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How is the government addressing the staff shortage?

Stéphanie van Rosmalen ·
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Governments are taking steps to address the healthcare staffing shortage through labor market policies, additional training places, higher salaries, and reducing administrative burdens. Yet these measures are still insufficient to keep pace with the growing demand for care. The shortage of healthcare staff is a structural problem that forces care organizations to seek their own solutions as well, including smart technology. In this article, we answer the most frequently asked questions about the healthcare staffing shortage and what can be done about it.

What measures is the government taking to address the healthcare staffing shortage?

The government is pursuing a combination of measures: more training places for healthcare professionals, higher salaries to make the profession more attractive, reducing administrative burdens, and encouraging career changers to enter the field. In addition, investments are being made in retaining existing staff through better working conditions and flexible hours.

Specifically, programs active in 2026 are focused on:

  • Increasing the inflow of new staff through targeted campaigns and subsidies for healthcare training programs
  • Reducing regulatory pressure so that healthcare workers can spend more time with clients
  • Encouraging part-time workers to increase their hours
  • Promoting collaboration between care organizations and educational institutions
  • Using technology as a supplement to human care

All of these measures target both the short and long term, but implementation is slow and results are still limited in practice.

Why is the government unable to solve the healthcare staffing shortage?

The healthcare staffing shortage is so persistent because demand for care is growing faster than the supply of healthcare workers. An aging population is causing demand for care to increase by approximately 6% each year, while the labor market simply cannot provide enough people to keep up.

Several structural factors are at play that complicate government policy:

  • An aging population: More elderly people means more people in need of care, while the working-age population is shrinking in relative terms
  • High workload and staff attrition: Many healthcare workers leave the profession prematurely due to stress, physical strain, and emotional pressure
  • Slow inflow: Healthcare training takes years, meaning the effect of additional training places will only become visible in the long term
  • Competition in the labor market: Other sectors offer more attractive employment conditions, making it harder to recruit new staff

Government policy can improve the conditions, but cannot resolve the fundamental labor market shortage quickly enough. Care organizations therefore cannot afford to wait solely for government intervention.

What can care organizations do themselves beyond government policy?

Care organizations can partially offset the staffing shortage by working smarter rather than harder. This means streamlining processes, redistributing tasks among staff, and deploying technology that takes over routine tasks — freeing healthcare professionals to focus on what truly requires human attention.

Practical steps care organizations can take on their own:

  • Task reallocation: let nurses do what they were trained for, and automate administration and monitoring
  • Invest in employee well-being to reduce turnover and retain existing staff
  • Collaborate with other organizations for flexible deployment of staff
  • Use data and technology to plan care more effectively and ease the burden of night shifts
  • Actively involve staff in finding solutions to build buy-in

The combination of a strong internal culture and smart technological support makes the difference for organizations that want to deliver responsible care with fewer staff.

How does AI technology help address staffing shortages in healthcare?

AI technology helps address the healthcare staffing shortage by taking over tasks that would otherwise require continuous human presence, such as monitoring clients and patients. This allows healthcare workers to use their time more purposefully and reduces the need to fill night shifts with supervisory tasks.

In practice, AI-based monitoring makes it possible to oversee larger groups of clients without requiring proportionally more staff. Systems that automatically detect when a client has fallen or is lying in an unsafe position send an immediate alert to the caregiver. This means valuable time is not spent on preventive check-rounds, but is instead deployed when action is actually needed.

This has a direct impact on workload: fewer unnecessary rounds, less stress from fear of missing something, and more peace of mind for both clients and staff. Technology acts here as a reliable extra set of eyes — not as a replacement for the caregiver.

What is the difference between traditional monitoring and AI-based monitoring in healthcare?

Traditional monitoring in healthcare is reactive: a staff member periodically checks whether everything is in order, or responds to an alarm button pressed by the client themselves. AI-based monitoring is proactive: the system independently recognizes situations such as a fall or a risky movement and alerts staff immediately — even when the client is unable to call for help themselves.

Traditional monitoring

With traditional methods, healthcare workers rely on fixed check-rounds or simple sensors such as bed mats and motion detectors. These systems generate many false alarms, leading to so-called alarm fatigue: staff respond more slowly because they have grown accustomed to unwarranted alerts. Furthermore, they provide no insight into exactly what is happening.

