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Case Study: physIQ & VHA Virtual Care Solution

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Originally published in Digital Medicine Society (DiMe)’s “Resources in Action” Case Study hub


physIQ activates the power of wearable biosensor data to generate personalized, clinically valid, actionable insights that help healthcare providers achieve better patient outcomes and enable safer, faster, more efficient clinical trials.

 

The Problem

≫ While we have been able to demonstrate the ability of the pinpointIQ™ solution to predict worsening health of Veterans with heart failure, we needed to demonstrate the value in an applied VHA program that could be adopted as a tool to drive early interventions by clinicians.

≫ By demonstrating the ability to attenuate hospital readmissions, improve communication with patients and give effective monitoring tools to providers, we can provide a holistic evaluation and that justifies support of this program over time and across the whole VA.

The Resources

≫ We used the VA-DiMe value-driven framework to guide us in designing and evaluating the Continuous Remote Patient Monitoring (cRPM) LINK-HF Program.

≫ We chose it because by demonstrating the ability to attenuate hospital readmissions, improve communication with patients and give effective monitoring tools to providers, we can provide a holistic evaluation and that justifies support of this program over time and across the whole VA.

≫ This framework helps identify metrics and measures that address the measures of access, effectiveness, efficiency, and equity.

The Impact

✓ cRPM helps patients with heart failure preserve functionality, conduct daily activities more freely, and pursue a more active lifestyle.

✓ Reduces the negative impacts on caregivers and improves care for Veterans living in a rural location.

✓ Allows clinicians to manage patients more effectively by proactively aiming their attention to the right patient at the right time.

✓ Better patient and clinician satisfaction; many felt the process minimized trips to the clinic/hospital and they still felt well supported.