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评估药物依从性应用程序的功能、特性和健康素养水平,并为医疗保健专业人员和患者创建一个可搜索的基于网络的依从性应用程序资源。

Assessment of medication adherence app features, functionality, and health literacy level and the creation of a searchable Web-based adherence app resource for health care professionals and patients.

作者信息

Heldenbrand Seth, Martin Bradley C, Gubbins Paul O, Hadden Kristie, Renna Catherine, Shilling Rebecca, Dayer Lindsey

出版信息

J Am Pharm Assoc (2003). 2016 May-Jun;56(3):293-302. doi: 10.1016/j.japh.2015.12.014. Epub 2016 Apr 7.

Abstract

OBJECTIVES

To assess the features and level of health literacy (HL) of available medication adherence apps and to create a searchable website to assist health care providers (HCP) and patients identify quality adherence apps.

PRACTICE DESCRIPTION

Medication nonadherence continues to be a significant problem and leads to poor health outcomes and avoidable health care expense. The average adherence rate for chronic medications, regardless of disease state, is approximately 50% leaving significant room for improvement.

PRACTICE INNOVATION

Smartphone adherence apps are a novel resource to address medication nonadherence. With widespread smartphone use and the growing number of adherence apps, both HCP and patients should be able to identify quality adherence apps to maximize potential benefits.

INTERVENTIONS

Assess the features, functionality and level of HL of available adherence apps and create a searchable website to help both HCP and patients identify quality adherence apps.

EVALUATION

Online marketplaces (iTunes, Google Play, Blackberry) were searched in June of 2014 to identify available adherence apps. Online descriptions were recorded and scored based on 28 author-identified features across 4 domains. The 100 highest-scoring apps were user-tested with a standardized regimen to evaluate their functionality and level of HL.

RESULTS

461 adherence apps were identified. 367 unique apps were evaluated after removing "Lite/Trial" versions. The median initial score based on descriptions was 15 (max of 68; range: 3 to 47). Only 77 apps of the top 100 highest-scoring apps completed user-testing and HL evaluations. The median overall user-testing score was 30 (max of 73; range: 16 to 55).

CONCLUSION

App design, functionality, and level of HL varies widely among adherence apps. While no app is perfect, several apps scored highly across all domains. The website www.medappfinder.com is a searchable tool that helps HCP and patients identify quality apps in a crowded marketplace.

摘要

目的

评估现有用药依从性应用程序的健康素养(HL)特征和水平,并创建一个可搜索的网站,以帮助医疗保健提供者(HCP)和患者识别高质量的依从性应用程序。

实践描述

用药不依从仍然是一个重大问题,会导致健康状况不佳和可避免的医疗费用。无论疾病状态如何,慢性药物的平均依从率约为50%,仍有很大的改进空间。

实践创新

智能手机依从性应用程序是解决用药不依从问题的一种新型资源。随着智能手机的广泛使用和依从性应用程序数量的不断增加,HCP和患者都应该能够识别高质量的依从性应用程序,以最大限度地发挥潜在益处。

干预措施

评估现有依从性应用程序的特征、功能和HL水平,并创建一个可搜索的网站,以帮助HCP和患者识别高质量的依从性应用程序。

评估

2014年6月在在线市场(iTunes、谷歌Play、黑莓)中进行搜索,以识别可用的依从性应用程序。根据作者确定的4个领域的28个特征,记录在线描述并进行评分。对得分最高的100个应用程序进行用户测试,采用标准化方案评估其功能和HL水平。

结果

共识别出461个依从性应用程序。去除“精简版/试用版”后,对367个独特的应用程序进行了评估。根据描述得出的初始中位数分数为15(满分68;范围:3至47)。得分最高的100个应用程序中只有77个完成了用户测试和HL评估。用户测试的总体中位数分数为30(满分73;范围:16至55)。

结论

依从性应用程序的应用程序设计、功能和HL水平差异很大。虽然没有一个应用程序是完美的,但有几个应用程序在所有领域的得分都很高。网站www.medappfinder.com是一个可搜索的工具,可帮助HCP和患者在竞争激烈的市场中识别高质量的应用程序。

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