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Drug poisoning management using smartphones: an apps review study based on use case classification model
  1. Sadrieh Hajesmaeel Gohari1,
  2. Kambiz Bahaadinbeigy2,
  3. Shahrad Tajoddini3,
  4. Sharareh R Niakan Kalhori4
  1. 1 Medical Informatics Research Center, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran
  2. 2 Modeling in Health Research Center, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran
  3. 3 Emergency Medicine Department, Neuroscience Research Center, Institute of Neuropharmacology, Kerman University of Medical Sciences, Kerman, Iran
  4. 4 Department of Health Information Management, School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran, Iran
  1. Correspondence to Dr Sharareh R Niakan Kalhori, Tehran, Iran (the Islamic Republic of); sh-rniakank{at}sina.tums.ac.ir

Abstract

Drug poisoning is the most common form of poisoning in the world. Timely and efficient management of this form of poisoning may save the life of many patients. Today, smartphone apps are widely used for various utilisations, such as for medical purposes. This study aimed to review the crucial characteristics of Android and iOS apps for drug poisoning management and categorise them by the use case classification model. Google Play and App Store were searched in December 2018 for drug poisoning apps using the keywords toxicology, poisoning, drug poisoning and drug toxicities, and resulted in 551 smartphone apps. The 17 final apps were evaluated based on the following items: platform, cost, date of update, country, app target, target group, rating and developer. The results showed that 64.7% of apps were available on both platforms and 53% were free to download. Majority of the apps (53%) were designed for medical staff and 47% were developed in the USA. In 47% of the apps, users rated a score above 4 for apps evaluation, and in 47% the last update was 1 year ago. Nine distinct use cases from the published use case classification model were found in 17 apps. The results of this study can help users select and use a reliable app for management of drug poisoning. The results also showed that 22 use cases of the 31 introduced were not considered in the development of the apps. Application of these use cases may improve the quality of drug poisoning management apps.

  • poisoning
  • drug-related side effects and adverse reactions
  • disease management
  • quality of health care
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Footnotes

  • Contributors SHG and SRNK planned the study. Data acquisition and analysis were performed by SHG. Collected data on apps were analysed by SHG, KB and SRNK. KB and ST advised about the clinical aspects of the study. SHG and SRNK drafted and corrected the final version of the work, which was approved by all the authors.

  • Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.

  • Competing interests None declared.

  • Patient consent for publication Not required.

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Data availability statement All data relevant to the study are included in the article.

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