post-hoc analysis. Missing data imputation and self-reporting bias may also impact on results.
Factors such as QoL BMI, HbA1c levels, and a history of cardiac events are significant predictors of costs. The results suggest there may be a place for interventions that improve quality-of-life and concurrently reduce pharmaceutical costs in patients with CVD or DM.
本研究利用前瞻性随机对照试验的数据,估计糖尿病(DM)或心血管疾病(CVD)患者药物支出的预测因素。确定药物使用的驱动因素及其可改变程度,可以为制定具有成本效益的政策提供信息。
该试验随访了来自三家普通诊所的 260 名年龄>18 岁(平均 68 岁)的患者,为期 12 个月。患者患有 2 型糖尿病(90 名患者)或心血管疾病(170 名患者)。在 12 个月时,通过回顾性方法获得了在药物福利计划(PBS)上开具的药物的成本。从问卷调查中获得了社会人口统计学数据和与健康相关的生活质量(QoL)。还收集了临床指标(包括体重指数(BMI)、血压、高低密度脂蛋白(LDL)和 HbA1c)。
DM 患者(AU$4119)的药物费用平均值高于 CVD 患者(AU$2424)。两组中费用最大的贡献者是用于治疗 CVD 或 DM 以外疾病的药物。两组中,QoL(EQ5D)和 BMI 是成本的重要预测因素。心脏事件史、HbA1c、年龄和失业是 DM 组成本的重要预测因素。心力衰竭诊断、住院频率和 LDL 水平是 CVD 组成本的重要预测因素。两个模型的回归因子可以解释总成本的大约三分之一的变化。
由于数据来自试验,并且该研究没有为此事后分析提供动力,因此其普遍性将受到限制。缺失数据插补和自我报告偏倚也可能影响结果。
QoL、BMI、HbA1c 水平和心脏事件史等因素是成本的重要预测因素。结果表明,在 CVD 或 DM 患者中,可能有必要进行改善生活质量并同时降低药物成本的干预措施。