Quisel Tom, Foschini Luca, Zbikowski Susan M, Juusola Jessie L
Evidation Health, San Mateo, CA, United States.
inZights Consulting, LLC, Seattle, WA, United States.
J Med Internet Res. 2019 Mar 20;21(3):e11486. doi: 10.2196/11486.
Chronic diseases have a widespread impact on health outcomes and costs in the United States. Heart disease and diabetes are among the biggest cost burdens on the health care system. Adherence to medication is associated with better health outcomes and lower total health care costs for individuals with these conditions, but the relationship between medication adherence and health activity behavior has not been explored extensively.
The aim of this study was to examine the relationship between medication adherence and health behaviors among a large population of insured individuals with hypertension, diabetes, and dyslipidemia.
We conducted a retrospective analysis of health status, behaviors, and medication adherence from medical and pharmacy claims and health behavior data. Adherence was measured in terms of proportion of days covered (PDC), calculated from pharmacy claims using both a fixed and variable denominator methodology. Individuals were considered adherent if their PDC was at least 0.80. We used step counts, sleep, weight, and food log data that were transmitted through devices that individuals linked. We computed metrics on the frequency of tracking and the extent to which individuals engaged in each tracking activity. Finally, we used logistic regression to model the relationship between adherent status and the activity-tracking metrics, including age and sex as fixed effects.
We identified 117,765 cases with diabetes, 317,340 with dyslipidemia, and 673,428 with hypertension between January 1, 2015 and June 1, 2016 in available data sources. Average fixed and variable PDC for all individuals ranged from 0.673 to 0.917 for diabetes, 0.756 to 0.921 for dyslipidemia, and 0.756 to 0.929 for hypertension. A subgroup of 8553 cases also had health behavior data (eg, activity-tracker data). On the basis of these data, individuals who tracked steps, sleep, weight, or diet were significantly more likely to be adherent to medication than those who did not track any activities in both the fixed methodology (odds ratio, OR 1.33, 95% CI 1.29-1.36) and variable methodology (OR 1.37, 95% CI 1.32-1.43), with age and sex as fixed effects. Furthermore, there was a positive association between frequency of activity tracking and medication adherence. In the logistic regression model, increasing the adjusted tracking ratio by 0.5 increased the fixed adherent status OR by a factor of 1.11 (95% CI 1.06-1.16). Finally, we found a positive association between number of steps and adherent status when controlling for age and sex.
Adopters of digital health activity trackers tend to be more adherent to hypertension, diabetes, and dyslipidemia medications, and adherence increases with tracking frequency. This suggests that there may be value in examining new ways to further promote medication adherence through programs that incentivize health tracking and leveraging insights derived from connected devices to improve health outcomes.
慢性病对美国的健康状况和成本有着广泛影响。心脏病和糖尿病是医疗保健系统最大的成本负担之一。坚持服药与这些疾病患者的更好健康状况和更低的总体医疗保健成本相关，但药物依从性与健康活动行为之间的关系尚未得到广泛探讨。
本研究的目的是在大量患有高血压、糖尿病和血脂异常的参保人群中，研究药物依从性与健康行为之间的关系。
我们对医疗和药房索赔以及健康行为数据中的健康状况、行为和药物依从性进行了回顾性分析。依从性通过覆盖天数比例（PDC）来衡量，使用固定分母和可变分母方法从药房索赔中计算得出。如果个体的PDC至少为0.80，则被视为依从。我们使用了通过个体连接的设备传输的步数、睡眠、体重和食物日志数据。我们计算了跟踪频率以及个体参与每项跟踪活动的程度的指标。最后，我们使用逻辑回归来建立依从状态与活动跟踪指标之间的关系模型，将年龄和性别作为固定效应。
在2015年1月1日至2016年6月1日的可用数据源中，我们识别出117,765例糖尿病患者、317,340例血脂异常患者和673,428例高血压患者。所有个体的平均固定和可变PDC，糖尿病患者为0.673至0.917，血脂异常患者为0.756至0.921，高血压患者为0.756至0.929。一个8553例的亚组也有健康行为数据（如活动追踪器数据）。基于这些数据，在固定方法（优势比，OR 1.33，95%可信区间1.29 - 1.36）和可变方法（OR 1.37，95%可信区间1.32 - 1.43）中，跟踪步数、睡眠、体重或饮食的个体比未跟踪任何活动的个体更有可能坚持服药，将年龄和性别作为固定效应。此外，活动跟踪频率与药物依从性之间存在正相关。在逻辑回归模型中，将调整后的跟踪率提高0.5会使固定依从状态OR增加1.11倍（95%可信区间1.06 - 1.16）。最后，在控制年龄和性别时，我们发现步数与依从状态之间存在正相关。
数字健康活动追踪器的使用者往往更能坚持服用高血压、糖尿病和血脂异常药物，且依从性随跟踪频率增加。这表明，通过激励健康跟踪的项目以及利用连接设备获得的见解来改善健康状况，研究进一步促进药物依从性的新方法可能具有价值。
