A Pictorial Schema for a Comprehensive User-oriented Identification of Medical Apps
21 August 2013
accepted: 16 January 2014
20 January 2018 (online)
Objectives: The huge amount of released medical apps prevents medical app users from believing that medical scientific societies and other accreditation bodies as well, have the resources and the power for assigning to any medical app a quality score. By the time being, any medical app user has to take the risks related to the frequently insufficient accreditation of that app. Providing clear user-oriented schemas, to be adopted both when putting a medical App on the market and when an App comes to be evaluated by a cohort or single users, becomes crucial. The aim of our research was to define a pictorial identification one-shot schema for a comprehensive user-oriented identification of medical apps.
Methods: Adopting a pictorial approach is common in software design modeling. To build up our identification schema we started from the limited number of Apps already available on a web site of app reviews (iMedicalApps.com), and we identified an appropriately large set of attributes for describing medical apps. We arranged the attributes in six main families. We organized them in a one-shot comprehensive pictorial schema. We adopted a traffic light color code for assessing each attribute, that was sufficient to provide simple elements of alerts and alarms regarding a single App. Then, we considered apps from iMedicalApps.com web site belonging to three medical specialties: cardiology, oncology, and pharma and analyzed them according to the proposed pictorial schema.
Results: A pictorial schema having the attributes grouped in the families related to “Responsible Promoters”, “Offered Services”, “Searching Methods”, “Applications Domains”, “Envisaged Users”, and “Qualifiers and Quantifiers” has been identified. Furthermore, we produced a one-shot pictorial schema for each considered app, and for each medical specialty, we produced it also in an aggregated form.
Conclusions: The one-shot pictorial schema provides a useful perception of when and where to use a considered app. It fits positively the expectations of potential but different user’s profiles. It can be a first step towards a systematic assessment of apps from the user viewpoint.
- 1 Marceglia S, Bonacina S, Zaccaria V, Pagliari C, Pinciroli F. How might the iPad change healthcare?. J R Soc Med. 2012; 105 (06) 233-241.
- 2 Huckvale K, Car M, Morrison C, Car J. Apps for asthma self-management: a systematic assessment of content and tools. BMC Med 2012; 10: 144
- 3 Ricciardi L, Mostashari F, Murphy J, Daniel JG, Siminerio EP. A national action plan to support consumer engagement via e-health. Health Aff (Millwood) 2013; 32 (02) 376-384.
- 4 Ozdalga E, Ozdalga A, Ahuja N. The smartphone in medicine: a review of current and potential use among physicians and students. J Med Internet Res 2012; 14 (05) e128
- 5 Burki TK. Cancer apps. Lancet Oncol 2013; 14 (07) 580-581.
- 6 McCartney M. How do we know whether medical apps work?. BMJ 2013; 346: f1811
- 7 N. N. Most smartphone apps for melanoma detection are inaccurate. Health Devices 2013; 42 (04) 135
- 8 Rosser BA, Eccleston C. Smartphone applications for pain management. J Telemed Telecare 2011; 17 (06) 308-312.
- 9 Visvanathan A, Hamilton A, Brady RR. Smartphone apps in microbiology - is better regulation required?. Clin Microbiol Infect 2012; 18 7E 218-20.
- 10 Demidowich AP, Lu K, Tamler R, Bloomgarden Z. An evaluation of diabetes self-management applications for Android smartphones. J Telemed Telecare 2012; 18 (04) 235-238.
- 11 Albrecht UV, von Jan U, Pramann O, Matthies HK. I, App: Trustworthy Medical Apps. T11- Village of the Future - Pillar 5: Social and Policy Incentive Framework. Medical Informatics Europe - MIE 2012. August 26th-29th, 2012. Pisa, Italy. Avail- able at URL. http://plrimedapplab.weebly.com/publications.html Accessed: November 15, 2013
- 12 Lewis T. Apple now asking app developers to provide sources of medical information. (Online, September 18, 2013>). Available at URL. http://www.imedicalapps.com/2013/09/apple-app-developers-sources-medical-information/ Accessed: November 15, 2013
- 13 Huy NP, vanThanh D. Evaluation of mobile app paradigms. Proceeding of MoMM ’12- The 10th International Conference on Advances in Mobile Computing & Multimedia. New York, NY: ACM; 2012. ISBN: 978-1-4503-1307-0 25-30.
- 14 Peng H, Gates C, Sarma B. et al Using probabilistic generative models for ranking risks of Android apps. Proceeding of CCS ’12- The 2012 Association Computing Machinery (ACM) conference on Computer and communications security. New York, NY: ACM; 2012. SBN: 978-1-4503-1651-4 241-252.
