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[使用TestObs移动应用程序评估慢性血液透析患者的治疗依从性:治疗依从性的技术监测模型及决定因素]

[Use of the TestObs mobile application for the evaluation of therapeutic adherence in chronic hemodialysis patients: Technological monitoring model of treatment adherence and determining factors].

作者信息

Chettati Mariam, Bouchemla Nadia, Fadili Wafae, Laouad Inass

机构信息

Centre hospitalo-universitaire Mohammed VI, Principal Av. Ibn Sina, BP2360, Marrakech, Maroc; Laboratoire bioscience et santé, Faculté de médecine et de pharmacie de Marrakech, université Cadi Ayyad, 274, Semlalia, 40000 Marrakech, Maroc.

Centre hospitalo-universitaire Mohammed VI, Principal Av. Ibn Sina, BP2360, Marrakech, Maroc.

出版信息

Nephrol Ther. 2022 Nov;18(6):557-564. doi: 10.1016/j.nephro.2022.07.397. Epub 2022 Oct 21.

Abstract

INTRODUCTION

Non-adherence behaviors are very common in chronic hemodialysis patients, it is estimated that only one patient out of two complies with medical prescriptions, these behaviors are associated with a higher risk of morbidity and adverse events as well as increased expenses for health systems. The aim of our study was to assess adherence to long-term prescribed medications in chronic hemodialysis patients, using a mobile application named TestObs, as well as to determine the main factors influencing medication adherence.

METHODS

We conducted a prospective descriptive study, between January and June 2019. We developed a mobile application named TestObs, downloadable on playstore for android devices, which assesses with the Girerd questionnaire, the adherence to the main medications taken by chronic hemodialysis patients. We included adult patients, with a duration of dialysis of more than 6 months, all patients who downloaded TestObs, tested their adherence to their medication by answering the questionnaire. We created a web-based platform, where data was collected from the application and then analyzed and tabulated. Regarding the statistical analysis, the normal distribution of the variables was studied by the Kolmogorov-Smirnov test, the analysis of the qualitative variables used the Pearson's Chi and Fisher's statistical test, the Hosmer Lemeshow test was used to examine the quality of the final logistic regression model.

RESULTS

We collected 90 adult chronic hemodialysis patients, 51 of them (56%) were selected to enter the study. We found good compliance in 46.15% of patients, minor noncompliance in 32.87%, and noncompliance in 20.98%. In multivariate analysis, the factors influencing adherence were the presence of other comorbidities (diabetes and vision problems) and the number of pills per day.

DISCUSSION

In this study, we report treatment adherence problems in 53.85% of patients, our results are close to the data reported in hemodialysis patients in the literature, different factors influence the quality of treatment adherence, in our study poly-medication and the presence of other comorbidities were the statistically significant determinants. The new technology assessment instruments were used in hemodialysis patients and were able to provide real-time monitoring of adherence behaviors.

CONCLUSION

We believe that mobile health technologies hold promise for assessing and improving medication adherence in hemodialysis patients, so we suggest that TestObs represents an accessible and free of charge tool, based on a validated questionnaire, that can allow patients to benefit from new technologies for medical monitoring, and may eventually constitute an interventional program to improve medication adherence; however, this technological tool should not replace traditional therapeutic education; prior targeting of non-adherent patients and an optimal combination of several tools can help improve adherence in these patients.

摘要

引言

不依从行为在慢性血液透析患者中非常普遍,据估计,每两名患者中只有一名遵守医嘱,这些行为与更高的发病风险和不良事件以及卫生系统费用增加有关。我们研究的目的是使用一款名为TestObs的移动应用程序评估慢性血液透析患者对长期处方药的依从性,并确定影响药物依从性的主要因素。

方法

我们在2019年1月至6月期间进行了一项前瞻性描述性研究。我们开发了一款名为TestObs的移动应用程序,可在安卓设备的应用商店下载,该应用程序通过吉勒德问卷评估慢性血液透析患者对主要服用药物的依从性。我们纳入了透析时间超过6个月的成年患者,所有下载TestObs的患者通过回答问卷来测试他们对药物的依从性。我们创建了一个基于网络的平台,从应用程序中收集数据,然后进行分析和制表。关于统计分析,通过柯尔莫哥洛夫-斯米尔诺夫检验研究变量的正态分布,定性变量的分析使用皮尔逊卡方检验和费舍尔统计检验,霍斯默-莱梅肖检验用于检验最终逻辑回归模型的质量。

结果

我们收集了90名成年慢性血液透析患者,其中51名(56%)被选入研究。我们发现46.15%的患者依从性良好,32.87%的患者轻度不依从,20.98%的患者不依从。在多变量分析中,影响依从性的因素是存在其他合并症(糖尿病和视力问题)以及每天的药片数量。

讨论

在本研究中,我们报告了53.85%的患者存在治疗依从性问题,我们的结果与文献中报道的血液透析患者的数据接近,不同因素影响治疗依从性的质量,在我们的研究中,联合用药和存在其他合并症是具有统计学意义的决定因素。新技术评估工具被用于血液透析患者,并能够提供对依从行为的实时监测。

结论

我们认为移动健康技术有望评估和改善血液透析患者的药物依从性,因此我们建议TestObs是一个基于经过验证的问卷的可获取且免费的工具,它可以让患者受益于用于医疗监测的新技术,并最终可能构成一个改善药物依从性的干预项目;然而,这种技术工具不应取代传统的治疗教育;预先针对不依从患者并优化多种工具的组合有助于提高这些患者的依从性。

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