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5 elements of 'smart' hospital rooms
'Smart' hospital rooms combine virtual, remote patient monitoring and AI tools to enhance clinician workflow, care outcomes and patient experience.
Amid the proliferation of digital health technology, health systems are exploring how these technologies can be integrated to enhance patient care. One approach becoming increasingly popular is creating 'smart' hospital rooms in healthcare facilities to boost patient experience and clinical outcomes.
While there is no one definition of a 'smart' hospital room, it generally includes technologies, like virtual and AI-driven tools, that allow clinicians to monitor, interact with and guide treatment remotely for patients during their hospitalization. However, the technologies and elements included in smart hospital rooms can vary from facility to facility.
For example, the University of Utah has built smart rooms in its rehabilitation hospital that include lights, blinds, thermostats, doors and TVs controlled through an iPad app, Meanwhile,Houston Methodist Center for Innovation is working on smart hospital room designs that include voice-controlled room controls and ambient intelligence-powered tools.
In this article, Virtual Healthcare will examine the elements most commonly found in 'smart' hospital rooms.
BEDSIDE TABLETS AND TVS
While most patient rooms are equipped with a TV, smart rooms include 'smart' TVs that act as conduits for virtual care. Clinicians can use 'smart' TVs to connect and interact with patients without physically entering the room, affording patients and clinicians convenience without sacrificing needed clinical oversight.
Many of these TVs, like the one installed by New Jersey-based Virtua Health, include a feature that enables clinicians to virtually 'knock' and ask to enter the room. The clinician can only initiate the audio-video feed to see and speak with the patient if the patient agrees.
Similarly, hospital-provided bedside tablets allow clinicians and patients to communicate virtually. Tablets make it easier for patients to engage with educational materials, better understand treatment plans, access information about their hospital stay and, in some cases, connect with their loved ones outside the hospital.
TVs and tablets in hospital rooms also provide entertainment resources to patients. Some devices allow patients to connect or cast their own streaming services to their screen, allowing them to watch their favorite shows or movies.
VOICE ASSISTANT DEVICES
In recent years, voice-activated assistants, like Amazon's Alexa or Apple's Siri, have grown popular for healthcare use cases. While these solutions in the home do not always provide reliable medical information, in the hospital, they can offer convenient communication pathways between patients and their care teams.
The hands-free nature of voice assistants is especially beneficial for bedridden patients in the hospital who cannot move freely. The devices allow themto connect with staff when they need help.
Technology companies have answered the call for wider availability of these devices in the hospital setting. In 2023, Amazon announced a new suite of healthcare capabilities for its Alexa device. Alexa Smart Properties for Healthcare, the Amazon arm that helps health systems deploy and manage Alexa-enabled devices at scale, added WebRTC support. Thisenables audio and video calls between Alexa Echo and non-Echo devices.
It also incorporated Private Branch Exchange (PBX) support, which allows providers to link Alexa Smart Properties-supported devices with the healthcare facilities' phone systems to route Alexa calls and support caller ID when patients and medical staff conduct incoming and outgoing calls.
REMOTE PATIENT MONITORING TOOLS
Though remote patient monitoring (RPM) tools are generally used to extend care outside the hospital, these technologies are also helpful within hospital units. Common RPM devices, like healthcare wearables and blood pressure monitors, can allow in-hospital care teams to continuously monitor patient vital signs.
For instance, Houston Methodist scaled an inpatient RPM solution across its eight hospitals last year that captures multiple vital signs, including heart rate at rest, respiratory rate at rest and skin temperature. This data allows clinicians to intervene quickly when a patient deteriorates and identify stable patients who could be discharged.
Additionally, a pilot study conducted by the Cleveland Clinic and GE HealthCare showed that RPM tools could provide critical information to clinicians without prompting alarm fatigue. The study identified suitable alert thresholds for continuous heart rate, saturation and ventilation monitoring, and then compared blinded and unblinded continuous ward monitoring.
Researchers found that unblinded continuous monitoring, where clinicians had access to monitoring results, decreased the number of times vital signs exceeded the normal thresholds by 25%, mitigating patient deterioration.
AI-ENABLED FALL DETECTION
Falls are a common and dangerous byproduct of hospitalization. According to the Agency for Healthcare Research and Quality's Patient Safety Network, falls occur at a rate of 3 to 5 per 1,000 bed-days, resulting in an estimated 700,000 to 1 million hospitalized patients falling each year. Many of these falls result in injuries, including fractures and head trauma, or even death.
Increasingly, health systems are implementing AI-enabled fall detection solutions that use video and sensor data to predict patient falls, enabling care teams to intervene early and prevent them.
For example, Virtua Health's 'smart' rooms will feature ambient sensors that will map the room with Light Detection and Ranging (LiDAR) and thermal imaging, allowing hospital staff to monitor the movements in the room. The sensors create a safe zone, and based on the patient's movement, they can predict whether they will exit that safe zone and have a potential fall. The system then alerts the care team.
Researchers have also been working to enhance these solutions. For instance, a study published in September 2024 described how researchers used transfer learning to overcome data limitations and computational efficiency concerns associated with using a fall detection tool built on deep neural networks. Additionally, the researchers incorporated Explainable AI (XAI) techniques to ensure transparent and trustworthy decision-making in the tool, which is essential to overcome black box AI challenges in healthcare.
REAL-TIME LOCATION SYSTEMS
Real-time location systems enable hospitals to track patients and staff across hospital and health system buildings. Devices like tags, sensors, and display screens enable real-time tracking. The tags are attached to people and generally emit signals, such as radio frequency identification (RFID) or ultrasound. A network of sensors picks up these signals. The sensors transmit the data to the screens, which display the movements of the person with the tag.
'Smart' hospital rooms are often outfitted with these devices to improve patient throughput, clinical workflows and resource management.
Research shows that these systems are effective in approximating patient wait times and patient-provider interactions and tracking workflow deficiencies and areas for better time management. They also improve healthcare providers' well-being and productivity and shorten patient wait times.
Anuja Vaidya has covered the healthcare industry since 2012. She currently covers the virtual healthcare landscape, including telehealth, remote patient monitoring and digital therapeutics.
