HTM leaders share the practical changes—some simple, some more strategic—that are moving the needle on preventable equipment outages.

By Alyx Arnett

Downtime is a given in healthcare, no matter how well a department is staffed or how new the equipment is. “Taxes and downtime—those are the certainties in life,” says David Brennan, chief product officer and senior vice president at the medical parts procurement company PartsSource.

But healthcare technology management (HTM) leaders emphasize that even if failures can’t be eliminated entirely, they can be reduced. Here, they share insights across four key areas that are helping cut avoidable downtime.

1. Leveraging AI for Faster Repairs

Dan Miles, vice president of IT at third-party service organization Intelas, has seen significant improvements in first-time fix rates through artificial intelligence (AI)-powered diagnostic tools. His team developed proprietary software that provides technicians with recommended repairs based on historical data and equipment service patterns.

“This is an AI capability that looks at all the history and capabilities, and it presents to the technicians, ‘Here’s how this type of equipment was serviced previously for the same common issue,’” says Miles. “And that speeds up repair.”

The platform also consolidates previously scattered information—such as service histories and manuals—into one place. Technicians can run AI-powered searches from their mobile devices to quickly surface guidance.

“AI can read the manual faster, and the technician could ask the AI, ‘I’m seeing this error code. What does it mean?’” says Miles. “The AI had already ingested those manuals for that type of equipment and is able to regurgitate back to the technician.”

According to Miles, these capabilities have helped Intelas reach an 84.5% first-time fix rate over the past seven months, compared to the industry average of 70% to 75%.

But he notes that HTM teams don’t need proprietary AI to start seeing improvement. Miles recommends beginning with the fundamentals: consolidating data sources and looking for patterns across supported equipment types.

“Consolidate information to the people that are out in the field working,” he says. He adds that even “cheap and dirty” analytics tools—such as Microsoft Power BI—can help identify trends in failures, parts needs, or recurring service issues. “Patterns are key,” he says. “Those are simple ways to be able to service it without the big technology.”

2. Optimizing CMMS Performance

A computerized maintenance management system (CMMS) can be a powerful tool for reducing equipment downtime, says Rich Sable, product manager at TMA Systems, which offers the EQ2 HEMS CMMS platform, and it starts with having complete and accurate data.

Without correct serial numbers, purchase dates, vendor information, and software versions, technicians lose time tracking down details instead of troubleshooting, he says. And when they’re on the phone with tech support, missing fields can slow everything down even further.

Accurate data also supports better prioritization. Sable notes that CMMS platforms can calculate risk at the device-type level, automatically assigning the correct priority based on whether the device is high- or lower-risk equipment. “This way, when the work orders are coming in, the criticality of the device itself is properly identified,” he says. 

Preventive maintenance, when scheduled and tracked properly through the CMMS, can also prevent failures. “Preventive maintenance could limit downtime by almost up to 30%,” Sable says. 

Parts management is another CMMS feature closely tied to downtime. Missing spares—or long backorders—can delay repairs for months. Sable suggests using min/max thresholds, so the CMMS automatically reorders frequently used items. “It’s a critical thing,” he says, noting that many organizations still fall behind on preventive maintenance solely because parts never arrived.

CMMS platforms can also interface with cybersecurity and RTLS tools, allowing IT-related updates (like software versions or network identifiers) to flow directly into the system, automatically triggering work orders when software recalls apply, and helping technicians quickly locate mobile devices such as infusion pumps.

Standardizing failure codes in the CMMS is another area where Sable sees clear value. Several years ago, AAMI brought together CMMS vendors and HTM leaders to develop a short, mutually exclusive list of failure codes to replace the long, overlapping lists many hospitals use. Sable says EQ2 HEMS adopted that list, so technicians don’t have to guess between similar codes. With clearer choices, recurring issues stand out more quickly in the data.

For HTM leaders unsure where to begin, Sable recommends starting small: “They have to at least measure the downtime that they’re seeing now and where the pain points are.” From there, teams can dig into which device types and models fail most often—and start addressing the root causes.

