Jane Dickerson, PhD, DABCC, and Darci Sternen of Laboratory Stewardship Focus recently interviewed pathologist and informaticist, Ila Singh, MD, PhD, about the national effort to standardize lab test naming through TRUU-Lab. Singh is the chief of laboratory medicine and pathology informatics at Texas Children’s Hospital and professor at Baylor College of Medicine.
What is TRUU-Lab?
TRUU-Lab or Test Renaming for Understanding and Utilization-Lab, is an initiative that unites people who are involved in ensuring that laboratory testing is done correctly. TRUU-Lab stakeholders include clinicians; electronic medical record (EMR), laboratory information system, and instrumentation vendors; representatives of professional societies such as the Association for
Diagnostics & Laboratory Medicine (ADLM, formerly AACC); and even federal agencies, like the Centers for Disease Control and Prevention (CDC), Food and Drug Administration (FDA), and Centers for Medicare & Medicaid Services (CMS). The stakeholders consistently attend meetings and are invested in trying to get some standardization in laboratory test names.
There is a common realization that many errors happen because clinicians don’t necessarily understand what test to order. There’s very little standardization around selecting names for tests—in fact, most of the time, people are choosing lab test names in silos, often without consultation even within their own institution.
For example, there’s a paper from the Department of Veterans Affairs (VA) that shows there are more than 50 names for albumin just within the VA system (Med Care 2019;57:e22-7).
Can you tell us the story of how you got the idea for TRUU-Lab, and how it came to be?
Well, Patient-centered Laboratory Utilization Guidance Services (PLUGS) was indirectly involved in this because I was thinking about stewardship around 2018–2019 when I was on the National Committee for Laboratory Stewardship with PLUGS. And I was thinking about how each of us is sitting in our own hospital or lab stewardship test committees and having the same conversation about confusing vitamin D test names. It just struck me that there needs to be something more united. Additionally, it took me more than 6 months to unify vitamin D test names at my own institution. It’s just one test, and to think that to change the names —to put in a clinical decision tool that would guide people away from the 1,25 dihydroxyvitamin D test—it took that long! It just felt like an enormous waste of time for everyone. There should be something better, more unified, that would save all of us a lot of time.
And that’s when I thought we need to be working toward standardization. Around the same time, we also had a case of measles, and nobody could find the name of the test because it was classified in the system as “rubeola.” That also made me think that when the clinician is ordering a test, their only window into the test is that test name in the EMR.
It’s almost unbelievable that there’s more information available about a $5 item on Amazon than the most expensive test in an EMR.
The EMR makes no attempt to tell you that you may need a more extensive algorithm when ordering a test. If clinicians need more information, they often need to leave the EMR and consult a test catalog or use a search engine. If a laboratory wants to provide more information, it is forced to develop soft alerts or other clinical decision tools that slow everybody down with more clicks.
What are the most pressing goals for TRUU-Lab?
We have four major goals. The first is to find out what features of an individual lab test make it most comprehensible to the ordering providers. What parts of a test name are recognized as being helpful and which parts are unhelpful? Can we make some guidelines around test naming using our understanding of test names? That’s one of our biggest goals because most names have been created without the input of the people who use them.
The second goal is to use that understanding of test features and build a list of test names.
The third goal is to test them in a mock EMR, to put these TRUU-Lab test names alongside other test names and see if people select the intended test.
The final goal is to have these test names as part of a foundation build of all EMR systems, so that we could say “these are carefully selected and vetted names, and we all should use them.”
What is the strategy for identifying tests that could inform naming conventions for a broad range of laboratory tests?
One of the first projects that we did in TRUU-Lab was surveying American Society for Clinical Pathology members on what they thought were problematic test names. These are all laboratory people who have their own experiences of observing care providers getting confused with certain tests. We received 200 different responses and organized them into 10 categories, like “easy to mix up,” “synonyms,” “convention,” etc. We then went about conducting more scientific surveys—first educating clinicians about a given test and then asking them what features in a test name might be helpful for understanding what the test is about.
What is one key element of success for TRUU-Lab?
Building a diverse team is very important. For what we’re doing, I have found that it’s essential to have the diversity of thought that comes from federal liaisons (CDC, CMS) working together with people from all walks of pathology, geneticists, family practice clinicians, and obstetrician-gynecologists.
As an example of this, one team member had experience working in FDA and helped us design a failure modes and effects analysis to analyze potential errors in lab testing. That idea and process was not something I would have come up with on my own and highlights the value of different perspectives.
Do you have any high-level lessons from developing and analyzing surveys to share with readers?
We have learned a lot by working with the Brand Institute for survey formatting and development. The Brand Institute runs surveys for the pharmaceutical industry and has a large registry of providers who they reach out to and ask to take our surveys. We identify the types of providers we want to include (e.g., pediatricians, family medicine), and the survey is distributed with a specific ratio of providers. Through this process, we have learned that providers want more information included in the test name and fewer abbreviations. We’ve learned iteratively through the survey process and have taken great care to reduce bias to get the best information, for example, asking a question on the “best name” without using any names of the test in the question.