Artificial intelligence (AI) is poised to revolutionize patient care within hospital settings.
Artificial intelligence (AI) is poised to revolutionize patient care within hospital settings. For security integrators, this shift presents significant opportunities – but also necessitates a nuanced understanding of the technology's potential along with its ethical and logistical implications.
“AI-powered video analytics have already reached the point where we are seeing them play a meaningful role in improving patient care in clinical settings,” said Jamie Barnfield, Senior Sales Director at IDIS Europe. “As AI video capabilities improve further, we expect to see a quiet revolution in the way healthcare providers deploy them.”
Proactive safety: a new frontier
AI-powered video analytics offer a leap forward in patient safety. Features such as loitering detection and line-crossing alerts, typically associated with security applications, hold immense promise for proactive intervention in healthcare settings. Now, hospitals can monitor sensitive areas and receive immediate notifications of potential patient risks or escalating situations.
“Using well-proven AI video tools such as line-cross and loitering detection, healthcare providers already have the option to proactively monitor locations for potentially harmful activity, identifying patterns, and predicting potential issues before they escalate,” said Barnfield. “This can not only help to improve patient safety, it can enhance operational efficiency, and optimize resource allocation.”
Courtney Whaylen, Account Executive, Enterprise, Genetec pointed out that Dealing with staff shortages is difficult enough for hospitals and healthcare facilities. Finding more efficient ways to monitor patients and handle tasks helps hospital staff work smarter.
“They can set up perimeter protection analytics and create defined zones for each patient’s room or area,” Whaylen said. “If the patient leaves their room or the designated area, or falls out of their bed, the system will trigger an alarm, notify nurses and provide a live video so they can quickly see what’s happening. Video analytics can also help staff quickly detect instances of theft, violence, or intrusion, while people-counting analytics can monitor foot traffic and patient flow, and alert staff to overcrowding in emergency areas. All of these examples help facilities improve patient care and overall operations.”
Privacy & ethics is the central challenge
Patient privacy and data security are paramount concerns. Integrators must ensure a deep familiarity with regulations like HIPAA (US), GDPR (EU), and applicable regional privacy laws. Handling sensitive areas like mental healthcare becomes especially complex, highlighting the need for transparent system design and strict patient consent protocols – even when involving authorized family members or caregivers.
“Collecting and analyzing information about patients and visitors can raise concerns about privacy and data security,” Whaylen said. “There are also ethical concerns about the potential misuse of data and violation of patient autonomy. This is why keeping patient identities and data safe is critical for healthcare providers.”
Deploying video analytics built with privacy by design can help reduce these concerns. This involves implementing video analytics with full transparency, along with having well-defined objectives and policies around how data is collected, stored, and used.
“It’s important, of course, to be aware of requirements and concerns around patient privacy and data security,” Barnfield said. “Many systems integrators will already be familiar with requirements and constraints that quite rightly come with conducting video surveillance. In the US, for example, integrators need to follow regulations like HIPAA, while in the EU there’s GDPR to consider, as well individual country privacy laws.”
Proportionality is a key consideration. For example, in mental healthcare settings the need for enhanced patient protection, staff and visitor safety, and general security, can override privacy norms and system configuration practices that apply to general settings.
“For instance, patients experiencing acute mental health crises are often better monitored by discreet and low-profile cameras,” Barnfield added. “This allows clinical staff to make regular observations – of as a minimum of 15- or 30-minute intervals - more easily than the old method of peering through small windows or door shutters into isolation rooms.”
A single fisheye camera not only eliminates the blind spots that patients might use to avoid observation, but they have also been proven across a number of facilities to reduce patient stress and minimize the risk to staff of verbal or physical aggression.
“The ability to remotely monitor patients via VMS, rather than sitting outside isolation rooms, or missing an observation, reduces the stressed and workloads on often already overworked clinical teams, and provides evidence for the audit trails needed to comply with acute mental healthcare standards,” Barnfield added.
Beyond security to falls, flow, and optimization
AI's applications go far beyond individual patient safety. Fall detection is a prime example, especially for elderly patients. By instantly alerting staff to slips, trips, and falls, AI can significantly improve emergency response times and reduce the risk of serious injuries.
“One of the most useful capabilities of AI in healthcare and assisted living settings is fall detection,” said Barnfield. “Falls are often a cause of fatalities or serious injuries, especially among older patients, and particularly if they are left lying on the ground for any significant period of time. An AI-alert to a slip, trip, or fall can allow a faster response by healthcare professionals. Our future vision is to integrate video into push-to-talk (PTT) radio solutions so that security teams and first responders quickly and better coordinate responses to falls and other safety and integrators incidents especially across large and often complex hospitals.”
Additionally, AI-based video analytics can streamline operations by monitoring foot traffic patterns and flagging overcrowding in emergency departments. Such insights allow hospitals to optimize resource allocation and enhance the overall patient experience.
Navigating adoption in a challenging landscape
Security integrators should be mindful that AI adoption in healthcare extends beyond traditional sales cycles. These projects often require buy-in from multiple departments, demanding a persuasive business case that demonstrates value for security, operations, and clinical stakeholders.
“Integrators also need to be aware that many of today’s AI functions are not seen as a security sell and will likely require multi-departmental buy-in in what are often complex organizations,” Barnfield pointed out. “This complexity will increase sales cycles and often means building business cases with several stakeholders.”
And today, it’s also worth bearing in mind that many healthcare providers globally are still recovering from the impact of the Covid pandemic, with backlogs of elective surgeries, and patients that have presented late with conditions that have become more serious as a result.
“This means that budgets are tight. It could therefore be some time before healthcare organizations fully adopt AI video for patient care or have the time to consider how it could revolutionise some departments,” Barnfield said. “So many hospitals are currently short-staffed and focusing on attracting more nurses, doctors, and care staff, just to get back on track.”
Privacy by design
To allay privacy concerns, security integrators must spotlight AI solutions with built-in safeguards. Privacy-by-design tools like pixelation protect patient identities while ensuring authorized personnel can access unobscured footage in emergencies.
Strict data management policies and transparent communication about the technology's implementation are crucial.
The future: AI as a tool for integration
The potential of AI in healthcare extends far beyond the applications discussed. On the horizon is further integration with medical devices and personalized care protocols.
Security integrators who master both AI's technical possibilities and the nuanced requirements of healthcare will be best positioned to spearhead this transformation in patient care and safety.