AI-based monitoring

AI systems continuously analyze image data and recognize patterns that indicate a fall, an unsafe lying position, or other risky behavior. Accuracy is considerably higher than with older technologies, dramatically reducing the number of false alarms. Healthcare workers are only alerted when action is genuinely required, which increases both efficiency and trust in the system.

When is AI-based monitoring the right choice for a care facility?

AI-based monitoring is the right choice for a care facility when the staffing shortage leads to insufficient supervision, when night shifts are difficult to fill, or when the number of fall incidents is high. It is also a logical step for organizations that take privacy seriously while also wanting to improve client safety.

Concrete signs that a facility is ready for AI-based monitoring:

  • Night shifts are consistently understaffed
  • Fall incidents result in injuries that could have been detected sooner
  • Staff experience high workloads due to supervisory tasks
  • Clients or family members express concerns about safety and privacy
  • The facility wants to scale up without hiring proportionally more staff

AI-based monitoring is not a replacement for healthcare staff, but a supplement that makes the available workforce more effective.

How Kepler Vision helps with the staffing shortage

At Kepler Vision Technologies, we have developed AI solutions that directly support care organizations in tackling the staffing shortage. Our software, Kepler Night Nurse, watches over clients around the clock and automatically detects unsafe situations such as fall incidents. Healthcare workers receive an alert within seconds, without anyone needing to be continuously present.

What our solution concretely offers:

  • Fall detection and fall prevention with unparalleled accuracy: just one false alarm every 92 days
  • Lying position recognition that flags risks at an early stage
  • Full privacy protection: footage is never viewed by humans, and caregivers only enter the room when the software requests it
  • Easy implementation through a plug-and-play concept, quick to schedule and configure
  • Compliance with ISO 27001 and NEN 7510 for secure handling of patient data

Want to know how we can help your care organization with smart AI-based monitoring? Get in touch with us at keplervision.eu and discover what Kepler Vision can do for your facility.

Frequently Asked Questions

How long does it take for AI-based monitoring to become operational in a care facility?

Thanks to the plug-and-play concept of systems like Kepler Night Nurse, implementation is typically completed within a few days. No major IT infrastructure is required: the software is configured on existing hardware and staff are guided through its use. Most facilities notice a tangible reduction in workload during night shifts within the first few weeks.

How do healthcare workers typically respond to the introduction of AI-based monitoring?

Resistance is understandable, but in practice staff tend to become positive quickly once they realize the technology supports them rather than replaces them. It is important to involve staff early in the selection and implementation process so they feel heard and learn to trust the system. Transparent communication about the goal — fewer unnecessary rounds, less stress — significantly increases buy-in.

Is AI-based monitoring also suitable for smaller care facilities with a limited budget?

Yes, AI-based monitoring is not exclusive to large organizations. Many providers work with scalable subscription models where you only pay for the number of rooms or clients being monitored. Moreover, the cost of the technology is often offset by savings on agency staff, the costs associated with fall incidents, and reduced staff turnover resulting from a lower workload.

How is client privacy protected with AI-based monitoring?

Modern AI monitoring systems are designed with privacy as a core principle: footage is processed locally and never viewed by humans. The software analyzes only movement patterns and body position, and only sends an alert when an unsafe situation is actually detected. Systems that comply with ISO 27001 and NEN 7510 also provide the assurance that patient data is handled securely and in accordance with applicable laws and regulations.

What are the most common mistakes care facilities make when addressing the staffing shortage?

A common mistake is focusing exclusively on recruitment while failing to address the outflow of existing staff. Attracting new employees makes little sense if the workload remains so high that experienced workers continue to leave. Another pitfall is adopting technology too late: facilities that wait until the situation becomes critical fall behind organizations that have already invested in scalable smart support solutions.

Can AI-based monitoring also help reduce fall incidents, not just detect them?

Yes, in addition to detecting fall incidents, advanced AI systems can also identify risky situations at an early stage — such as a client moving restlessly or assuming a dangerous lying position before a fall actually occurs. By alerting staff early, caregivers have the opportunity to intervene preventively. This shifts the focus from reacting to preventing, which benefits both client safety and the working experience of staff.

How do you measure the success of AI-based monitoring within a care organization?

Concrete metrics include: the number of fall incidents per month, response time to alerts, the number of false alarms, staff satisfaction, and absenteeism due to illness. By comparing these figures before and after implementation, you get a clear picture of the impact. Many facilities see demonstrable improvements across several of these indicators within three to six months.

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