By turning equipment data into actionable insights, HTM teams are reshaping how hospitals manage technology, budgets, and patient safety.
By Christopher Becks, president, clinical asset management at TRIMEDX
Clinical engineering has evolved from a reactive, repair-based service to a strategic, data-informed function within healthcare systems. By leveraging real-time analytics and equipment performance data, healthcare technology management (HTM) teams can predict failures, fine-tune maintenance schedules, and make smarter decisions about when to repair, replace, or transfer assets.
These insights not only improve equipment uptime and patient safety, but they also help optimize the supply chain by forecasting parts demand, reducing emergency orders, and informing procurement strategies. Data also plays a growing role in strengthening medical device cybersecurity, enabling teams to identify vulnerabilities, track software updates, and mitigate risks proactively.
As hospitals face financial and operational pressures, data-driven HTM is essential to building a more resilient, efficient, and secure healthcare infrastructure.
The Power of Predictive Analytics
Predictive analytics is at the heart of this transformation. By collecting data on parts usage, repair trends, failure trends, clinical engineering teams can forecast potential issues and decrease equipment downtime. Predictive work systems (PWS) can utilize real-time and historical data to spot warning signs of device problems and notify technicians before the device reaches a point of failure. This allows clinical engineering teams to schedule maintenance or repairs at convenient times without disrupting patient care.Â
TRIMEDX data shows 1,000 downtime events are diverted or avoided annually due to its PWS—allowing health systems to avoid more than 31,000 hours of unplanned downtime. Proactively addressing issues before a device fails reduces costly unplanned equipment outages, improves patient experience, and helps health systems avoid lost revenue.
In addition, predictive technologies allow health systems to prepare for their maintenance or replacement needs in advance, ensuring supplies and parts are ordered in time to avoid shortages or delays that could interrupt patient care.  Â
Smarter Capital Planning
Insights into a device’s age, repair history, condition, and utilization can also empower health systems to make smarter capital-planning decisions. Without this type of data, health systems can become reactive, often relying on subjective arguments for capital allocation. Health systems should work to establish a coordinated, data-driven approach to maximize the value of every investment.
While this can often be challenging for healthcare organizations due to decentralized processes and lack of inventory visibility, health systems should consider working with an experienced partner to integrate clinical engineering data with financial and operational insights in one platform. As access to equipment data and inventory metrics expands, health systems will gain real-time visibility into how their medical equipment investments are performing—and where the most critical needs exist. This will allow health system executives to make informed choices about when to repair, replace, or reallocate devices.
The right partner will also be able to access large amounts of data across multiple health systems around the country. This large-scale data and broader sample size enables more reliable benchmarking to improve predictability and inform sound decision-making.
The ability to analyze industry-wide utilization data and trends will help health systems stay ahead of potential supply chain disruptions too. This is especially valuable at a time when 90% of healthcare supply chain professionals foresee major disruptions due to increased costs and price volatility, according to one survey. That same survey found 81% of medical equipment manufacturers predict longer lead times and supply shortages stemming from increased production costs and import restrictions.
While it’s crucial for a health system to have an in-depth understanding of its own data, having a clear view of the broader supply landscape allows the organization to predict and prepare for potential sector-wide risks well in advance.
Enhancing Cybersecurity Through Data
Cybersecurity has become a crucial component of HTM as more devices become connected to hospital networks, and health care remains a top target of cyberattacks. More than half of connectable medical devices have known critical vulnerabilities. Up-to-date and accurate data is the foundation of strong cyber defenses.
Health systems should prioritize working with a partner that can aggregate real-time information on device vulnerabilities, software versions, and patch histories. This information will equip clinical engineering and IT professionals to proactively identify and mitigate cyber-risks before they impact patient care. Teams can also use this information to decide if a vulnerability should be addressed through a patch, an upgrade, or a full device replacement.
Increased visibility across the organization will make it easier to spot anomalies or potentially unsecured devices, which is vital when a healthcare data breach takes, on average, more than 200 days to identify. This data-driven approach not only reduces exposure to cyber threats but also supports compliance with evolving regulatory standards. As the digital footprint of medical devices grows, data-driven cybersecurity is essential to protecting both patient safety and hospital operations.
The Role of AI
Artificial intelligence has the potential to accelerate access to data and improve reporting across HTM—but its effectiveness depends on maintaining accurate, reliable foundational data. By aggregating not only medical device attributes but also broader healthcare data, AI has the potential to help ensure the right equipment is available at the right time and place.Â
An eventual integration with systems like electronic medical records, electronic health records, and scheduling platforms could also support more adaptive, data-informed patient care.
Putting Data-Driven Insights to Work
As health systems navigate increasing financial pressures and operational complexity, data-driven HTM has become a necessity. From predictive maintenance and smarter capital planning to enhanced cybersecurity and AI-powered decision-making, data empowers health systems to operate with greater precision, agility, and impact.
By transforming raw information into actionable insights, health systems can make objective decisions that allow them to optimize the value of their clinical assets and better serve their communities.
About the author: Christopher Becks is president of clinical asset management solutions at TRIMEDX. Becks brings more than two decades of leadership experience in healthcare technology and asset optimization, including nearly six years with TRIMEDX in commercial and operational executive roles. Prior to joining TRIMEDX, he had senior leadership positions at Aramark Healthcare Technologies and served as principal and owner of BioMedical Solutions, Inc.
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