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Patient-Centered PHR Pulls Together Four Data Sources for Post-Market Surveillance of Medical Devices

August 12, 2018
by David Raths
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Can a patient-powered platform enable more robust and thorough post-market surveillance?

The Yale School of Medicine and Mayo Clinic are experimenting with a personal health record platform that allows patients to gather real-world data to share with researchers for post-market surveillance of medical devices.

Speaking to the NIH Collaboratory Aug. 10, Sanket Dhruva, M.D., an assistant professor of clinical medicine at the UCSF School of Medicine and a cardiologist at the San Francisco VA Medical Center, described some of the limitations of the current mechanisms used by the U.S. Food and Drug Administration for medical device surveillance and the potential for real-world evidence to help clinicians better understand the safety and effectiveness of devices.

Currently the FDA uses passive surveillance such as reporting of adverse events to the Manufacturer and User Facility Device Experience (MAUDE) database and does studies when safety concerns need to be investigated. Researchers at the Yale University-Mayo Clinic Center of Excellence in Regulatory Science and Innovation (CERSI) are seeking to complement that approach with real world data. They are conducting a demonstration projects for NEST, the National Evaluation System for Health Technology, which was established by the Medical Device Innovation Consortium and funded by FDA.

Dhruva said the best data sources would be prospectively planned and offer continuously updated longitudinal follow-up for a comprehensive set of clinically relevant outcomes. “Ideally it would include patient-reported outcome measures as well as patient-generated data and would integrate seamlessly with existing data systems,” he said.  

Both claims and EHR data sources are commonly used for device surveillance. But they have limitations of their own, he said. Claims data are ubiquitous but not collected for supporting research. They are complete only if people remain in the same health system, so there tend to be gaps in data. Also they have time lags in availability. “They cannot identify use of a specific medical device,” Dhruva added.

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EHR data offers very rich clinical information, but EHRs also are not designed to support research. The data is complete only if the patient remains in the same health system, so there may be many important gaps in data. “EHR data rarely includes patient-reported outcomes in a structured format,” Dhruva said. “Parts of patient-reported outcomes are in clinician notes or scanned documents,” he added. EHRs are rarely able to identify the use of a specific medical device.

In 2012, the FDA issued a rule requiring medical devices and packaging to have Unique Device Identifiers: However, there has been limited benefit because the UDI is unavailable in administrative claims data and EHR data, Dhruva said. “The UDI has a lot of potential to track devices and outcomes, but while we push for it to be better integrated in EHR and claims data, we can work on getting more real world data for medical device surveillance.”

The pilot project allows patients to provide their own outcomes (through short questionnaires and through synchronizing data from mobile health trackers) after they have received a procedure that utilizes medical devices. The Hugo personal health record aggregates data from four sources: EHRs, pharmacy portals, wearable devices  and patient answers to e-mailed questionnaires that become patient-reported outcomes.

(Hugo’s founder is Harlan Krumholz, M.D., a professor of medicine and epidemiology and public health at Yale School of Medicine.)

The study is following 60 patients for eight weeks after they undergo two procedures that use medical devices: the multiple devices (including sutures and stapler) used to perform bariatric surgeries (either sleeve gastrectomy or gastric bypass) in patients seeking weight loss and an ablation catheter when used in patients with atrial fibrillation seeking a return to sinus rhythm.

One goal is to test if the patients’ EHR data from multiple health systems can be synchronized into a research-ready database. (The Hugo PHR currently works with 600 health system portals. If patients have data with other providers’ portals, they can download Continuity of Care Documents and then upload them to Hugo, with research assistant help. Patients are being provided with syncable devices such as Fitbits to provide additional insights into their health and health outcomes. The study is also testing the feasibility of obtaining medication data from pharmacies. Patients who use Walgreen’s or CVS can log into their portals and download data.

Overall, the study is trying to answer the question of whether such a patient-powered  mHealth platform enable more robust and thorough post-marketing surveillance.

“Getting comprehensive longitudinal data “can only be obtained if the patients link and upload data from different health systems into the application,” Dhruva said. “We hope this is going to become easier through implementation of FHIR and Blue Button 2.0, but it is important that patients link or upload data from all the health systems from which they receive care.” He said combining that with patient-generated data should give clinicians a better understand of how they are doing in the post-procedure setting.

 

 


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Additionally, the system provided extensive and comprehensive reporting with data analytics showing where and to what extent response improvements were made, but also providing the information the hospital needed to better utilize the system and make adjustments to improve results.

