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Towards a protocol for the development of mobile health Apps for patient self-monitoring

Towards a protocol for the development of mobile health Apps for patient self-monitoring. Background

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Towards a protocol for the development of mobile health Apps for patient self-monitoring

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  1. Towards a protocol for the development of mobile health Apps for patient self-monitoring Background Mobile health (mHealth) applications (Apps) based on cellular phones, Smartphones and tablet computers are a rapidly growing trend in healthcare. However, healthcare professional involvement during App development appears to be limited [1]. Furthermore, when patients are the end-users, a lack of user-centred design is also apparent [2]. • Results – key findings • Use information about the regulatory framework (guidance from MHRA, FDA etc.) to assess whether an App should be considered a medical device or not. • A phone audit before commencing a research study allows discovery of the range of prior experiences and preferences for phone functions amongst participants (e.g. alarm clock). Normal daily use and research study use of phone functions may mix or conflict. • Self-monitoring App designs need to incorporate tolerance of real-world phone use e.g. not keeping devices turned on or charged up; missing or ignoring prompts. If an App is being used to monitor care, reliability must be assessed. • Secure collection and storage of data is of prime concern in gaining ethical approval. Smartphone email and SMS are not secure enough for personal data collection. • Burden on the patient cannot be overlooked e.g. frequency of self-monitoring prompts. Passive monitoring may be ethically and practically preferable for more frequent measurements. Pilot studies should aim at measuring adherence. • A participatory design process helps to reveal the needs of researchers and research subjects which may not initially be apparent. Method The Multidisciplinary Assessment of Technology Centre for Healthcare (MATCH) programme has developed a number of Smartphone Apps for patient self-monitoring in collaboration with researchers, clinicians and patient groups for a range of clinical areas including mild asthma, sickle cell disease and infertility treatment [3]. In these applications, patients use an App to report their symptoms (e.g. breathlessness, pain, distress), quality-of-life and effect on daily activities. With some of these Apps physiological data is also captured either directly or by manual input. A case study analysis was performed on the design processes for the Apps to reveal key themes. Conclusions A number of challenges must be addressed in the development process for self-monitoring Apps: to fully elicit both user & clinical needs; to fulfil ethical and research governance requirements; to effectively test prototypes for their usability, functionality and reliability in real-world use scenarios. To achieve this, communication between researchers, developers and ethical reviewers is vital at an early stage of design. The authors aim to collaborate on developing a best practice protocol for mHealth App design for self-monitoring and other applications. Case study screenshots Left to right: Asthma Self-Reported Wellness PEF data entry, Asthma Self-Reported Wellness diary entry, PEF meter & Bluetooth pulse oximeter, SimpleEye Live Pulse Oximeter App, Sickle Cell Monitoring App, IVF Stress App (all Apps designed at University of Nottingham except SimpleEye Live Pulse Oximeter which is a commercial App used for data capture alongside both the asthma and sickle cell Apps). References [1] Rosser BA and Eccleston C (2011) Smartphone applications for pain management. Journal of Telemedicine and Telecare, 17(6), 307-312 [2] McCurdie T, Taneva S, Casselman M Yeung M, McDaniel C, Ho W, Cafazzo J (2012) mHealth Consumer Apps: The Case for User-Centered Design, AAMI Horizons, Fall, 49-56 [3] Craven MP, Selvarajah K, Miles R, Schnädelbach H, Massey A, Vedhara K, Raine-Fenning N, Crowe J (2013) User requirements for the development of Smartphone self-reporting applications in healthcare, in Kurosu, M (Ed.): Human-Computer Interaction, Part II, HCII 2013, LNCS 8005, 36-45 The authors acknowledge the support of the UK Engineering and Physical Sciences Research Council through the MATCH Programme (EPSRC Grant EP/F063822/1) although the views expressed are entirely their own.

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