一种用于多个短间隔的再填充依从性算法，以估计再填充依从性（ReComp）。

A refill adherence algorithm for multiple short intervals to estimate refill compliance (ReComp).

作者信息

Bryson Chris L, Au David H, Young Bessie, McDonell Mary B, Fihn Stephan D

机构信息

Health Services Research and Development Northwest Center of Excellence, Seattle, Washington 98101, USA.

出版信息

Med Care. 2007 Jun;45(6):497-504. doi: 10.1097/MLR.0b013e3180329368.

DOI:10.1097/MLR.0b013e3180329368

PMID:17515776

Abstract

BACKGROUND

There are many measures of refill adherence available, but few have been designed or validated for use with repeated measures designs and short observation periods.

OBJECTIVE

To design a refill-based adherence algorithm suitable for short observation periods, and compare it to 2 reference measures.

METHODS

A single composite algorithm incorporating information on both medication gaps and oversupply was created. Electronic Veterans Affairs pharmacy data, clinical data, and laboratory data from routine clinical care were used to compare the new measure, ReComp, with standard reference measures of medication gaps (MEDOUT) and adherence or oversupply (MEDSUM) in 3 different repeated measures medication adherence-response analyses. These analyses examined the change in low density lipoprotein (LDL) with simvastatin use, blood pressure with antihypertensive use, and heart rate with beta-blocker use for 30- and 90-day intervals. Measures were compared by regression based correlations (R2 values) and graphical comparisons of average medication adherence-response curves.

RESULTS

In each analysis, ReComp yielded a significantly higher R2 value and more expected adherence-response curve regardless of the length of the observation interval. For the 30-day intervals, the highest correlations were observed in the LDL-simvastatin analysis (ReComp R2 = 0.231; [95% CI, 0.222-0.239]; MEDSUM R2 = 0.054; [95% CI, 0.049-0.059]; MEDOUT R2 = 0.053; [95% CI, 0.048-0.058]).

CONCLUSIONS

ReComp is better suited to shorter observation intervals with repeated measures than previously used measures.

摘要

背景

现有的衡量药物续方依从性的方法众多，但针对重复测量设计和短观察期设计或验证的方法却很少。

目的

设计一种适用于短观察期的基于续方的依从性算法，并将其与两种参考方法进行比较。

方法

创建了一种整合药物间断和药物过量供应信息的单一复合算法。利用退伍军人事务部的电子药房数据、临床数据以及常规临床护理中的实验室数据，在3种不同的重复测量药物依从性 - 反应分析中，将新方法ReComp与药物间断的标准参考方法（MEDOUT）以及依从性或药物过量供应的标准参考方法（MEDSUM）进行比较。这些分析考察了使用辛伐他汀时低密度脂蛋白（LDL）的变化、使用抗高血压药物时血压的变化以及使用β受体阻滞剂时心率在30天和90天间隔内的变化。通过基于回归的相关性（R2值）以及平均药物依从性 - 反应曲线的图形比较来对比各项指标。

结果

在每次分析中，无论观察期长短，ReComp均产生显著更高的R2值以及更符合预期的依从性 - 反应曲线。在30天的间隔期内，LDL - 辛伐他汀分析中观察到最高的相关性（ReComp的R2 = 0.231；[95%置信区间，0.222 - 0.239]；MEDSUM的R2 = 0.054；[95%置信区间，0.049 - 0.059]；MEDOUT的R2 = 0.053；[9 "%置信区间，0.048 - 0.058]）。