Medical Research Institutions Driving mHealth Innovation

Mony Weschler

The clinical trials industry is currently in the midst of examining mHealth technology pilots, however, many of those pilots have vanished without reporting on actual outcomes, and whether the technologies were deployed across biopharmaceutical organizations. The healthcare industry, however, has developed mHealth piloting infrastructures that have led to full organizational deployment. In this interview, Mony Weschler, Chief Technology and Innovation Strategist at Montefiore, will elaborate on his experiences with successfully piloting and deploying mHealth technologies.

Moe Alsumidaie: Healthcare reform and the payer system are spawning new operational models for hospital systems. Can you elaborate on how this is impacting your need to innovate via mHealth? Will mHealth ultimately replace clinical staff?

Mony Weschler: Montefiore’s leadership has been visionary and they positioned us well for emerging payer models. Part of the challenge in offering healthcare services in the Bronx was that fee-for-service wasn't a terrific model. So, in the mid 90’s, Montefiore created our Care Management Organization (CMO) to deliver a population health model, which focuses on cost savings through patient engagement and patient-centric initiatives, and we’ve been able to successfully and efficiently manage close to 500,000 lives. In many ways, we are referenced as the model to follow for the new payment schemes.

Our model takes a lot of resources and technology working in synergy to manage that type of a population. What's different is that we built up to it and now our care management organization has grown to thousands of care managers--clinical individuals that are managing almost 500,000 lives. So ultimately you need a resource that is focused on managing the population whether in the acute care setting, the primary care setting, the urgent centers, the clinics and even managing the patients when they're outside of our health system, but, that can be made scalable by incorporation the right mHealth technology.

MA: Can you expand on how growth pressures are influencing the need for you to innovate via mHealth?

MW: We have grown the treatment of our patient populations over the years, now the pressure is to get to one million patients. We need to manage almost twice as many resources, however, we cannot just double the resources; it is too costly, and is not scalable. So, to make this scalable and sustainable, we use mHealth technologies to help care managers focus on the right patients at the right time. mHealth initiatives do not replace the staff we have in place, but the staff need to be provided with the right tools and resources so they can continue to do a better job with more patients.

MA: Please describe how you pilot and demonstrate the impact of innovative mHealth studies on your patient populations before deploying the technologies across the board.MW: Our philosophy involves ensuring that the mHealth technology we’re deploying provides patients with a user friendly experience, and whether the pilot generates successful outcomes. Our technological infrastructures at Montefiore make running pilots much easier, as we have the ability to reach out to and be in touch with a large number of patients. Moreover, our infrastructure enables us to incorporate technology pilots into our workflows, such as funneling patients to the right care manager when appropriate or even helping care managers prioritize at-risk patients. When presenting a pilot to management, I highly recommend a process that outlines to the stakeholders what you're trying to achieve. Have very clear goals.

Naturally, we submit our studies to the IRB and obtain approval before executing them, we provide management with realistic timelines, such as three to nine months, depending on what we're trying to study, and measure and record as much as we can about the study. After the study, there has to be a review process to check if we have achieved those outcomes.

If you are measuring things like appointment adherence, then you need to be able to have all the data around appointments and make sure that you can see that you are comparatively making an impact based upon all the interventions, and that you are moving the needle with your newer intervention. In terms of measurement frequency, you cannot wait until the end of the study. You have to measure the points every two to three weeks, depending on the length of the study to make sure that everything is working as it should, optimizing the technology as you go; otherwise you'll find surprises at the end of the study. We use a dashboard that we built that records a lot of these outcomes, and gives us a visualization layer, so that we can better track changes in outcomes.

MA: What are the common challenges that you face during pilot execution?MW: One of the common challenges we face involves non-technological aspects, such as deployment and onboarding. We learned that it is critical to monitor the data on a regular basis, so that you can improve the chances of success. In one of our studies, we were able to see very early in the process that onboarding was an issue, because we set ourselves to enroll a cohort of 500 patients, but, discovered three to four weeks into the study, that only 25% of the patients who were receiving intervention were on-boarded. If we didn’t monitor that data and didn’t do anything about the onboarding issue, we would have gone through four months of the pilot and our data would have not been valid from the get-go. So, the technology might have looked like it failed when it actually was not failing.

MA: Can you provide an example of a successful mHealth program that you recently deployed? What were the outcomes?MW: One of our pilots involved measuring wellness activities with children and families in the Bronx, and we deployed the pilot through school programs. The pilot gave us some real keen insight about patient activity and performance in different age groups (i.e., first graders versus 12th graders). The pilot also gave us insight into the percentages of the class that are interacting and doing assigned exercises correctly as well as their performance based on the sociodemographic groups.

Our vision is to effectivity hand out activity monitors to children in the Bronx and build a social media experience around it. So, not just getting the kids to exercise in school, but also to try to change behavior down the line to treat the obesity issue and pediatric diabetes problem. We are trying to test if we can get kids to be more active, have internal competitions between schools and use and vet on their competitive edge to get them to be healthier, less dependent on medications, and ultimately prevent obesity and diabetes. Correspondingly, the detailed data generated from mHealth will allow us to provide very compelling evidence that demonstrates benefits and potential outcomes, which can be used to acquire larger grants, and provide justification why we need to buy these devices and deploy exercise programs for all children in schools.