3. Strategic Parts Management

Parts delays remain one of the most persistent contributors to equipment downtime, says PartsSource’s Brennan. While supply chain pressures have eased since the height of COVID-19, disruptions still occur regularly. “Typical [integrated delivery networks] lose tens of millions of dollars in revenue….every year due to unplanned downtime,” he says. “Parts delays and parts fulfillment are a material part of the downtime story.”

According to Brennan, delays can come from multiple points in the supply chain, including manufacturers with material shortages or low production yields, quality issues that halt shipments, missed logistics handoffs, or parts sent to the wrong location. The problem is compounded by the number of proprietary components that have no secondary sourcing option.

Because no single strategy fits all equipment types, Brennan recommends HTM teams start by stratifying their parts inventory. High-frequency items—such as batteries, infusion pump covers, and other components prone to drops or wear—are worth stocking onsite. But most parts don’t break often enough to justify local inventory. “Eighty-five percent of what hospitals buy on an annual basis, they buy less than twice a year,” Brennan says. “It’s a really long-tail supply chain.” For expensive items like CT tubes, a regional distribution model is more realistic than keeping spares in-house, he says.

Historical consumption data can help forecast needs, but Brennan notes that most individual hospitals don’t have enough volume to identify reliable patterns. He encourages teams to work with partners—or adopt internal processes—that help interpret demand signals, identify second- or third-sourcing options, and guide purchasing toward the most reliable suppliers.

For HTM departments managing parts independently, Brennan recommends implementing an active quality management program. “You’d have to track religiously the performance of every transaction,” he says. This means measuring return rates, shipping accuracy, fulfillment speed, and vendor errors. He also emphasizes standardizing procurement pathways so technicians aren’t navigating dozens of vendor relationships with inconsistent pricing and processes.

4. Enhancing HTM-Clinical Communication

Clear communication between HTM and clinical teams directly influences how quickly problems are identified and resolved. Radhika Kumar, CCE, network vice president of clinical engineering at clinical engineering services company TRIMEDX, says, “HTM teams seeking to strengthen relationships with clinicians should begin with proactive engagement and transparency….Presenting solutions rather than just problems helps build trust and positions HTM teams as partners in patient care.”

TRIMEDX supports this approach with layered communication practices. Automated messaging through its CMMS platform provides real-time updates whenever ticket status changes, and a self-service portal allows clinical leaders to check progress without waiting for callbacks. A dedicated Client Experience Center serves as a safety net for urgent inquiries, but Kumar notes that responsibility for communication ultimately rests with HTM personnel—whether through automated documentation or direct check-ins during repairs.

Day-to-day coordination also plays a role. Rounding with clinical teams helps surface issues early, and shared dashboards give both groups visibility into equipment availability and open tickets. TRIMEDX’s Predictive Work System further supports communication by identifying device issues before they escalate, giving technicians time to plan repairs around clinical schedules.

A recent sterilizer issue illustrates how collaborative communication can reduce downtime. Billie Thurston, network vice president of clinical engineering at TRIMEDX, describes how facilities staff, clinical users, and HTM technicians worked together to troubleshoot the problem. Each group reviewed its part of the workflow—from steam traps to internal processes to the equipment itself—until they identified that instrument wrapping and tray selection were contributing to failures.

“By working together and sharing information openly, we were able to resolve the problem and eliminate about five days of downtime,” Thurston says.

Looking ahead, stakeholders expect predictive maintenance capabilities to play an even bigger role in reducing downtime. Miles’ team has already developed a program that monitors equipment telemetry data 24/7 using machine learning algorithms to predict failures.

“If you could get from being reactive to proactive, where, if something becomes out of spec, like helium levels, we will know and take a proactive approach. We’ll schedule the maintenance with our customers, so we don’t have that downtime,” says Miles. “That’s really the next emerging capability.” 

Sable expects AI integration to become a larger part of CMMS platforms. “AI thrives on data, and the CMMS is filled with data,” he says. TMA Systems plans to introduce AI capabilities that will allow users to get answers by asking the CMMS plain-language questions. He believes this shift will make it easier for HTM teams to identify failure patterns and rising problem areas.

As predictive tools and AI advance, HTM leaders say the goal remains the same: addressing potential failures earlier and keeping equipment available for patient care.

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