Reality Check on Integrating Remote Patient Monitoring Data into Clinical Workflow

July 6, 2015
Sometimes the enthusiasm about wearables and home monitoring can get ahead of the current capabilities of the health system. It is worthwhile and even refreshing to hear about the frustrations involved in attempts to set up such systems.

The capability to gather data from patients’ personal digital devices and from remote monitoring systems set up in the home holds out great promise for supplementing the data clinicians get from sporadic office visits.

But sometimes the enthusiasm about wearables and home monitoring can get ahead of the current capabilities of the health system. It is worthwhile and even refreshing to hear about the frustrations involved in attempts to set up such systems. They provide a reality check and a reminder that interoperability issues can limit success.

The title of a recent paper published in the Journal of Patient Centered Research and Reviews tells the story: Barriers to Implementing and Disseminating an Intervention to Improve Hypertension Control With Home Monitoring and Uploading of Data Into an Electronic Health Record.”

The CONtrolling Disease Using Inexpensive Technology (CONDUIT) study, funded by the Agency for Healthcare Research and Quality (AHRQ), was designed to test an approach to monitoring and managing hypertension that could be easily and widely disseminated and scalable to self-monitoring of other conditions.

Led by Barry Saver, M.D., M.P.H., associate professor of family medicine & community health at the University of Massachusetts Medical School, the randomized control trial tested whether an intervention consisting of self-monitoring of blood pressure (BP) and a feedback loop involving nurses and primary care providers could improve control of hypertension in patients with uncontrolled hypertension.  Rather than embedding the intervention in a proprietary EHR, the researchers used the free Microsoft HealthVault platform to receive participants’ BP readings and developed an interface to transmit HealthVault data into the EHR. Participants who could not upload their data from home could upload data at clinics.

But the researchers soon encountered IT issues that created barriers to implementing the project. “We designed it to use Microsoft HealthVault as an intermediary for sending home BP readings to the EHR to make it as EHR platform-independent as possible,” they wrote. “However, it became clear that neither Omron, the manufacturer of the BP monitors we used, nor Microsoft had envisioned our use cases.”

The researchers noted that substantial effort was required to develop the HealthVault-EHR interface, including custom programming to poll HealthVault for BP data and periodically send messages to nurses summarizing the patient-uploaded data.

They encountered other barriers:

• The BP monitors lacked unique device identifiers.

• Neither the devices, HealthVault or the EHR validated date/time data.

• Software changes by any of several entities caused data flows to break and required frequent revision of patient instructions.

• Protected health information protection in clinic-based uploads proved challenging.

• Patients and staff expressed satisfaction when the system worked, but had limited tolerance for software failures. Most clinicians supported the system, but would have greater enthusiasm if patient-generated BP readings were considered in HEDIS scoring.

They encountered enough problems that they had to curtail clinic-based uploading. Final enrollment was 196 persons, about half of the target of 400. Three-fourths of participants chose to upload data from home and one-fourth at their clinics. Among the 147 participants completing an exit interview, there were non-significant greater decreases in systolic BP (3.6mmHg, p=0.16) and diastolic BP (1.2mmHg, p=0.5) among those randomized to the intervention.

“When the CONDUIT system worked as designed, it was well-accepted by patients and providers, but the various “moving parts” under control of different organizations led to multiple challenges and frustrations,” the report noted. “For similar interventions to be successful, hardware and software vendors must consider a wider range of use cases in their design processes.”

While noting that some health systems are indeed finding success deploying remote patient monitoring (RPM) systems, a December 2014 paper on the HIMSS web site, adds to the list of challenges the CONDUIT researchers found. “Intelligent data filtering is necessary, so applying the ‘quantified self’ concept to present unlimited physiologic data back to providers is incompatible with large health systems’ workflows,” wrote authors Alisa Niksch, M.D.; Steven Davidson, M.D.; and Brian Rothman, M.D.

“Data analytics providing risk assessments, condition identification, and intervention recommendations are lacking, owing to both a paucity of integrated platforms and algorithmic regulatory requirements when treatment modifications are recommended,” the HIMSS researchers noted. “Validation and verification of patient-provided data is another system challenge, as verification of patient identity is crucial in ensuring both accuracy and security.”

They added that most institutions that implement digital health and remote patient monitoring systems rely heavily on in-house IT specialists. For others, external support and additional software integration services are costly and present a wide range of technical challenges. The CONDUIT study reinforces that point because the researchers were trying to develop an approach that was inexpensive and reproducible.

Looking at it in a positive light, we are still in the first inning of this game, and these challenges just present more opportunities for digital health entrepreneurs to solve.

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