Although patient safety is paramount in healthcare settings, about 1 in 10 patients is harmed in healthcare, and more than 3 million deaths occur due to unsafe care, says the World Health Organization (WHO). The reality is hospitals and healthcare facilities face numerous challenges in managing safety in addition to the risks of healthcare associated infections (HAIs), equipment failure, and operational downtime.

Without safety management and quality control, patient care and the overall functioning of facilities is compromised. Predictive cleaning and smart maintenance, two emerging technologies, have the power to transform safety in healthcare environments. They optimize cleaning and maintenance schedules as well as reduce risks, prevent accidents, and ensure long-term viability of healthcare services.

Predictive cleaning using real-time data and advanced algorithms

Cleaning plays a vital role in customer satisfaction and business profits. Regular cleaning offers many benefits, such as disease prevention, allergy reductions, and fall prevention, to name some.

Commercial cleaning represents the first line of defense against contamination. For example, commercial floor spaces can become the dirtiest parts of a building. Therefore, cleaning and sanitizing commercial flooring is vital to a healthy work environment. It also contributes to a positive business brand image.

In healthcare settings, predictive maintenance cleaning deploys smart sensors in high-touch areas such as patient rooms, operating theaters, and restrooms. These sensitive sensors monitor foot traffic, air quality, and surface contamination levels. Data gathered by the sensors are transmitted for analysis using machine learning algorithms that predict when and where cleaning is needed. Say an area with high patient traffic, like the emergency ward, might need more frequent cleaning, while a surgery room requires thorough disinfection to prevent contamination. There are also predictive cleaning systems that make use of robots to automate the cleaning process.

To illustrate, robotic vacuum cleaners and ultraviolet (UV) sterilization robots automatically clean and sterilize areas based on predictive data received. Robot deployment offers several advantages, such as reducing human error, thorough cleaning, and disruption reduction because they can operate during low-traffic hours. Moreover, robots instead of human staff can enter areas at high risk for contamination, thereby reducing possible exposure to harmful pathogens and chemicals.

Another bonus is that predictive cleaning generates real-time data and automated alerts, ensuring that cleaning tasks are completed, and increasing adherence and compliance to hygiene standards and safety regulations.

Smart maintenance is a proactive approach to equipment safety

The safety of equipment in hospitals and healthcare facilities affects patient outcomes, staff safety, and financial stability. Medical device failures can result in misdiagnoses, delayed or incorrect treatments, direct harm, and even fatalities. It’s no surprise that the U.S. Food and Drug Administration (FDA) receives more than 2 million medical device accident reports each year. These reports may pertain to deaths linked to medical devices, serious injuries, and malfunctioning equipment.

When machines malfunction or fail, downtime is high, which disrupts patient care and increases wait times. Furthermore, staff devotes a considerable amount of time to troubleshoot, find alternative equipment, or reschedule appointments, diverting valuable resources. It’s inevitable that the cost of care will jump because of extended stays, additional diagnostic tests, and further treatments. We’re not even talking about legal liabilities and malpractice claims that can become very costly, in addition to repair and replacement costs.

It’s crucial for workers to maintain all equipment and devices regularly. Specifically, smart maintenance that uses the internet of things (IoT), artificial intelligence (AI), and predictive analytics to monitor the condition of critical medical infrastructure and equipment can predict failures and problems before they happen.

To illustrate, sensors on medical devices such as ventilators, magnetic resonance imaging (MRI) machines, and infusion pumps keep track of performance metrics like temperature, vibration, and use. AI algorithms analyze the data to predict potential malfunctions so maintenance can be scheduled before a problem occurs.

A sudden equipment breakdown during a procedure can have severe consequences for patient safety. Smart maintenance significantly reduces that risk by ensuring that equipment is always in optimal working condition. Additionally, proactive maintenance prevents minor issues from turning into major costly breakdowns, improving the longevity and reliability of expensive medical equipment. Smart sensors can also monitor heating, ventilation, and air conditioning (HVAC) systems, predicting issues that could compromise air quality, temperature regulation, or even fire safety.

Another area where smart maintenance is a plus is the continuous monitoring of electrical systems and plumbing to determine potential hazards like wiring issues, leaks, or fires.

 In summary, predictive cleaning and smart maintenance are not only about efficiency. They are fundamental components of a robust safety-management quality control system in healthcare environments.