Chris Lennon, Healthcare Business Development, Healthcare at Hanwha Vision America explains how intelligent video surveillance in healthcare helps to enhance security, increase efficiencies and provide patients with the care they need.
Healthcare facilities of all sizes are increasingly using a mix of AI, cloud computing and real-time analytics technologies to boost the capabilities of their intelligent video surveillance systems.
Cameras with AI capabilities and built-in edge intelligent audio and video analytics are now commonly installed throughout a healthcare facility to meet a varied set of security and surveillance needs.
Organizations are deploying more surveillance in healthcare with diverse features and capabilities, but also, how a facility deploys and monitors those cameras is critical.
AI is playing a larger role in real-time disease detection, tracking potential outbreaks and predicting health risks before they escalate.
Machine learning algorithms analyze electronic health records (EHRs), wearable data and social determinants of health to improve surveillance accuracy.
AI-Powered Natural Language Processing (NLP) is extracting valuable insights from unstructured clinical notes, social media posts and news reports to detect potential public health threats.
AI also opens the door to generating predictive analytics to help healthcare facilities shift to a more proactive posture and plan their operations further in advance.
AI and predictive analytics can detect potential health risks based on vital signs and other data, enabling timely interventions and preventing complications.
On an operational level, predictive analytics can help with resource and staff allocation.
AI can also play a role in creating personalized treatment plans and improving patient outcomes, ultimately helping to streamline healthcare operations, from administrative tasks to medication management.
From a security and surveillance perspective, hospitals are complementing their cameras’ security monitoring performance with enhanced data-gathering capabilities combining intelligent audio/video analytics and AI.
The result of this surveillance in healthcare is targeted object detection, characteristics extraction and object classification, which can save time for hospital security teams by accelerating forensic searches.
When an incident occurs, locating a person of interest can take a matter of minutes instead of having to sift through hundreds of camera streams for hours.
This combination of IP cameras and analytics in surveillance in healthcare helps security professionals get a better handle on access control and monitoring of hallways, entrances and exits, and exterior parking lots.
Knowing which doors visitors can use to access and exit a building is important when placing cameras.
Surveillance in healthcare’s built-in edge analytics can be used for people-counting to accurately track the volume of people entering or exiting a building, which helps administrators and hospital security teams monitor their population on any given day.
Across the industry, facilities are increasing their use of specialized analytics in surveillance in healthcare as organizations look for new insights into every aspect of their daily operations, and to protect their staff, patients and visitors.
Cameras with AI can analyze patients in behavioral health units and in-patient rooms to detect self-harm risks or aggression, identifying aggressive body language, escalating voices or erratic movements, and then sending alerts to security teams.
Another example of new analytics available for surveillance in healthcare is a collaboration between Hanwha Vision and Triton, where Hanwha has integrated a Triton sensor into a POE+ powered device that can detect vaping activities in unauthorized areas, as well as enhance air quality monitoring.
The sensor can also identify THC and environmental anomalies like screams and glass breaks.
Cloud integration, real-time alerts and people counting and loitering detection are also available.
Other examples include AI-based blocked exit detection AI that will help with Joint Commission audits, conducted regularly to assess a facility’s compliance with standards and focused on patient safety and quality of care.
Also, new slip-and-fall analytics in surveillance in healthcare can monitor, detect and document when someone slips at the hospital.
Organizations are increasing their use of cloud-based platforms in surveillance in healthcare for real-time public health reporting.
Interactive dashboards provide instant updates on disease spread, vaccination rates and healthcare resource availability.
Cloud-based video storage allows remote access to security footage, reducing on-premise storage costs and enabling collaboration across hospital networks.
Advancements in data interoperability also allow for seamless sharing of patient information between different healthcare providers and systems.
As more connected devices are used for a growing number of patient care applications, especially remote monitoring, securing networked devices can be integral for preventing unauthorized access and data breaches.
The increasing use of AI and deep machine learning algorithms is helping to detect and classify distinct objects (people, vehicles, faces and license plates) while clearly distinguishing them from their environmental surroundings.
These “smart” technologies filter out irrelevant motion triggers to focus only on people, objects and vehicles, and generate only the events users need to see for effective forensic searches and enhanced operational efficiency.
They also minimize storage and bandwidth by not tracking and recording every type of object in motion.
Multi-directional and pan-tilt-rotate-zoom (PTRZ) technology is beneficial to hospitals looking to get the most out of their security spending.
With one device through one data connection, a facility can record several key areas like pharmacies, hallways or lobbies with unique fields of view.
Hospitals are also deploying both on-premise and cloud-based solutions, depending on their size, budget and coverage needs.
Beyond the monitoring and protection of a facility, new technologies are increasingly being combined to create new surveillance in healthcare solutions to enhance patient care.
With the integration of IP PTZ cameras and Virtual Care platforms, hospitals can perform 24/7 centralized patient monitoring and conduct remote monitoring and observation of various units for applications including telesitting, virtual nursing, medication verification and virtual admission, discharge and transfer (ADT).
Hospital staff can remotely check on patients from a central command center at the nurses’ station, keep an eye on various in-room equipment using motorized camera lenses or view which way a patient’s body is turned.
This level of remote patient monitoring using AI-powered video analytics helps to track patient movements and detect signs of distress, such as falls or abnormal behavior, enabling faster intervention.
Staff can detect unusual movements that indicate a patient may be about to fall, alerting nurses before incidents occur.
Some advanced systems even integrate third party plug-ins to monitor heart rate, respiration and temperature without physical contact.
It’s one more example of moving the patient care process from reactive to proactive, and key staff can use their time for other activities without getting bogged down by time-intensive, tedious logistics.
There is also an increased use in Remote Patient Monitoring (RPM), including wearables and connected devices, which will play a greater role in patient care and allow for more proactive monitoring and intervention.
The healthcare sector is a prime target for cyber-attacks, so cybersecurity will continue to be a major focus.
Healthcare organizations must implement robust security measures to protect sensitive patient data from breaches, while at the same time maintaining compliance with constantly changing data privacy regulations.
Video analytics can monitor patient flow and wait times at registration or in the ER, dynamically adjusting staffing levels to reduce bottlenecks.
In terms of automated workflow optimization, AI is being used to analyze patient wait times, staff efficiency and facility occupancy to optimize resource allocation.
For asset tracking and theft prevention, healthcare facilities use cameras to track the location of medical equipment to prevent loss and improve use.
Beyond safety, care and efficiency, installing the right surveillance in healthcare infrastructure can be the right diagnosis to improve patient care, remotely monitor sensitive areas and maintain a safe and welcoming public environment for staff, patients and visitors.
This article was originally published in the May edition of Security Journal Americas. To read your FREE digital edition, click here.
