Too Many Dashboards, Not Enough Insight: How Companies Can Build Remote Patient Monitoring Tech

Too Many Dashboards, Not Enough Insight: How Companies Can Build Remote Patient Monitoring Tech Jennifer Bae and Ami Bhatt

With the rise of digital health technology, the ability to track a host of health indicators has been incorporated into wearables and medical-grade devices. The odds are great that many readers of this article have used this information in a recent doctor’s visit. This is called remote patient monitoring (RPM) which CMS defines as the “use of digital technologies to collect health data from patients in one location and electronically transmit that information securely to providers in a different location.”

Many RPM companies are operating under the assumption that for their signal to be used, they need to build their own user-friendly dashboard for accessing that information. Despite the dollars in creation and marketing dedicated to the visualization of data, RPM adoption remains limited largely because of the underemphasis on shared infrastructure.

To build remote patient monitoring technology for ready adoption, repetitive data streams must be avoided. To be successful in clinical adoption, we offer technology companies the following three recommendations.

Simplify data streams.

First, understand the realities facing their clinician end users. The average American clinician already interacts with several different systems to treat an individual patient, including the electronic health record and clinical imaging systems, before considering the information collected from a remote patient monitoring system. They are often required to see a high number of patients in a day to meet relative value unit (RVU) requirements while faced with the inefficiency of stitching together information in real time from the systems they already must use.

Add to this the pressure of practicing medicine with pandemic-induced staffing shortages, there is a real need to make the practice of medicine simpler and more streamlined. Adding a unique dashboard for each indicator could worsen the experience for these increasingly burnt-out clinicians.

Curate visualization to what is needed.

Second, think critically about what you are measuring and why. Ensuring that data capture mirrors clinically relevant measurements which are actionable will drive clinical adoption. Data points may be specific to the underlying chronic condition being managed and only useful in specific contexts. Pulse oximetry has limited usage outside of individuals with significant lung disease or other specific entities. Similarly, individuals with no concerns for arrhythmia may not benefit from constant heart rate monitoring, which may lead to over-monitoring and health-related anxiety.

There is an opportunity to simplify the amount and type of information presented to clinicians before and during a visit to provide the most salient information for the patient and their specific condition.

Integrate information into a single screen.

Lastly, be sure to integrate. Consider that the best dashboard is probably the one that most clinicians are using. The driving goal in collecting patient-generated data—physiologic, social determinants and patient-reported outcomes—from a variety of sources is to create a complete picture of that patient’s current state. That cannot be successful in a series of disjointed snapshots. Instead of entering this crowded space, buying or partnering with another more established player may be a better option for companies with remote patient monitoring capabilities.

There is an increasing trend toward mergers and acquisitions in the healthcare delivery space. Amazon’s recent sunsetting of Amazon Care and purchase of One Medical is a perfect example of large companies purchasing solutions in the form of other entities. Health systems are making investments in data infrastructure through the likes of Health Catalyst and Carta Healthcare, among others.

Similarly, there are several companies (including Myia Health and HealthPals in addition to the EMR companies) built with an eye toward data visualization at the patient level that can integrate with the electronic health record. Startups need to determine how they can interact with those tools to be a meaningful participant in patient-centered care delivery.

Conclusion

A better user experience does not overcome the challenge of having too many dashboards. While interoperability challenges remain, it is within our reach to ensure that novel companies whose strength lies in collecting information at the patient level think about not only allowing but actively driving data transfer and data usability across products.

Simplifying data streams, curating visualization to the need at hand and integrating that information into a single screen will yield better care and clinical adoption. When caring for a patient, the clinician end user just wants a singular picture of the human being in front of them.

Photo: Tajuddin Molla, Getty Images