Five Ways to Evaluate Mobile Medical Apps via Research


There are many barriers to the adoption of health, fitness, and medical apps. A recent article summarizing the report from PWC’s Global Healthcare division states that adoption of mHealth technologies will lag consumer demand. I wholeheartedly agree with David Levy, MD (global healthcare leader of PwC when he said “Despite demand and the obvious potential benefits of mHealth, rapid adoption is not yet occurring. The main barriers are not the technology but rather systemic to healthcare and inherent resistance to change.”  Relevant to both of these is the lack of demonstration of clinical efficacy of medical apps. Few medical apps have obtained FDA approval. The demonstration of clinical efficacy and/or cost-savings is a key ticket to reimbursement which itself is significant with regards to adoption.  Proof that positive clinical efficacy trials lead to reimbursement is evidenced by Sotera Wireless’ ViSi Mobile vital sign monitor and WellDoc’s DiabetesManager.  Trials take time, are costly, not necessary unless falling under FDA requirements (yet to be announced), and not seen as important for business development by many app developers. Here are a few ways in which the trials might be done to demonstrate to payers, providers, and other stakeholders that medical apps should be adopted.

1.    Crowdsourced research studies. While traditional clinical studies are the usual pathway to the healthcare marketplace for products like medical devices, crowdsourced health studies  are attractive for patient engagement necessary tools like medical apps.  Online health communities like wegoHealth, patientslikeme, 23andme, and others are groups of patients and caregivers with common diseases and concerns who might participate in crowdsourced studies. The merits and drawbacks of crowdsourced health studies have been discussed in more detail in a previous post.

2.    Academic institutional-based studies.  Medical schools are developing their own apps.  There are multiple reasons for this phenomenon.  Johns Hopkins University School of Medicine has been developing apps as well as  performing clinical efficacy studies on selected health apps. There has been long-time collaboration between industry and academia.  I do not see why medical apps and other digital health technologies cannot follow this path.

3.    Feasibility studies.  As adoption has been slow and not many apps are undergoing clinical trials, perhaps a good first ‘baby step’ is to conduct feasibility studies as Happtique is performing now on its medical app prescribing program called mRx.  The study will not evaluate efficacy of apps prescribed by physicians but will evaluate how many times physicians prescribe the app and how many times patients fill them. While feasibility studies are not efficacy studies, they do spread awareness of the technology of prescribing apps, possibly improve patient-physician relationships, familiarize the parties involved with the process, and expose patients to what apps might do for them.

4.    Comparative effectiveness studies.  Because of how many apps there are within specific areas of health and medicine, they might lend themselves to open label trials without necessarily a standard care study arm.

5.    Other unique research study design methods.  In August 2011, scientists, policy makers, technologists, health professionals and others gathered at the mHealth Evidence Workshop to discuss new and unique methods of evaluating efficacy of mHealth technology. The diversity of technologies, study populations, and the rapidly changing landscape of technology lends itself to emerging ways of evaluating them.

Most stakeholders in the healthcare arena agree that apps will play, at some point in time, a significant role in disease prevention and treatment.  Most apps will not fall under the requirement for FDA approval. Certification standards for usability, privacy, safety, and content have been developed by Happtique for their certification program which will begin soon.  Though this is itself a huge step in the evaluation process, these standards do not assess efficacy, leaving a large void.  Efficacy trials will be welcome by all, and need not be the same old clinical trials producing ‘evidence-based’ recommendations which have been the subject of recent attention.

About these ads

About davidleescher

David Lee Scher, MD is Director at DLS HEALTHCARE CONSULTING, LLC, which specializes in helping digital health technology companies, their partners and clients. As a former cardiac electrophysiologist and pioneer adopter of remote patient monitoring, he is uniquely qualified to address both clinical and operational concerns of clients. Scher was Chair of Happtique's Blue Ribbon Panel which established standards for certification of medical apps in the categories of safety, operability, privacy, and content. He is a well-respected expert in mobile and other digital health technologies and lectures worldwide on technology and its impact on patients and healthcare systems.
This entry was posted in clinical trials, digital health, FDA, healthcare economics, Healthcare IT, medical apps, mHealth, mobile health, smartphone apps, technology and tagged , , , , , , , . Bookmark the permalink.

3 Responses to Five Ways to Evaluate Mobile Medical Apps via Research

  1. In this fledgling field of study, knowing what to measure and how to measure it can be a long drawn out process of trial and error. Or you can seek out experts who have already published and there aren’t very many of those people out there and even fewer who are willing to share due to their current competitive advantage of being ahead of the pack. My approach has been to publish and share with just about anyone who will listen and I still find that most entrepreneurs, doctors and academic researchers would rather blaze their own trail. Call it naive or ego. I’m not sure. Many translational mHealth trials are published at http://type1techventures.com My hope has always been to accelerate by not studying that which has already been studied yet I know now that runs counter to human nature and the clinical research machine which likes to get paid for redundant studies loaded with limitations, gaps and poor design which of course then beget their next study.

  2. gene loeb, Ph.D. says:

    It is sadly true that while mobile health applications could help many, their adaption is very slow. This response explains possible reasons: demand and the obvious potential benefits of mHealth, rapid adoption is not yet occurring. As the response explains: “The main barriers are not the technology but rather systemic to healthcare and inherent resistance to change.” But an additional reason is the lack of publicity on their use and lack of a central way to obtain apps. There are also competing apps for various functions makingn their selection difficult. One solution is nationally publicized demonstrations, perhaps by NIH and publicity by them of the ongoing research. In the area of gerontology, the need for these apps is especially needed. Other articles and comments such as these go far to speeding up the use of mtech apps.

    • Gene, Thanks for your thoughts. Yes, awareness is necessary, and as stated this will derive from good apps proven with efficacy trials. Regarding multiple apps for a single purpose, this sector like most in a free economy will drive competitors to develop better apps.

Leave a Reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out / Change )

Twitter picture

You are commenting using your Twitter account. Log Out / Change )

Facebook photo

You are commenting using your Facebook account. Log Out / Change )

Google+ photo

You are commenting using your Google+ account. Log Out / Change )

Connecting to %s