- 15 Barton AJ. The regulation of mobile health applications. BMC Med 2012; 10: 46
- 16 U.S. Department of Health and Human Services. Food and Drug Administration. Mobile Medi- cal Applications - Guidance for Industry and Food and Drug Administration Staff. Avail- able at URL. http://www.fda.gov/downloads/MedicalDevices/DeviceRegulationandGuidance/GuidanceDocuments/UCM263366.pdf Accessed: November 15, 2013
- 17 Albrecht UV, Von Jan U, Pramann O. Standard reporting for medical apps. Stud Health Technol Inform 2013; 190: 201-203.
- 18 Albrecht UV, von Jan U, Jungnickel T, Pramann O. App-synopsis - standard reporting for medical apps. Stud Health Technol Inform 2013; 192: 1154
- 19 Happtique. Health App Certification Program. Certification Standards. (Online, October 2013). Available at URL. http://www.happtique.com/docs/HACP_Certification_Standards.pdf Accessed: November 15 2013
- 20 Boyer C, Selby M, Scherrer JR, Appel RD. The Health On the Net Code of Conduct for medical and health Websites. Comput Biol Med 1998; 28 (05) 603-610.
- 21 Lewis TL. A systematic self-certification model for mobile medical apps. J MedInternet Res 2013; 15 (04) e89
- 22 mHIMSS App Usability Work Group. Selecting a Mobile App: Evaluating the Usability of Medical Applications. The Healthcare Information and Management Systems Society (HIMSS). July. 2012
- 23 iMedicalApps. Available at URL. http://www.imedicalapps.com Accessed: November 15 2013
- 24 MedicalApp Journal. Available at URL http://medicalappjournal.com/ Accessed.November 15 2013
- 25 Dayer L, Heldenbrand S, Anderson P, Gubbins PO, Martin BC. Smartphone medication adherence apps: potential benefits to patients and providers. J Am Pharm Assoc 2013; 53 (02) 172-181.
- 26 Goldbach H, Chang AY, Kyer A, Ketshogileng D, Taylor L, Chandra A, Dacso M, Kung SJ, Rijken T, Fontelo P, Littman-Quinn R, Seymour AK, Kovarik CL. Evaluation of generic medical information accessed via mobile phones at the point of care in resource-limited settings. J Am Med Inform Assoc 2013 (Epub ahead of print). PubMed PMID: 23535665..
- 27 Wolf JA, Moreau JF, Akilov O, Patton T, English JC, Ho J, Ferris LK. Diagnostic inaccuracy of smartphone applications for melanoma detection. JAMA Dermatol 2013; 149 (04) 422-426.
- 28 Franko I O. Smartphone apps for orthopaedic surgeons. Clin Orthop Relat Res 2011; 469 (07) 2042-2048.
- 29 Cornwall J, Pollard MF. Evaluation of free i-applications for tertiary level gross anatomy education. Australas Med J 2012; 5 (04) 239-242.
- 30 NHS Health Apps Library. Available at URL. http://apps.nhs.uk/ Accessed November 15 2013
- 31 Marceglia S, Mazzola L, Bonacina S, Tarquini P, Donzelli P, Pinciroli F. A comprehensive e-prescribing model to allow representing, comparing, and analyzing available systems. Methods Inf Med 2013; 52 (03) 199-219.
- 32 International Organization for Standardization (ISO). IEC 62366:2007, Medical devices - Application of usability engineering to medical devices. 2008. Available at URL. http://www.iso.org/iso/home/store/catalogue_ics/catalogue_detail_ics.htm?csnumber=38594 Accessed: November, 15 2013
- 33 Gail MH, Brinton LA, Byar DP, Corle DK, Green SB, Shairer C, Mulvihill JJ. Projecting individualized probabilities of developing breast cancer for white females who are being examined annually. J Natl Cancer Inst 1989; 81 (24) 1879-1886.
- 34 Rockhill B, Spiegelman D, Byrne C, Hunter DJ, Colditz GA. Validation of the Gail. et al model of breast cancer risk prediction and implications for chemoprevention. J Natl Cancer Inst 2001; 93 (05) 358-366.
- 35 Pletneva N, Vargas A, Boyer C. Health on the Net. Requirements for the general public health search. Deliverable of EU project KHRESMOI. (Online, May 20, 2011). Available at URL. http://www.hon.ch/Global/pdf/Khresmoi/KHRESMOI_general_public_survey_report.pdf Accessed: November 15 2013
- 36 Associazione Nazionale Medici Cardiologi Ospedalieri (ANMCO). Available at URL. http://www.anmco.it . Accessed: November 15, 2013 (in Italian)