Six years after an industry push to standardize CMMS maintenance records, adoption remains limited, hindering comparisons across organizations.
By Alyx Arnett
Healthcare technology management (HTM) departments have years of maintenance records documenting equipment failures, downtime, and repair costs. But meaningful comparisons of that information across healthcare organizations remain largely out of reach, even after an industry effort to establish common standards for how maintenance work is documented.
That effort, sponsored by the Association for the Advancement of Medical Instrumentation (AAMI), began in 2020. Drawing on an analysis of 2.5 million work orders from six major computerized maintenance management system (CMMS) vendors, the collaborative published white papers recommending 14 failure cause codes, followed by 10 work order types in 2021.
But six years later, the recommendations have seen limited adoption, and differences in how HTM departments classify equipment failures and maintenance work continue to stand in the way of meaningful comparisons across organizations, says Carol Davis-Smith, CCE, FACCE, AAMIF, who co-authored the white papers.
“Unfortunately, [the issues are] very similar still,” says Davis-Smith. “We, as a community, do not have consistency or any sort of standardization across all of our programs in terms of data.”
Why Widespread Adoption Has Been Difficult
One of the biggest obstacles to widespread adoption of the recommended failure cause codes and work order types has been the desire among HTM departments to maintain control over how their maintenance data is categorized, says Davis-Smith. She says many health systems were reluctant to abandon their existing terminology, while CMMS suppliers continued accommodating customers who wanted to customize their systems. Some CMMS vendors attempted to incorporate the recommendations into their standard configurations, Davis-Smith says, but encountered resistance from customers who preferred their own categories.
“I think the reason the vendors did not lock it down is because their client said, ‘Do not lock it down because I want to make these changes. I want to customize it to myself,'” Davis-Smith says.
That’s been the experience at CMMS vendor FSI, according to Joe Stockman, director of product experience. Although FSI wasn’t among the six vendors involved in the standardization effort, Stockman says the company has raised the possibility of adopting the published recommendations with customers implementing new CMMS platforms, but, he says, “I can’t think of any of our HTM customers that have said yes.”
The response has been different among FSI’s facilities management customers. A similar standardization effort in healthcare facilities management has seen somewhat greater acceptance. With support from the American Society for Health Care Engineering (ASHE) and the Facility Guidelines Institute, a group of healthcare professionals developed recommended classifications for buildings, spaces, building systems, and assets, with the goal of establishing more consistent terminology across healthcare organizations. Stockman says approximately half of FSI’s facilities management customers have been willing to adopt those recommendations.
That willingness has been harder to find among HTM customers. Stockman believes limited awareness of the HTM recommendations, along with resistance to change, has contributed to their lack of adoption. He says he doubts voluntary adoption will be enough to bring consistency to CMMS data across healthcare organizations and third-party service providers.
“I just don’t see it catching on without somebody or some agency or some requirement that makes you,” he says.
Standardizing Data Without Industrywide Standards
Jeremy Cook, senior director of HTM at Methodist Le Bonheur Healthcare, believes greater consistency across the industry would allow HTM departments to compare their performance, learn from one another, and avoid developing their own approaches to documenting maintenance work.
“If we all want to basically be able to learn from each other and not have to keep reinventing the wheel at a local level, then we all have to be practicing and documenting the same way,” Cook says.
At Methodist Le Bonheur, Cook and his team began their own CMMS data standardization effort five years ago, starting with a fundamental problem: making sure equipment manufacturers and models were identified consistently in the system.
The department worked to eliminate variations in manufacturer names, checking company websites to establish consistent naming conventions. They also had to account for equipment carrying the names of companies that had since been acquired, distinguishing the manufacturer shown on a device from the company currently responsible for it.
Getting those names right laid the groundwork for more reliable reporting and analysis. With equipment identified consistently, the department could more accurately examine maintenance histories and costs across devices from the same manufacturer or model, rather than having that information scattered across differently named records. The team subsequently expanded its standardization efforts to equipment types and failure cause code categories.
To keep equipment records consistent across its approximately 40 to 50 imaging and biomedical engineering staff members, Cook’s department locked down standardized fields so technicians can’t change them. When technicians add equipment already configured in the CMMS, the system automatically fills in the standardized information.
“None of that stuff is the technician’s ability to change in our system,” Cook says.
The department designated an employee to oversee new equipment entries. When a manufacturer or model isn’t already in the CMMS, that employee verifies the information and creates a template for future entries.
Cook says the approach has reduced the manual work involved in maintaining the database. He estimates that 90% to 95% of incoming equipment now matches an existing template.
