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 next three (for the first three, read here).
Smarter Hospital Team Communication: Smartphone Group Text Messaging Improves Efficacy, Workflow, and Provider Satisfaction
Summary of Abstract:
In this study, the investigators tackle the challenge of inefficient communication within healthcare teams utilizing a smartphone based platform called Medigram. In this randomized, controlled cluster study at Stanford Hospital, three inpatient teams were assigned to use either Medigram plus standard communications or just standard communications. Outcomes were based on survey data. In the assessed domains, the smartphone based platform was rated significantly more effective in enabling clear communication, efficiency, integration into workflow, and patient discharge management. Analysis for free response questions also yielded insights into which aspects of the platform users found particularly useful with ease of use and group texting being among the most commonly cited. One key limitation identified was the lack of connectivity in certain locations.
Given the increasing attention being paid to how healthcare teams communicate, this study is quite timely. That the results are entirely based on subjective assessments does limit what we can say about efficiency and efficacy improvements. Nonetheless, the insights garnered here are interesting and very relevant in terms of guiding not only further iterations of this platform but also other communication tools. For example, the insight that the group texting feature is highly valued would be important to consider going forward. And though subjective, there is value to the perceived benefits among team members who felt communication is improved.
User Profiles of a smartphone application to support drug adherence – Experiences for the iNephro Project
Summary of Abstract:
Adherence to increasingly complex medication regimens is a major challenge. iNephro is an application that was released in 2010 aimed at improving patient compliance with therapy. In this investigation, the researchers share insights gleaned from usage data and surveys collected from the cohort of patients using the application from 2010 to 2012. Usage data was collected on 11,688 patients and surveys from 2,279 users. Of all users, 30% used the application once a week for at least four weeks and 30% used it for at least 12 weeks. The majority of patients, based on the surveyed subset, had cardiovascular disease (75%); a significant number had a history of transplantation, cancer, renal disease, and diabetes (13%, 9%, 7%, 7% respectively). Respondents were majority male (68%), a mean age of 44, and most were on fewer than six medications (68%).
Patients, particularly elderly patients, with only one medical problem are few and far between. As such, promotion of medication adherence is critical. While this investigation does not validate apps as an effective platform for this purpose, it does provide insights into the audience for the application and usage. Particularly striking is the apparently infrequent use of the application; one would imagine that a drug adherence app would need to be used daily at least to be successful. Also striking were the insights into the patient population using the app, particularly the relative over representation of transplant patients in the respondents. While what is presented in the abstract is limited and certainly prone to several biases, we hope that it is a teaser to a much more in depth and detailed presentation at Medicine 2.0 – this kind of data could have far reaching impact on future designs of medication adherence interventions.
Summary of Abstract:
In this study, the investigators utilized the accelerometer within the iPhone 4 to design a smartphone based version of the popular clinical assessment of frailty known as the “get up and go” test. Using a group of frail and healthy elderly patients, they conducted this test and collected a series of kinematic data points using embedded technology in the iPhone. From this they analyzed which combination of variables best distinguished between the two populations. Ultimately, they designed an algorithm using acceleration, angular velocity and displacement that accurately distinguished between the two populations more effectively than the traditional metric of time alone.
While there is significant attention being paid to smartphone peripherals, there is a great deal of untapped potential in the capabilities already embedded in these devices. This effort is a great example of an innovative application of the existing device capabilities to capture clinically relevant data, in this case frailty. One could imagine a number of potential applications both in the clinic and outside the clinic. It’s unclear whether this algorithm was both designed and tested in the same population; if so, it would be important to assess its efficacy in a second population of patients.