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Humana Taps New Fitbit Connected Platform for its Members

September 24, 2018
by Rajiv Leventhal, Managing Editor
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Fitbit and Humana are expanding their partnership to help members adopt and implement healthy behaviors to help prevent and manage chronic conditions, officials from both companies announced last week.

Humana has selected Fitbit Care, a connected health platform for health plans, employers, and health systems that combines health coaching and virtual care through the new Fitbit Plus app. The new solution will now be the preferred health coaching solution for Humana’s employer group segment.

Through this partnership, which has been ongoing for about five years, officials noted, more than 5 million Humana members will have the potential to access Fitbit wellness solutions or health coaching.

The Fitbit Care health coaching solution combines Fitbit’s 11 years of experience helping consumers make meaningful behavior changes with the clinical knowhow of Twine Health, a coaching platform Fitbit acquired in early 2018. Coaches work with participants to create personalized care plans and connect with members through multiple channels that include in-app communications, phone and in-person meetings, giving people the flexibility to choose what works best with their lifestyle.

Humana, meanwhile, serves members through a comprehensive range of wellness programs and capabilities, such as Go365 and the Humana Employee Assistance Program (EAP), with the goal to help employers control rising costs related to worker health, such as increased healthcare consumption and lost productivity. Fitbit Care is the latest aspect of this endeavor.

“With healthcare costs and rates of chronic disease increasing, there is a clear need for innovative tools and services to help people make the lifestyle and behavior changes necessary to reverse this trend,” said Adam Pellegrini, general manager, Fitbit Health Solutions. “Expanding our partnership with Humana allows us to accelerate our common goal of helping more people get and stay healthy, and I'm confident that together we can help drive better health outcomes.”

Added Jeff Reid, Humana’s senior vice president of wellness solutions, “By adding Fitbit Care’s new health coaching capabilities, we can offer even more personalized, meaningful support to our members who are focused on specific health goals, such as smoking cessation or weight loss, or the management or prevention of chronic condition.”

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Who Will Watch the Apple Watch?

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Designing and deploying devices like the Apple Watch Series 4 is the easy part. The hard part is building systems of care that actually improve health based on the information supplied by technology.

Years ago, when I was a medical student, one of my mentors regularly told us to order a test on a patient only if we knew how the result would change the plan of care. This was his way of teaching us the difference between data and actionable information. I was reminded of this foundational wisdom as I read reports and was interviewed about the new Apple Watch Series 4 (AW4) with fall-detection and electrical heart-rate sensor capabilities. It’s clear AW4 will generate new data. It’s less clear how that data can be harnessed to improve health outcomes in the real world.

Health IT has been “Data-Rich, Information Poor” (DRIP) for decades. It’s essential that data from devices like AW4 be turned into useful, actionable information. So, hoping to gain additional insights on some possible practical applications of AW4, I called up my old friend and colleague Deepak Talreja, M.D., F.A.C.C., a practicing interventional cardiologist and experienced medical informaticist.

There is exciting potential in devices like AW4. They represent a significant step on the journey towards the Internet of Things (IoT) for healthcare. As Talreja noted, “Similar innovations have already reached the marketplace—with step-counting and biometrics of ‘Fitbit’-type wearable devices, CardioMEMS™ for heart failure, and the Alivecor Kardia portable phone peripheral that also offers an optional e-cardiology ‘over-read’ for an additional monthly fee.”

Talreja and I agree that the widespread deployment of a diverse array of devices that connect, communicate and collaborate to promote better health is inevitable. While this vision is full of promise for the long run, it will face many challenges and limitations in the near term. Ultimately the “Iron Triad” of people, process, and technology will determine the success of these efforts so, it’s worth thinking about AW4 from this perspective.

“The competition between consumer-driven wearables and medical-grade devices will test the limits of HIPAA privacy laws, medical-provider and subspecialist access, the willingness of providers to evaluate nontraditional data streams both during scheduled visits and after hours, and medicolegal laws and precedents,” Talreja said. For devices like AW4, he concluded, “One key will be to ferret out what measurables are both useful and interpretable by consumers.”

They will also test the reimbursement system since someone will have to cover the cost of all of this. The devices aren’t free. Providers are rightly reluctant to give their services away. It is unclear at this time who will pay for the device or services. Sure, some patients will pay out of pocket, but that’s not a scalable or sustainable approach.

