AdhereR: An Open Science Approach to Estimating Adherence to Medications Using Electronic Healthcare Databases

被引：8

作者：

Dima, Alexandra ^{[1
]}

Allemann, Samuel ^{[1
,2
]}

Dediu, Dan ^{[3
]}

机构：

[1] Univ Claude Bernard Lyon 1, EA Hlth Serv & Performance Res 7425, Lyon, France

[2] Univ Basel, Pharmaceut Care Res Grp, Basel, Switzerland

[3] Univ Lumiere Lyon 2, Lab Dynam Langage, Lyon, France

来源：

MEDINFO 2019: HEALTH AND WELLBEING E-NETWORKS FOR ALL | 2019年 / 264卷

基金：

瑞士国家科学基金会;

关键词：

Medication Adherence; Medical Records; Reproducibility of Results;

D O I：

10.3233/SHTI190479

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

Adherence to medications is a key performance indicator and behavioral outcome in healthcare. Electronic healthcare databases represent rich data sources for estimating adherence in both research and practice. To build a solid evidence base for adherence management across clinical settings, it is necessary to standardize adherence estimation and facilitate its appropriate use. We present the recent development and oportunities offered by AdhereR, an R package for visualisation of medication histories and computation of adherence.

引用

页码：1451 / 1452

页数：2

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