The history of medicine is littered with well intentioned actions that, upon more rigorous evaluation, failed to benefit and even harm patients.

Developing an evidence base to help guide the design and implementation of mobile health technology is critical.

The Medicine 2.0 conference is one of the leading venues for dissemination and debate of mHealth research and iMedicalApps is proud to be part of that mission.

To further our mission of promoting and disseminating mobile health tools that have positive impacts on the care of our patients, iMedicalApps will be presenting an award for outstanding research at Medicine 2.0.

We have selected our semi-finalists and, over a series of articles, will share their work and our perspectives on how they help advance the evidence base of mobile health. Here are the first three.

Apps4CPR: A review study of mobile applications for cardiopulmonary resuscitation training and support

Summary of Abstract:

This is a mixed methods evaluation of the quality and usability of mobile apps for resuscitation support and training available in the two largest mobile application stores (Apple App Store & Android Market). Mobile applications for CPR have been systematically collected via the search interfaces of the app stores. Two emergency physicians reviewed these apps in terms of criteria. They examined functionality, conformity with regulations, target group and language. In addition, the experts provided a quality rating on an ordinal scale from 0-10.

Furthermore, each app was evaluated against three expert criteria:

  • Training Features
  • Conformity to BLS Guidelines
  • Integrated Emergency Call Feature

Approximately a third of the apps (n=16) follow current guidelines. Nearly 75% of the tested apps (n=34) include emergency support, and 13 offer direct access to an emergency call. Only 5 apps show high usability and appealing hedonic quality for laymen.


Mobile apps which aim to provide knowledge or some degree of training in CPR should be appropriately validated given the results of this study. Well intentioned individuals using these applications may find that they only have a 5/34 chance of downloading an app suitable for a layperson. Further research about the design strategies that can make these types of apps successful is needed. In addition, the abstract reinforces the need for guidelines to ensure appropriate content in mobile medical apps.

Diabetes During Pregnancy: Effect of mHealth Remote Monitoring on Blood Glucose Control. A randomized controlled trial

Summary of Abstract:

This is a small RCT which piloted a peripartum diabetes mHealth remote monitoring system based on a smartphone platform. BG readings from a Bluetooth-enabled glucometer were automatically transmitted by the smartphone to application servers that responded with self-care messages based on pre-defined care paths. 99 pregnant patients were recruited with gestational diabetes mellitus (GDM) and type II diabetes mellitus. GDM subjects in the intervention (mHealth) group demonstrated significantly better adherence to the BG measurement schedule (3.7 vs. 3.3, p=0.014) and better average BG measurements (5.9 mmol/L vs. 6.1 mmol/L, p<0.0007).


The results of this small RCT highlights the effective use of technology to improve outcomes for diabetic populations. It also highlights the potential uses of connected Bluetooth technology for management of chronic health conditions. There are questions to be asked, however, related to the small sample size and potential cost of rolling out bluetooth devices to the wider diabetic population. It will also be interesting to see what observations they provide from this experience that could improve system design.

Mobile Health Apps: Evidence-Based User Interface Development

Summary of Abstract:

This is a rigorous investigation into the efficiency, accuracy, and satisfaction with 6 separate user interfaces for recording health data using handheld devices. A 150 participant user panel was recruited and asked to record several vital sign measurements. The results showed that the numeric keyboard took significantly less time (p-value < 0.001 Kruskal-Wallis) than the other models to enter measurements. In addition, they observed significant differences in data entry accuracy between the different models with the numeric keyboard being among the better performers.


The success of most mHealth interventions, particularly those that utilize apps, hinges on their usability. Apps that are hard to use can expect to be rapidly discarded by patients. We were struck here by the rigorous testing applied by these researchers to a small yet critical component of app design. This study applies appropriately robust methodology to evaluate which model is most appropriate–the results of which will have far reaching implications for medical app development. It is a great example of the kind of thoughtfulness that needs to be applied to medical app design in the future.