Unlocking the value in patient-generated health data

This and other such memorable quotes were among my many takeaways from the HIMSS annual conference last week in Orlando.

Along with the increase in healthcare consumerism, there is a growing awareness among health systems of the need to involve patients in their medical care. An important aspect of enabling that is to harness the continuous stream of data from wearables, sensors and other internet of things (IoT) devices that is now referred to as patient-generated health data or PGHD. PGHD can provide valuable insights to clinicians in population health management (PHM) and personalized medicine.

Old wine in new (smartphone-enabled) bottles

The notion of PGHD is not new.

Every time a patient shows up at a physician’s office and starts describing symptoms, the doctor has started gathering PGHD. Hitherto, this verbal exchange would form part of the basis for the doctor’s diagnosis and would likely be recorded in the doctor’s notes from the visit.

However, technology has enabled patients to communicate with doctors more frequently, as opposed to the episodic mode of interaction characterized by the physician office visit. The growing use of smartphones, remote monitoring devices and mobile health applications provides patients with new ways to share data with physicians. This allows physicians to develop more comprehensive views of patients — especially of how patients are doing in between office visits, which can significantly improve outcomes in chronic disease management.

It’s important to note that PGHD isn’t just clinical data such as health and treatment history; it is also social determinant data such as lifestyle, which enables the physician to get a holistic picture of a patient. It’s also important to know that physicians have generally resisted PGHD in their diagnosis and treatment decisions. The reasons are many: data overload, incomplete or unreliable data, privacy and security concerns, and so on.

Recognizing the value of PGHD and the role of technology in advancing patient engagement in healthcare, the Office of the National Coordinator of Health IT (ONC) started developing a policy framework in 2015 to assess the opportunities for improving health outcomes through the collection and use of PGHD.

As a part of a two-year demonstration of the potential benefits of PGHD, the ONC contracted with consulting firm Accenture to develop a white paper and simultaneously carry out demonstration projects with health systems. One of the projects is with Sutter Health, a large health system in northern California. The highlights of the project to date were presented at the HIMSS conference.

PGHD and the Sutter Health pilot

A key consideration for the pilot project was that the technology had to be in the clinical workflow — a theme which was echoed in many other sessions at HIMSS as critical for success, given the work overload that most physicians face today. Partnering with Validic, a digital health platform designed to collect and deliver personal health data from mobile applications securely into electronic health record (EHR) systems, Sutter Health was able to set up a workflow to integrate PGHD continuously with EHR data. Patients receive periodic dashboards incorporating this data. Physicians, in turn, get an enhanced dashboard with advanced interpretations of the same data, which enables a much richer discussion with patients around their care management programs. The patient dashboard was noted as one of the big motivators for patients to get engaged in their own healthcare. 

Data privacy, which has been one of the barriers to the use of PGHD, is addressed by  the Validic platform, which is designed to ensure a secure and private data exchange between doctor and patient.

An additional benefit of the program is that the increased understanding of patients enables a dynamic pull between care managers and patients to identify cases that could turn critical and stratify risk for population health management. 

Though the Sutter Health pilot hasn’t been operational long enough to generate any meaningful benefits, initial results indicate that new use cases are emerging beyond chronic disease management.

The opportunities and challenges for PGHD

An ongoing concern in the post-EHR world has been the risk of physician burnout due to high levels of documentation, accompanied by alert fatigue from clinical systems. Done right, PGHD should not create data overload; possible options could be to have the additional dashboards delivered once a day or some other optimal interval.

There is no question that the increasing body of data available on patients is enabling hospitals to take more risk and improve health outcomes, however there is no easy way today to move data between systems. Data interoperability remains a problem, because much of the EHR data is locked up in proprietary vendor platforms. The emergence of Fast Healthcare Interoperability Resources (FHIR) standards supported by consortia such as the Sequoia Project is expected to improve data interoperability in the near term.   

One of the biggest challenges for innovation in healthcare is the lack of a reimbursement model to support new technology solutions. Creating a system of incentives becomes necessary in this context. In light of the progression toward value-based care (VBC), adoption rates for new technology solutions that demonstrate ROI are expected to increase in the next 18 to 24 months.

From a healthcare policy perspective, there are other initiatives under way that could provide a boost for PGHD. The federal government’s Stage 3 guidelines for meaningful use (MU) of EHR technology, which are set to go into effect in 2018, require hospital EHR systems to have the ability to collect PGHD from nonclinical sources. Under the newly proposed Medicare Access and CHIP Reauthorization Act (MACRA), MU is one of the criteria for merit-based incentive payments and this might further boost PGHD. (However, the fates of MACRA and MU Stage 3 are unclear under the new administration at this time.)

The next stage in all of this is cognitive analysis. Continuous data on patients will help develop predictive analytics models based on advanced algorithms that can be developed by training historical data. As IBM CEO Ginni Rometty put in in her opening keynote at HIMSS 2017, the future of healthcare is cognitive, and the most critical healthcare insights will be from the people who develop it using cognitive computing platforms such as Watson Health. Rometty urged health systems to “play offense” and seize the opportunities ahead. PGHD may just be the new game-changer.