Literature DB >> 29540025

Digitizing diagnosis: a review of mobile applications in the diagnostic process.

Annemarie Jutel1, Deborah Lupton2.   

Abstract

An increasing number of smartphone and software applications ("apps") have been developed and marketed to assist in the process of diagnosis, yet little attention has been paid to their content, claims, potential risks, limitations or benefits of their use. This study sought to describe and catalogue available diagnosis apps and explore their impact on the diagnostic process. We undertook a content analysis of the app descriptions and developers' websites using the descriptions provided for 131 medical diagnosis smartphone apps that were available in the Google Play and Apple App stores. Each app was reviewed for its content and approach, and its claims to medical authority. Four major categories of apps were identified: 1. apps for diagnosing; 2. diagnosis coding apps; 3. books, journals, or other publications in app format; 4. apps for medical education. Our analysis found that while these apps provide access to medical information previously widely not available to lay users and offered a convenient diagnostic tool for practitioners, many failed to describe the evidence base underpinning, or any other credential supporting, their design and use. These apps potentially shift how diagnosis operates, reconfiguring disease concepts and lay-professional relations. However they also raise the risk of conflict of interest and presenting inaccurate information. Further research is required into how these apps are used, the implications for medical practice and the impact on doctor-patient relationship.

Entities:  

Keywords:  apps; diagnosis; doctor-patient; mobile software; smart phones

Year:  2015        PMID: 29540025     DOI: 10.1515/dx-2014-0068

Source DB:  PubMed          Journal:  Diagnosis (Berl)        ISSN: 2194-802X


  6 in total

1.  Evaluating a mobile application for improving clinical laboratory test ordering and diagnosis.

Authors:  Ashley N D Meyer; Pamela J Thompson; Arushi Khanna; Samir Desai; Benji K Mathews; Elham Yousef; Anita V Kusnoor; Hardeep Singh
Journal:  J Am Med Inform Assoc       Date:  2018-07-01       Impact factor: 4.497

2.  Screening accuracy of a 14-day smartphone ambulatory assessment of depression symptoms and mood dynamics in a general population sample: Comparison with the PHQ-9 depression screening.

Authors:  Sebastian Burchert; André Kerber; Johannes Zimmermann; Christine Knaevelsrud
Journal:  PLoS One       Date:  2021-01-06       Impact factor: 3.240

3.  A Comparison of Artificial Intelligence and Human Doctors for the Purpose of Triage and Diagnosis.

Authors:  Adam Baker; Yura Perov; Katherine Middleton; Janie Baxter; Daniel Mullarkey; Davinder Sangar; Mobasher Butt; Arnold DoRosario; Saurabh Johri
Journal:  Front Artif Intell       Date:  2020-11-30

4.  User Perception of New E-Health Challenges: Implications for the Care Process.

Authors:  María Esther González-Revuelta; Nuria Novas; Jose Antonio Gázquez; Manuel Ángel Rodríguez-Maresca; Juan Manuel García-Torrecillas
Journal:  Int J Environ Res Public Health       Date:  2022-03-24       Impact factor: 3.390

5.  Decision-Making in the Pediatric Emergency Department-A Survey of Guidance Strategies among Residents.

Authors:  Sebastian Gaus; Jeremy Schmidt; Paul Lüse; Winfried Barthlen; Eckard Hamelmann; Hendrik Vossschulte
Journal:  Children (Basel)       Date:  2022-08-09

6.  Patient Perspectives on the Usefulness of an Artificial Intelligence-Assisted Symptom Checker: Cross-Sectional Survey Study.

Authors:  Ashley N D Meyer; Traber D Giardina; Christiane Spitzmueller; Umber Shahid; Taylor M T Scott; Hardeep Singh
Journal:  J Med Internet Res       Date:  2020-01-30       Impact factor: 5.428

  6 in total

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