The Limits of Technology

It’s important to be precise about capabilities when it comes to functions like electrocardiogram (ECG) production and analysis. AW4 is FDA-cleared to identify normal heart rhythms or signs of Atrial Fibrillation (AFib). Essentially, AW4 can tell if you are “fine” or should "get this checked out.” Also, it does not address other important, common and lethal cardiac arrhythmias like Ventricular Fibrillation.

AFib itself can be benign or lethal. Analysis based on the available FDA data suggests AW4 will have a positive predictive value of around 45 percent. This means more than half the time the ECG app flags a problem, it will be wrong. Throw in the expectation that the population of AW4 owners is likely to skew towards younger and healthier and the number of false positives will be even higher.

This raises the real possibility of needlessly scaring a lot of people and wastefully taxing an already overburdened healthcare system. Based on his experience with remote monitoring and consumer devices, Talreja points to theimportant implications of increasing utilization of primary care and subspecialty medical services, additional medical testing, and emergency room and urgent care visits by anxious patients who in some cases will be responding to monitoring artifacts.”

Interoperability with the rest of the health IT ecosystem is another big challenge. AW4 “interoperability” appears to be limited to production of a PDF. This will be highly limiting and potentially counter-productive. How will that PDF flow into the system of care in a timely and reliable manner? EHRs (electronic health records) are already overstuffed with PDFs which can be hard to find and are unstructured. Will this PDF be one more “needle” in that “haystack”? And who, exactly, is supposed to read and act upon these reports?

People and Process: Who is Watching the Watch?

It does no good to have devices like AW4 generating data if we don’t know what to do with it or don’t have processes in place to reliably respond. Designing and deploying devices like AW4 is the easy part. Building the systems of care that can act upon the information they supply will be much harder and essential if they are to have a significant impact on health.

And, this is a consumer-facing device so an effective system of care is highly likely to include the patient, their family, other caregivers in addition to traditional healthcare providers. It will not be easy to sort this all out into a reliable, scalable system. AW4’s fall-detection function provides an excellent window into these kinds of people and process challenges.

The AW4 app can detect when the wearer has fallen and send an alert. I’m a member of the sandwich generation. The idea that I could support my elderly mom in her efforts to live independently and safely by having her watch tell me if she has “fallen and can’t get up” is appealing.

But I have concerns about process and making the info actionable. What if I am out of range, busy, asleep or incapacitated in some way? Who is “watching the watch” and able to act if I can’t?  Those concerns are magnified if there are issues with sensitivity, specificity or if the device is prone to user error. There are also very basic “people” questions like, “Will Mom consistently wear the watch?”

The Cure for DRIP: A Population Health – AI Mash-up   

Talreja believes it’s feasible to build “a reliable, scalable and useful IoT for healthcare out of devices like AW4, but this will ultimately require a combination of population health and advanced analytics.” He’s right. As the number and variety of devices grows, the tidal wave of data they generate will have to be filtered for human consumption and action. If we don’t, we will just make DRIP worse.

For patients, there is the promise of AI-assisted interpretation and decision support that empowers them to better sort out what’s going on and what they should do. For providers, it is the promise of automated monitoring and notification—air traffic control as it were—to help them find and focus on the individual patients with serious problems. The addition of automated protocols for routine care will further reduce the burden on human providers while advanced decision support will assist them in dealing with complex situations even more effectively.

The Best Day or the Worst?

As several others have noted, upon hearing about the AW4, Ethan Weiss, M.D., a University of California, San Francisco cardiologist, tweeted, “I can’t figure out whether today is the best day in the history of Cardiology or the worst.” Talreja and I agree the answer to Dr. Weiss’s question is “Yes.” It will be some of both. Eventually, a well-designed IoT for healthcare comprised of many such devices will be a boon to better heath at lower cost. However, the combination of limited functionality, weak interoperability, low positive predictive value and lack of well-defined care process points to a rocky start and limited benefits at first.

Achieving meaningful success will be a challenge with many ups and downs and frequent reminders that turning data into actionable information requires serious attention to people, process and technology. Otherwise, it’s just more DRIP, DRIP, DRIP.

Dave Levin, M.D., has been a physician executive and entrepreneur for more than 30 years. He is a former Chief Medical Information Officer for the Cleveland Clinic and serves in a variety of leadership and advisory roles for health IT companies, health systems and investors. You can follow him @DaveLevinMD or email DaveLevinMD@gmail.com.

Deepak R. Talreja, M.D., F.A.C.C. is a practicing interventional cardiologist and medical informaticist. You can follow email him at  talreja@yahoo.com.

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