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The adoption of remote patient monitoring – technology that enables monitoring of patients outside of clinical settings – is blocked by the fee-for-service payment model.

How To Increase The Value Of Remote Patient Monitoring

Remote patient monitoring received a needed push from the pandemic crisis, which has accelerated its adoption. As a component of telehealth, remote monitoring enables the recording of vital signs and other biometrics to extend telehealth beyond video visits. But implementation and payment are still challenging.

A recent article on remote monitoring accuses this new technology of exacerbating physician burnout caused by “technostress,” time pressure, and workflow issues. Another from the New England Journal of Medicine cites the challenges of reimbursement in the fee-for-service environment, specifically, the “volume, value, and appropriate use of this care model.”

A comprehensive approach to virtual chronic care is needed. This includes a strong evidence base for remote monitoring. We need to answer the question, “what combination of devices and services are effective in improving care and reducing complications and disease progression?” For instance, remote monitoring devices can receive FDA approval for the accuracy of measurement, but how easy is the setup at home and how can the measures be best presented to the provider, enabling better outcomes and reducing burden?

Some health systems have successfully launched virtual hospitals or remote monitoring command centers staffed by nurses to monitor a large number of patients at scale. These centers remove the burden from the primary care provider and promote consistent virtual care. While there are some articles on best practices, few large-scale studies report outcomes, including reduced admissions and ER visits and improvement in key health measures. At the same time, we see virtual care programs, such as Digital Diabetes Prevention programs, which provide monitoring and also virtual coaching. Some of these have published large outcome studies, including equivalent outcomes and also superior results compared to routine outpatient care.

Fee-for-service was never a care model designed for chronic conditions

Payment for remote monitoring is now available for Medicare and Medicaid in the US but only on a fee-for-service basis. What is needed is more value-based care payment models to incentivize improving outcomes rather than episodic care. Fee-for-service was never a care model designed for chronic conditions. A value-based approach can help reduce physician burnout by encouraging the type of care physicians were trained to do – improving outcomes via evidence-based chronic care on a continuous basis.

In summary, what is needed to successfully utilize data from remote monitoring includes:

  • Meaningful display of the data to providers, whether that is a primary care physician or a remote monitoring command center nurse. Perhaps this would mean a trend graph within the results section on the EMR displaying how many times the person with diabetes was out of range during the past month or under medications, how many times a person with asthma used a rescue inhaler in a specific time period;
  • Appropriate payment models, preferably a value-based incentive with quality measures that demonstrate the stability in a panel of persons with chronic conditions. However, such quality measures should not be an additional burden to the provider but obtained from existing data;
  • Workflow considerations – new care models should integrate and simplify care, not make it more complex and burdensome. This is where many innovations break down;
  • Finally, involving patients and care partners in the implementation details. Will the remote monitoring be easy to set up? How will it include individuals’ differences, for example, whether someone’s lifestyle is more active or more sedentary? How is the support designed if something goes wrong?

All of this implies a comprehensive approach to remote monitoring as a new model of care with an evidence base that shows its effectiveness at scale.


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