Latest articles in Medical Informatics

Alexandra Griessbach, et. al.
Published on 08.09.2018
Alexandra Griessbach
+2
Christophe Gaudet-Blavignac, et. al.
Published on 08.09.2018
Christophe Gaudet-Blavignac
+3
Christophe Gaudet-Blavignac, et. al.
Published on 08.09.2018
Christophe Gaudet-Blavignac
+3
Katherine Blondon, et. al.
Published on 01.01.2017
Katherine Blondon
+3

Cardiovascular disease management, especially after an acute event, requires consideration of cardiovascular risk factors, which are generally lifestyle habits. Current implementation of recommended care is suboptimal, due in part to the difficulty of implementing and maintaining health behaviour changes. mHealth apps offer new approaches to support behavioural changes, in particular with the use of gamification strategies. These strategies have the potential to help maintain engagement over time. Reviews of current health apps that use gamification strategies show low integration of theoretical behavioural models in app design, and low use of gamification for cardiovascular self-management apps in general. We propose the integration of gamification strategies in a validated behaviour-change model, based on a patient survey and focus group. This model can be used to design a future smartphone app to support self-management of cardiovascular disease. 

Jean-Paul Calbimonte, et. al.
Published on 01.01.2017
Jean-Paul Calbimonte
+4

Research in the healthcare domain requires the collection of important and exhaustive datasets in order to validate a scientific hypothesis, or to assess the effectiveness of a treatment, technology, medicine, or procedure. The data acquisition phase for this type of work requires an often under-estimated amount of time and effort, while needing to maintain high quality standards for the entire process. Many of the tasks associated with data acquisition are often carried out manually, resulting in error-prone procedures, hand-transcription, inaccuracy, and time delays to produce a usable dataset. This paper presents MedRed (medical research data acquisition platform), an interface  and a service designed to facilitate the data acquisition process for researchers in the healthcare domain, and using REDCap software for data capture. This service is available first of all to all scientists at the HES-SO (University of Applied Sciences and Arts Western Switzerland) schools in Switzerland, and is partially supported by the Swiss universities’ CUS-P2 programme.

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