School of Computing, Mathematics and Engineering, Charles Sturt University, Bathurst, 2795, NSW, Australia.
Department of Computer Science and Engineering, Chittagong University of Engineering and Technology, Chattogram, 4349, Chattogram, Bangladesh.
J Med Syst. 2024 Aug 24;48(1):80. doi: 10.1007/s10916-024-02091-x.
With the proliferation of wound assessment apps across various app stores and the increasing integration of artificial intelligence (AI) in healthcare apps, there is a growing need for a comprehensive evaluation system. Current apps lack sufficient evidence-based reliability, prompting the necessity for a systematic assessment. The objectives of this study are to evaluate the wound assessment and monitoring apps, identify limitations, and outline opportunities for future app development. An electronic search across two major app stores (Google Play store, and Apple App Store) was conducted and the selected apps were rated by three independent raters. A total of 170 apps were discovered, and 10 were selected for review based on a set of inclusion and exclusion criteria. By modifying existing scales, an app rating scale for wound assessment apps is created and used to evaluate the selected ten apps. Our rating scale evaluates apps' functionality and software quality characteristics. Most apps in the app stores, according to our evaluation, do not meet the overall requirements for wound monitoring and assessment. All the apps that we reviewed are focused on practitioners and doctors. According to our evaluation, the app ImitoWound got the highest mean score of 4.24. But this app has 7 criteria among our 11 functionalities criteria. Finally, we have recommended future opportunities to leverage advanced techniques, particularly those involving artificial intelligence, to enhance the functionality and efficacy of wound assessment apps. This research serves as a valuable resource for future developers and researchers seeking to enhance the design of wound assessment-based applications, encompassing improvements in both software quality and functionality.
随着伤口评估应用程序在各大应用商店中的普及，以及人工智能（AI）在医疗保健应用程序中的日益融合，人们对综合评估系统的需求日益增长。目前的应用程序缺乏足够的基于证据的可靠性，因此需要进行系统评估。本研究的目的是评估伤口评估和监测应用程序，确定其局限性，并为未来的应用程序开发提供机会。我们在两个主要的应用商店（Google Play 商店和 Apple App Store）上进行了电子搜索，并由三名独立的评估员对选定的应用程序进行了评分。共发现了 170 个应用程序，根据一套包含和排除标准，选择了 10 个进行审查。通过修改现有的量表，我们创建了一个用于评估伤口评估应用程序的应用程序评分量表，并用于评估选定的十个应用程序。我们的评分量表评估了应用程序的功能和软件质量特性。根据我们的评估，应用商店中的大多数应用程序都不符合伤口监测和评估的总体要求。我们评估过的所有应用程序都专注于从业者和医生。根据我们的评估，ImitoWound 应用程序获得了最高的平均得分 4.24。但这款应用在我们 11 项功能标准中有 7 项标准。最后，我们建议利用先进技术，特别是人工智能技术，来增强伤口评估应用程序的功能和效果，这是未来的机会。本研究为未来希望改进基于伤口评估的应用程序设计的开发者和研究人员提供了有价值的资源，涵盖了软件质量和功能的改进。
