Arnet Isabelle, Greenland Melanie, Knuiman Matthew W, Rankin Jamie M, Hung Joe, Nedkoff Lee, Briffa Tom G, Sanfilippo Frank M
Department of Pharmaceutical Sciences, Pharmaceutical Care Research Group, University of Basel, Basel, Switzerland.
School of Population and Global Health, Faculty of Health and Medical Sciences, The University of Western Australia, Perth, WA, Australia,
Clin Epidemiol. 2018 Sep 6;10:1181-1194. doi: 10.2147/CLEP.S153496. eCollection 2018.
Electronic health care data contain rich information on medicine use from which adherence can be estimated. Various measures developed with medication claims data called for transparency of the equations used, predominantly because they may overestimate adherence, and even more when used with multiple medications. We aimed to operationalize a novel calculation of adherence with polypharmacy, the daily polypharmacy possession ratio (DPPR), and validate it against the common measure of adherence, the medication possession ratio (MPR) and a modified version (MPR).
We used linked health data from the Australian Pharmaceutical Benefits Scheme and Western Australian hospital morbidity dataset and mortality register. We identified a strict study cohort from 16,185 patients aged ≥65 years hospitalized for myocardial infarction in 2003-2008 in Western Australia as an illustrative example. We applied iterative exclusion criteria to standardize the dispensing histories according to previous literature. A SAS program was developed to calculate the adherence measures accounting for various drug parameters.
The study cohort was 348 incident patients (mean age 74.6±6.8 years; 69% male) with an admission for myocardial infarction who had cardiovascular medications over a median of 727 days (range 74 to 3,798 days) prior to readmission. There were statins (96.8%), angiotensin converting enzyme inhibitors (88.8%), beta-blockers (85.6%), and angiotensin receptor blockers (13.2%) dispensed. As expected, observed adherence values were higher with mean MPR (median 89.2%; Q: 73.3%; Q 104.6%) than mean MPR (median 82.8%; Q: 68.5%; Q 95.9%). DPPR values were the most narrow (median 83.8%; Q: 70.9%; Q 96.4%). Mean MPR and DPPR yielded very close possession values for 37.9% of the patients. Values were similar in patients with longer observation windows. When the traditional threshold of 80% was applied to mean MPR and DPPR values to signify the threshold for good adherence, 11.6% of patients were classified as good adherers with the mean MPR relative to the DPPR.
In the absence of transparent and standardized equations to calculate adherence to polypharmacy from refill databases, the novel DPPR algorithm represents a valid and robust method to estimate medication possession for multi-medication regimens.
电子医疗保健数据包含丰富的用药信息，据此可估算用药依从性。利用药物报销数据开发的各种测量方法要求所用方程具有透明度，主要是因为这些方法可能高估依从性，在用于多种药物时更是如此。我们旨在实施一种新的多药治疗依从性计算方法，即每日多药持有率（DPPR），并将其与常用的依从性测量方法——药物持有率（MPR）及其修正版本进行验证。
我们使用了来自澳大利亚药品福利计划以及西澳大利亚医院发病率数据集和死亡率登记处的关联健康数据。以西澳大利亚2003年至2008年因心肌梗死住院的16185名年龄≥65岁的患者为例，确定了一个严格的研究队列。我们应用迭代排除标准，根据既往文献规范配药记录。开发了一个SAS程序来计算考虑各种药物参数的依从性测量值。
该研究队列包括348例心肌梗死入院的新发病例（平均年龄74.6±6.8岁；69%为男性），他们在再次入院前使用心血管药物的时间中位数为727天（范围74至3798天）。所配药物有他汀类药物（96.8%）、血管紧张素转换酶抑制剂（88.8%）、β受体阻滞剂（85.6%）和血管紧张素受体阻滞剂（13.2%）。正如预期的那样，观察到的依从性值中，平均MPR（中位数89.2%；第一四分位数：73.3%；第三四分位数104.6%）高于平均MPR（中位数82.8%；第一四分位数：68.5%；第三四分位数95.9%）。DPPR值范围最窄（中位数83.8%；第一四分位数：70.9%；第三四分位数96.4%）。37.9%的患者平均MPR和DPPR得出的持有率值非常接近。观察窗口较长的患者中，这些值相似。当将80%的传统阈值应用于平均MPR和DPPR值以表示良好依从性的阈值时，相对于DPPR，平均MPR将11.6%的患者归类为依从性良好。
在缺乏用于从再填充数据库计算多药治疗依从性的透明且标准化方程的情况下，新的DPPR算法是一种有效且可靠的方法，可用于估算多种药物治疗方案的药物持有率。
