Some years ago, while in a discussion about technology innovation, the CIO of a world-famous healthcare institution spoke about his focus on compassionate care. That conversation struck a chord with me. At its very core, healthcare delivery is a human undertaking that is skillfully tailored to meet the needs of the individual patient. We should never lose sight of that fact. Digital health solutions must be a means to that end: delivering high-quality, compassionate, efficient, and safe patient care across the continuum of prevention, diagnosis, treatment, recovery, and follow-up. Technology must blend into the background and silently help human caregivers do their best work.
With this mission in mind, our team at Caregility is now embedding AI technologies into our proven virtual care platform to bring individualized patient care to a new level. The compassionate care belief system is a driving force as we set about that work.
We recognize the immense potential for AI in healthcare, but the consequences of getting it wrong, even in a tightly defined domain such as virtual care, could be harmful to care teams and patients. We’ve seen AI applied in broad strokes – delivering a standard set of capabilities to every patient without consideration of their individual needs. We believe that approach is a mistake, and we are committed to applying AI in a responsible way that respects the needs of individual patients and adapts accordingly.
Steering Principles for AI in Telehealth
To ensure our introduction of AI creates value for care teams and contributes to individualized patient care, we’ve embraced a few key steering principles. We believe these principles will help us stay true to our compassionate care beliefs, focus our development work, and allow us to adapt quickly as the underlying technology matures and we receive real-world feedback from our customers. Those steering principles include:
- Partnering our clinical and development teams closely on product direction. Our clinical solutions team, comprised of licensed healthcare practitioners with decades of experience in bedside nursing and virtual care program rollouts across leading healthcare institutions, plays a significant role in ensuring that the new AI enhancements we bring to market will positively impact the day-to-day experience of bedside clinicians and their patients.
- Responding to every patient as an individual. The more an AI-driven service is customized to the individual patient, the more meaningful the clinical insights that AI helps reveal are. Striving to achieve this level of personalized care delivery helps ensure actionability without introducing nuisance alarms.
- A focus on Return-on-Investment. We are committed to being clear-eyed about the financial and clinical outcomes new AI enhancements must deliver to justify the resource investment in time, money, and opportunity.
Caregility’s AI Roadmap
At Caregility, we are providing an optional set of AI-driven services that enhance specific virtual clinical programs, such as Virtual Nursing and Continuous Observation. As we build out these and other AI solutions, in order to adhere to our guiding principles, Caregility is employing an agile software development approach to release AI enhancements for virtual care in phases.
The initial phase is a minimum viable product (MVP) that embeds selected AI capability into our platform, delivering a targeted subset of our overall AI vision to Caregility customers and their patients. We will deploy the MVP to early field trial customers willing and able to partner closely with our clinical solutions team. Together they will provide our development team with a feedback loop that answers essential questions: Are we heading in the right direction? Is our vision for AI enhancement something that solves problems that exist in this institution, or should we adjust? Do our customers trust that this technology shows promise?
We’ll then make modifications and improvements to deliver subsequent phases, using customer feedback to drive value at every stage: Does it increase efficiency? Does it improve care quality? Does it positively impact patient and staff safety?
Our goal is to create additional value for our customers through the Caregility point-of-care telehealth systems that they have already deployed and are planning to deploy. With powerful edge computing and high-resolution cameras and microphone arrays that simultaneously support live two-way audio/video sessions and multimedia streaming, the Caregility Cloud™ platform was built with medical-grade AI integration in mind.
Intelligent Telehealth Endpoints
Each Caregility point-of-care system we deploy today is equipped with sophisticated, purpose-built microphone arrays and HD cameras that can introduce both remote clinician support and AI-enhanced monitoring to care teams. Here are a few examples that illustrate what purpose-built means:
- Patient rooms are often noisy environments. Caregility audio processing is purpose-built to perform well in this environment so that remote clinicians can pick up on alarms and hear patients and bedside teams clearly. That same capability can be dual-purposed to feed AI language processing components that enable ambient listening and documentation.
- To support patient observation at night, Caregility cameras are purpose-built with infrared night vision. That capability also ensures that computer vision-based AI performs well under low-light patient room conditions.
- Our point-of-care devices can send audio and video streams to multiple locations simultaneously to support simultaneous workflows. That means a remote doctor can consult with a patient at the same time the video stream is feeding our AI engine to monitor for patient safety issues such as the bed rail positioning.
The question we seek to answer through AI enhancement is: What tasks can AI help us automate to augment the work of care teams?
AI-Enhanced Audio, Video, and Radar for Virtual Care
As we set out to introduce clinical AI to our virtual care platform, we’re focused on three key areas.
Computer vision enhancements will analyze patient room video streams to look for safety risks, best practice adherence, and workflow optimization opportunities. If the engine detects something that requires human intervention, our intent is to flag it for the right member of the care team. We will leverage our existing iConsult and iObserver applications as the main way to surface useful AI-driven insights to care team members, with incremental updates expected. We want insights to be actionable, not disruptive. Customer feedback from early field trials will inform our roadmap.
In the outpatient context of telehealth, we plan to extend video stream processing to virtual visits to gather patient vital signs (i.e., respiratory rate, heart rate, blood pressure, and body temperature) from facial video analysis. We’ll present this live data to the remote clinician so they can see it as part of their remote consultation.
Acoustic-based AI will listen to audio streams for patterns that can alert staff to patient stress or behavioral issues. In the inpatient context, we are researching embedded AI to identify medically relevant parts of conversations between clinical staff and patients to relieve some of the clinical note-taking burden for care teams. Ambient listening will inform structured clinical data capture for nurses to review before being documented in the EHR.
We are also working to integrate an optional radar sensor with our point-of-care devices to support contactless vitals streaming in inpatient care. Trending heart and respiratory rates over time could signal deterioration or changes in the patient’s condition. Our goal is to support personalized compassionate care and alert the appropriate clinician if vital signs diverge away from that patient’s baseline. Sepsis is a major patient safety factor in our hospitals, and we believe widespread adoption of this type of technology will help attack that problem and others.
The AI journey ramps up for Caregility in 2024, when we release our first commercial offerings addressing two of our key focus areas: Augmented Observation and Vitals Trending. We will partner closely with our early field test customers to measure the impact those solutions have on key performance indicators. Customer feedback will fuel our next wave of intelligent telehealth enhancements aimed at advancing compassionate, personalized care.