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Leveraging AI Video Analytics for
Healthcare Security

Leveraging AI Video Analytics for Healthcare Security

A safe working environment is a major factor influencing the efficiency of employees and the quality of their work. When it comes to healthcare workers, its importance might be twofold, as patients’ safety and the quality of healthcare they receive is closely connected with the safety culture in healthcare delivery organizations. However, caregivers are far from being protected at work. They are subjected to violence on a regular basis. This includes physical attacks by patients, who may be delirious or under the influence of drugs, or threats from a distraught family member who can pass from verbal assaults to physical violence, and even become an active shooter.

Workplace violence comes at a high cost, as typically an employee subjected to violent acts requires compensation and medical treatment or misses work because of a workplace injury. Violence can also lead to other less obvious costs such as fatigue and stress which are tied to a higher risk of medication errors.

In an effort to build a positive safety culture, healthcare organizations apart from appointing manned security, create or enhance workplace violence prevention programs and deploy video analytics to make healthcare facilities security more proactive in their response to emerging threats. Let’s explore how AI next-gen physical security solutions help hospitals, clinics, nursing homes and other healthcare settings elevate their employee and patient safety.

Preventing violence against staff

Almost half of emergency physicians report being physically assaulted at work, while about 70 percent of emergency nurses report being hit and kicked while on the job. At the same time, many of the incidents at work remain unreported as healthcare workers consider injuries caused by patients unintentional, and therefore are likely to accept them as routine or unavoidable.

Though hospitals and other healthcare facilities are equipped with CCTV cameras, it’s almost beyond manned security capability to monitor all of them and detect each possible violent act. Thus, most violent incidents and high-impact events are discovered only after they occur.

With AI-powered next-gen solutions like Scylla Anomaly Detection and Behavior Recognition solution hospital security personnel will be able to handle multiple camera streams simultaneously, as the system detects fights with the impressive accuracy of 95%+ and sends alerts to all assigned endpoints once violent behavior is recognized. Such real-time surveillance will effectively increase situational awareness of security staff and help deescalate situations before they spill over into unacceptable or unlawful behavior.

Slip and fall detection

AI video analytics can also be effectively used for slip and fall detection. Emergencies can happen any time without warning. At healthcare facilities, the cases of patient falls are now all too common and remain a significant problem. Each year, roughly 700,000 to 1 million patient falls occur in U.S. hospitals resulting in around 250,000 injuries and up to 11,000 deaths. That is why fall detection technology is a much-needed feature in physical security systems. It will not help to prevent patients from falling but will ensure that security or medical personnel can respond to the situation as quickly as possible and provide help without delay.

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Weapon detection

Healthcare professionals are concerned about the growing number of victims affected by gun violence in hospitals every day. Incidents are caused by individuals, mainly former patients or their relatives, who feel wronged by the care that they or their loved ones received at the facility. Gun violence puts healthcare workers and everyone else who is seeking care at that hospital at tremendous risk. Therefore, it’s important for healthcare facilities to deploy tools that help detect threats proactively so they can instantly respond to potentially dangerous situations and minimize the amount of harm that can occur.

Scylla Object Detection solution is developed to automatically identify various kinds of weapons. It runs 24/7 analyzing video streams from security cameras in real-time. Once the threat is detected, the AI-powered system alerts the corresponding security unit to a potential threat.

What’s more, with the help of the Object Tracking solution the gunman will be traced across the connected cameras in real-time even when the weapon has been hidden.

Providing perimeter security

Another major vulnerability of hospital security is protecting its physical perimeter. Given the size and complexity of healthcare sites, it’s a tough task. Every hospital or clinic has sensitive assets such as confidential patients’ data, drug supplies and valuable medical equipment which present a target for thefts and vandalism. Therefore, round-the-clock perimeter monitoring and intrusion detection are critical. By deploying AI video analytics technologies healthcare facilities can monitor their premises in real time and report the intrusion in less than a second. Furthermore, it can be used in conjunction with access control systems to lock certain areas when a threat is detected.

Access control management

With regard to healthcare facilities, access control has its specific and requires a particular approach. Hospitals, clinics, nursing homes and other healthcare sites are expected to be welcoming for their patients, visitors and staff. On the other hand, they should provide proper access control management. This includes providing different access rights to employees, patients and visitors and managing access to different areas – from the reception area and visitor’s lobby, to high-security areas like pharmacies, psychiatric areas and emergency rooms. In addition, as healthcare professionals’ workflow pattern is quite changeable, the access control system has to be easily adaptable. Such challenges can be overcome by deploying an AI-powered Access Control solution which is tailored specifically to meet certain demands and seamlessly integrate different systems together for comprehensive workplace safety.

Parking area safety

Parking garages and surface lots are considered to be “high crime areas” in a hospital. They present the risk of thefts, car break-ins and attacks on health care workers. Slips and falls do happen at parking lots as well, especially during bad weather. By integrating AI technologies, security officers can detect threats, automate responses to reduce risks and expedite help where it’s needed.

COVID-19 protective measures

Coronavirus has created unprecedented challenges for healthcare. While healthcare professionals and the public are taking join efforts to fight the disease and prevent its spread, intelligent video analytics is critical to ensure compliance with the required protective regulations to maintain safety at public places and healthcare organizations in particular. By deploying AI-powered thermal screening hospital security managers can fast and non-invasively pinpoint individuals with elevated skin temperature, implement contact tracing or enforce safe social distancing between individuals. The module identifies non-compliance with social distancing mandates and sends an alert to the personnel to give an immediate response. Similarly, it can monitor wearing facemasks and other protective equipment in real time.

Final Takeaway

Hospital security professionals have to meet unique healthcare requirements like creating a non-violent working environment for health workers, ensuring patient and visitor safety, securing healthcare premises and keeping a check on valuable facility assets. In this regard, leveraging intelligent video analytics proves to be invaluable.

Cutting-edge physical security solutions help improve the quality and effectiveness of healthcare facilities providing round-the-clock monitoring, intelligent AI-based analytics and real-time incident notification. On top of that, enhanced video surveillance is instrumental to address such healthcare vulnerabilities as thefts, false lawsuits and vandalism.

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