Improving CMMS Data Without Waiting for Standards
Inconsistent CMMS equipment information and maintenance records are widespread problems across HTM departments, according to Davis-Smith. She encourages departments to clean up their existing records and put processes in place to keep the data standardized going forward.
She recommends reviewing the previous five years of maintenance records, particularly because that history is important for alternative equipment maintenance programs and capital planning. How far back to go is “a strategy decision,” Davis-Smith says, requiring departments to weigh the risks of leaving older records uncorrected. Some situations, such as investigating a medical device failure involving a patient injury, may require maintenance records going back 10 years or more.
Davis-Smith says HTM departments with inconsistent CMMS data generally know they have a problem, but there are simple ways to identify specific inconsistencies. One is to search the CMMS for equipment from a particular manufacturer, she says. A department looking for all its GE HealthCare equipment, for example, may find that some devices are missing from the results because they’re listed under older company names or variations.
“You’re going to immediately say, ‘I don’t have all of it because we spell GE different ways, and GE has changed their name,’” Davis-Smith says.
Davis-Smith also advises departments to make standardized dropdown menus that are easy for technicians to navigate. Don’t provide too many options, she says, as long lists of similar codes can make it difficult to select the appropriate one.
“If you have too many choices, then what’s your confidence level of people picking the right type?” she says.
Departments should examine whether technicians are using these codes consistently, says Dmytro Okhrimchuk, founder and CEO of Leera AI. He warns that inaccurate coding can produce misleading results even when the data appears reliable.
“The dangerous part is that bad codes don’t produce messy data. They produce precise, confident numbers that are wrong,” he says.
For example, he says, overusing “use error” can make equipment failure rates appear lower than they are, while repeatedly classifying intermittent faults as “no problem found” can obscure patterns of repeat repairs. Those inaccuracies can affect preventive maintenance intervals, alternative equipment maintenance strategies, and repair-or-replace decisions, he says.
To identify potential problems, Okhrimchuk suggests comparing, for example, the failure cause codes selected by individual technicians, watching for unusually frequent use of catch-all categories, and checking whether repeat repairs on the same device are assigned different codes.
Okhrimchuk also recommends helping technicians understand how their maintenance records inform equipment and staffing decisions.
“Explain the why. Technicians rarely see what happens to their data after they hit save. Show them, ‘This is the report that decided whether we replace the ventilators, and this is the record a surveyor will ask for,’” he says. “A repair fixes one device; a good record informs decisions about the whole fleet. When technicians see their documentation being used, quality goes up.”
George Reed, director of clinical engineering and laser safety officer at WakeMed Health & Hospitals, recommends prioritizing cleanup efforts based on how the data will be used. “Do not try to fix everything at once. Start with the decisions you need to make,” Reed says.
If service costs are the concern, Reed recommends focusing on equipment records, work orders, and repair expenses to understand where money is being spent and whether the current service approach makes sense. If downtime is the priority, he says departments should concentrate on accurately recording which devices are unavailable, how long they remain out of service, and why.
Reed says departments don’t need to correct every inconsistency before they can begin using their data. “I do not believe CMMS data has to be perfect before it becomes valuable,” he says. “The better question is: Is the data dependable enough to support the decision we are trying to make?”
The Path Toward Industrywide Standards
Cook says that while individual HTM departments can improve the quality of their own CMMS data, meaningful comparisons across healthcare organizations will remain difficult without a common approach to documenting maintenance work. Despite the years his department has spent standardizing its records, he says he would be willing to change those practices if the industry could agree on one.
“I don’t really care what the standard is because I know that if I hang on to my standard, then we’ll never get to a benchmarking component,” he says.
Cook believes the benefits of industrywide standardization could extend beyond comparisons among HTM departments. Medical device manufacturers, he says, could gain valuable insight into how their equipment performs in the field, potentially identifying recurring problems and improving their products.
“If all of us had very rich data, then technically the OEMs would want to partner with us to get our data so they can improve their products based on the failure rate analysis that we’re seeing in the field,” Cook says.
He argues that this could also give in-house HTM departments a more influential role in relationships with manufacturers, making their service records a valuable source of information rather than simply documentation of completed maintenance.
For Davis-Smith, the limited adoption of the AAMI recommendations hasn’t diminished the importance of establishing common standards. She remains hopeful that HTM departments will eventually be able to compare equipment performance and maintenance outcomes across organizations, rather than relying solely on their own records.
“I absolutely have hope that we will standardize this data,” she says.
But Davis-Smith says the ultimate objective isn’t simply better benchmarking. “Benchmarking locally, nationally, globally would be great, but for me, it means better patient care,” she says.
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Alyx Arnett is chief editor of 24×7 Magazine. Questions or comments? Email [email protected].
