Developing Medical Apps and mHealth Interventions

This book provides a practically applicable guide to designing evidence-based medical apps and mHealth interventions. It features detailed guidance and case studies where applicable on the best practices and available techniques from both technological (platform technologies, toolkits, sensors) and research perspectives. This approach enables the reader to develop a deep understanding of how to collect the appropriate data and work with users to build a user friendly app for their target audience. Information on how researchers and designers can communicate their intentions with a variety of stakeholders including medical practitioners, developers and researchers to ensure the best possible decisions are made during the development process to produce an app of optimal quality that also considers usability.

Developing Medical Apps and mHealth Interventions comprehensively covers the development of medical and health apps for researchers, informaticians and physicians, and is a valuable resource for the experienced professional and trainee seeking a text on how to develop user friendly medical apps.

Auteur

Dr. Alan Davies is a lecturer in Health Data Sciences at the University of Manchester in the Division of Informatics, Imaging and Data Sciences. Alan has a background in Computer Science (PhD) and Nursing Science (BSc) and has previously worked as a software engineer and app developer in industry. Alan also worked in interventional cardiology, assisting with routine and emergency cardiac procedures where he authored several medical textbooks on electrocardiogram (ECG) interpretation. More recently he has worked for the University of Manchester as a Research Software Engineer (RSE) and Data Scientist prior to becoming a lecturer. He delivers modules on the MSc in Health Informatics joint award delivered by UCL and the University of Manchester, where he is a module lead on the "Usable Health Systems Design" module and the "Modern Information Engineering" module. He also teaches on the MSc in Health Data Science on various modules, including "Understanding Data and Decision Making" and "Health Information Systems and Technologies". Alan's research is focused on mHealth interventions and how patients interpret medical data. Alan was a Data Science fellow at AstraZeneca, as well as a member of the Universities Research Ethics committee (UREC). Alan completed his PhD in the Interaction Analysis and Modelling lab at the University of Manchester using eye-tracking methods to examine how clinicians interpret ECGs.

Dr. Julia Mueller is a Research Associate in the Medical Research Council Epidemiology Unit at the University of Cambridge. She works within the programme on Prevention of Diabetes and Related Metabolic Disorders in High Risk Groups. Prior to this role, she worked as a Lecturer in Healthcare Sciences in the Division of Population Health, Health Services Research and Primary Care at the University of Manchester, leading a course unit on Digital Public Health on the Master of Public Health programme. Much of her research relates to digital health, with a particular focus on health-related behaviour change interventions such as mobile apps for chronic disease management. She is also a strong proponent of patient and public engagement and has organised and participated in various events and initiatives to help patients become involved in research and to disseminate research findings to members of the public. Julia completed a BSc in Psychology at the Georg-August-University in Goettingen, Germany, and an MSc in Health Psychology at the University of St Andrews. Her studies piqued her interest in the links between psychological and physical well-being, and in the potential of Web-based interventions for improving health. In 2018, Julia completed a PhD research project at the University of Manchester about the role of Web-based information in help-seeking of those worried about lung cancer.

Contenu
Introduction to mHealth.- Project development methodologies, management and data modelling.- Designing an mHealth intervention.- Application development and testing.- Data collection, storage and security.- Feeding back information to patients and users with visualisations.- Usability testing and deployment.- Designing an mHealth evaluation.- Data analysis methods.