Advanced monitoring camera.
The potential number of use-cases for AI in healthcare settings seems to be increasing at an exponential pace. Moving beyond uses for research and development, customer service needs, reducing administrative documentation burdens or easing regulatory processes, the latest trend by hospitals is to leverage the technology to help monitor patients.
In the most traditional sense, remote patient monitoring (RPM) refers to using digital technology to help monitor patients outside of traditional healthcare or clinical settings. For example, if a patient has a chronic condition, a wearable device or tracker can help monitor the patient and collect data over long periods of time and collate that data to provide the physician with more insights during the next appointment. The value is self-evident: “it provides visibility into patients’ lives outside of their scheduled appointments, which has historically been a barrier to timely and effective diagnosis and management. With data collected over time, care team members can manage and treat chronic conditions in a way that is timely, meaningful, and realistic to the patient’s lifestyle.”
However, over the years, innovators have started expanding the definition of RPM; healthcare experts are increasingly recognizing that patient monitoring is not only vital outside of healthcare settings, but just as imperative for patients within traditional care settings, especially with regard to long term care facilities, for high risk patients that require constant monitoring and even as a means to address growing workforce shortages.
With regard to hospitals, the American healthcare system is facing a rapidly growing healthcare worker shortage amidst a swiftly aging population. The American Association of Medical Colleges indicates that by 2036, there will be a shortage of almost 86,000 physicians. Moreover, according to key studies, authorities are projecting a shortage of nearly 63,000+ nurses by 2030. Indeed, without these two pillars, the healthcare system will come to a grinding halt.
This is why technology companies are trying to leverage AI as a means to potentially augment the healthcare workforce. Last week, famed telehealth company Teladoc Health announced that it would be launching AI capabilities to provide a “virtual sitter” solution. Normally, in many inpatient hospital settings, staff are used to “sit” and watch over patients that require extra monitoring and attention. However, this is one of the heaviest labor investments— constant monitoring by staff often takes away time from other tasks, meaning that healthcare facilities have to hire individuals solely for the task of being a sitter.
Teladoc’s virtual sitter solution hopes to address this very conundrum with AI: “Using advanced, pre-trained algorithms, motion detection and pose estimation, the expanded solution can visually detect patient movement that could lead to falls, enabling faster intervention by bedside staff.” A key use-case for this may be to monitor a patient that has an increased risk of falling; the AI tool may be able to monitor and alert staff if it detects that the patient has left their bed.
In a similar fashion, healthcare facilities are also increasingly leveraging “smart room” technology. Care.ai has pioneered numerous solutions in this space, leveraging AI and ambient sensors to make patient rooms “smart”: “NLP (natural language processing) can interpret and transcribe clinician and patient speech, turning it into structured data, which helps in automating documentation and reduces manual input. Machine learning sensors monitor patient activity and vital clinical and operations processes, learning from these data patterns to predict patient needs or detect anomalies, ensuring that the data driving decisions is both timely and accurate.” Per the company, the technology can be used for a variety of use-cases, ranging from fall prevention and preventing pressure injuries to enabling virtual rounding and ensuring that staff follow outlined protocols. In fact, the potential for this technology is so valuable that in August of this year, medical device and technology giant Stryker announced that it will be acquiring care.ai to add to its repertoire of enterprise solutions.
These are just a few examples of how healthcare and technology organizations are increasingly investing in AI tools to observe patients and help workflow needs. Indeed, while the majority of discussion around AI in healthcare tends to focus on physician use-cases and easing administrative burdens, there is significant scope for this technology to transform the patient monitoring space.
