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Medical Mobile App Classification Using the National Institute for Health and Care Excellence Evidence Standards Framework for Digital Health Technologies: Interrater Reliability Study

机译:医疗移动应用程序分类,使用国家健康和护理卓越证据标准框架数字健康技术框架:Interrater可靠性研究

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Background Clinical governance of medical mobile apps is challenging, and there is currently no standard method for assessing the quality of such apps. In 2018, the National Institute for Health and Care Excellence (NICE) developed a framework for assessing the required level of evidence for digital health technologies (DHTs), as determined by their clinical function. The framework can potentially be used to assess mobile apps, which are a subset of DHTs. To be used reliably in this context, the framework must allow unambiguous classification of an app’s clinical function. Objective The objective of this study was to determine whether mobile health apps could be reliably classified using the NICE evidence standards framework for DHTs. Methods We manually extracted app titles, screenshots, and content descriptions for all apps listed on the National Health Service (NHS) Apps Library website on July 12, 2019; none of the apps were downloaded. Using this information, 2 mobile health (mHealth) researchers independently classified each app to one of the 4 functional tiers (ie, 1, 2, 3a, and 3b) described in the NICE digital technologies evaluation framework. Coders also answered contextual questions from the framework to identify whether apps were deemed to be higher risk. Agreement between coders was assessed using Cohen κ statistic. Results In total, we assessed 76 apps from the NHS Apps Library. There was classification agreement for 42 apps. Of these, 0 apps were unanimously classified into Tier 1; 24, into Tier 2; 15, into Tier 3a; and 3, into Tier 3b. There was disagreement between coders in 34/76 cases (45%); interrater agreement was poor (Cohen κ=0.32, 95% CI 0.16-0.47). Further investigation of disagreements highlighted 5 main explanatory themes: apps that did not correspond to any tier, apps that corresponded to multiple tiers, ambiguous tier descriptions, ambiguous app descriptions, and coder error. Conclusions The current iteration of the NICE evidence standards framework for DHTs did not allow mHealth researchers to consistently and unambiguously classify digital health mobile apps listed on the NHS app library according to their functional tier.
机译:背景技术医疗移动应用的临床治理是具有挑战性的,目前没有评估此类应用的质量的标准方法。 2018年,国家健康和护理研究所(尼斯)制定了一个评估数字健康技术(DHTS)所需证据水平的框架,由其临床功能决定。该框架可能用于评估移动应用,这是DHT的子集。要在此背景下可靠地使用,该框架必须允许应用程序的临床功能的明确分类。目的本研究的目的是确定移动运行状况是否可以使用DHTS的良好证据标准框架可靠地分类。方法在2019年7月12日,我们手动提取了全国卫生服务(NHS)Apps Library网站上列出的所有应用程序的应用标题,屏幕截图和内容描述;没有任何应用程序下载。使用此信息,2个移动运营运行状况(MHECHEATH)研究人员独立分类为漂亮的数字技术评估框架中描述的4个功能层(即,1,2,3A和3B)中的一个应用程序。编码家还回答了框架中的上下文问题,以确定应用是否被视为更高的风险。使用Cohenκ统计评估编码器之间的协议。结果总计,我们从NHS Apps库中评估了76个应用程序。 42个应用程序有分类协议。其中,0个应用程序一致分为1级; 24,进入第2层; 15,进入三级3A; 3,进入第3B级。 34/76案例中的编码人员之间存在分歧(45%); Interrater协议差(Cohenκ= 0.32,95%CI 0.16-0.47)。进一步调查分歧的调查突出显示了5个主要解释性主题:与任何层,与多个层,模糊层描述,模糊的应用程序描述和编码器错误相对应的应用程序。结论DHTS良好证据标准框架的当前迭代不允许MHECHEATH研究人员根据其功能层始终如一地展示NHS App库上列出的数字健康移动应用程序。

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