Please refer to our August 29, 2025 discussion, “Hemostasis Assay Statistical Variation.” In this post, we linked the article, Mullier F, Gouin-Thibault I, Meijer P, et al. Time to integrate measurement uncertainty in method comparison and interpretation of hemostasis laboratory assays. Res Practice Thromb Hemost 2025: 9, https://doi.org/10.1016/j.rpth.2025.102993. The authors contend that we should report uncertainty data with each coagulation assay result, for example, “PTT: 47 seconds ± 2.5 seconds.” The article attracted several comments on LinkedIn. In follow-up, our October 2025 Quick Question is a poll that asks, “Do you support publishing assay uncertainty data with all results?” Please select a response indicating your opinion. If you select the third response, “It depends,” please leave your comment below.
10/4/25: I want to thank my colleagues and friends for their valuable comments posted below. Here is the citation for a pub that illustrates Dan Kaczor‘s comment posted October 4, 2025: Cary ER, Fink LM, Stokes SL, Simmons VL, Kaczor DA, Harmon S, Quarles L, Escobar C, Maier DJ. Selection and implementation for coagulation instruments/reagents in a multiple-hospital/clinic network. Blood Coagul Fibrinolysis. 2000;11:599-608. doi: 10.1097/00001721-200010000-00003. PMID: 11085279. The article is available from your medical library. Also, here’s Dr. Favaloro’s citation, posted on October 2, 2025: Favaloro EJ. Uncertainties in ‘Measurement of Uncertainty’ Measurements: A commentary from the perspective of a specialist haemostasis laboratory. Aust J Med Sci 2006; 27: 72-83.
Abstract
Selection, standardization, and implementation of instrumentation and reagents throughout a health care facility network can often be a difficult process. However, in today’s ever-changing health care setting, it is often mandated. The Veteran’s Integrated Systems Network 16 (VISN 16) was faced with such a task early in 1999, with the targeted area being its coagulation laboratories. The plan outlined in this paper was drafted to help facilitate the selection, standardization and implementation of coagulation systems for 17 health care facilities that make up the VISN 16 network. The VISN, encompassing 170,000 square miles, has 10 tertiary care hospitals, six of which have close relationships with affiliate universities. There are 299,733 patients enrolled in this health delivery system. The facilities range from large institutions performing both tertiary and outpatient care to small outpatient clinics. Because of the plan’s detailed, comprehensive content, which included analyses of a large number of performance parameters as well as cost-efficiency, the selection process was carried out using a checklist that could be helpful to other organizations selecting equipment and reagents for coagulation studies. An implementation process was devised, resulting in coagulation standardization across the Integrated Health Network.
Bob, Dan and Emmanuel have all weighed in with some great comments on MU. Borrowing from some literature I found on the BIO-Rad website I submit the following cited literature.
“Clinical laboratories typically calculate and keep records of their measurement uncertainty, providing uncertainty values to physicians and auditors upon request. Physicians can use uncertainty ranges to make more informed treatment decisions. For example, when a result is near a clinical decision value, physicians can use uncertainty intervals to determine whether or not a result is definitively lower or higher than that decision value. Similarly, if a result is close to a previous patient result, evaluating those results in the context of their uncertainty intervals can help determine if they are significantly different enough to warrant a change in treatment or diagnosis. Taking all of this information into account can help a physician confidently make the appropriate patient care conclusions.
“A calculable range of uncertainty exists for any measurement, and once we understand how to calculate that range, we can accurately represent the laboratory’s confidence level for any given result. Calculating uncertainty is only a few clicks away with Unity Real Time, which provides three built-in uncertainty formulas for quick and convenient calculations. In addition to helping laboratories comply with regulations, logging uncertainty values also demonstrates a commitment towards a higher standard of laboratory quality with careful and thorough result records.
“Examples of the practical utility of measurement uncertainty estimates might include confirmation that patients’ values meet quality goals set by the laboratory and meaningful comparison of a patient value with a previous value of the same type or with a clinical decision value.”
–ISO 15189 5.5.1.4
Reference
International Organization for Standardization. ISO 15189: 2012 Medical laboratories–Requirements for quality and competence. 2012.
Personal comments by mine are always directed towards the practical side of things. For example: “What is clinically significant vs statistically significant?” As mentioned earlier will employing the MU help the laboratory turn out a result that will enable the physician to determine definitely if they need to take an action in the patients treatment plan.
Testing laboratories often find the approach required to determine the time it takes to obtain the MU is not practical. Testing laboratories may choose to use a variety of data-driven approaches using laboratory data from calibrations, quality controls, or validation.
Is the posting of the MU necessary for every lab value a clinical laboratory really necessary or does it give one more number to “muck up the situation.”
Dave McGlasson
Not wishing to trivialise the topic, BG makes a good point about accuracy; MU gives an indication of the ‘accuracy’ of the test result for the presented sample; we have no idea able the validity of the test result for the patient, since we have no idea if the sample is accurately representative of the patient, dependent on proper collection and processing. Also, given biological variability, we have no real idea of the accuracy of the test result for the patient longitudinally. If we add MU to the patient report, should we also add information about biological variability (BV) to the report to give clinicians an ‘accurate’ measure of the ‘true’ patient report?
Dan Kaczor makes an excellent point…all the listed variables contribute to Measurement of Uncertainty (MU), but none of those are assessed with MU. MU is determined from QC precision data…which has really little to no pre-analytical variable associated with running that material. Thus, what MU is really assessing is the precision around a result, and not really the accuracy of the test result, which can mostly be affected by pre-analytical variables in hemostasis testing, the largest contributor to less accurate results So MU equals “trueness” around a particular number, but that does not mean “trueness” of the result.
Hi George,
My vote was a clear “NO” to your poll on publishing assay uncertainty with all results, which is why I initially chose not to comment (since you invited feedback mainly from “it depends” respondents). However, after reading the thoughtful contributions from Dan, Bob, and Emmanuel, I thought it might be helpful to share my perspective as well.
I fully agree with the authors of the RPTH commentary on the importance of recognizing uncertainty in laboratory results. However, I disagree with their recommendation to include quantitative uncertainty values with every reported measurand—particularly in reports issued to clinicians. It is important to distinguish between the extensive quality control measures and validation processes that take place behind the scenes in diagnostic laboratories and the expectations of clinicians who rely on those results to make timely, informed decisions.
Laboratories should, of course, maintain and document uncertainty or imprecision data for all active assays, readily available to auditors and clinicians upon request. When poor assay performance is identified, the laboratory must take corrective action—such as repeat testing, replicate analysis, or requesting a new sample—to ensure confidence in the reported results.
Clinicians, on the other hand, need clear and actionable results—concise, reliable, and timely—while retaining the option to explore deeper analytical details when necessary. In sound medical practice, any borderline or critical result that may influence patient management should prompt confirmatory or repeat testing, inherently addressing analytical uncertainty.
For these reasons, I do not believe that adding numerical uncertainty (e.g., ± values or percentages) to every laboratory report would meaningfully enhance clinical decision-making. Such an approach may be appropriate in research settings, clinical trials, or scientific publications, but not in routine clinical practice.
Hi George, I think that reporting MU’s with any coagulation result would be a disaster for the discipline. For most of my 40 plus years in coagulation it was clear that coagulation was the most misunderstood and even scary part of the laboratory. Fortunately, we’ve worked tirelessly to significantly improve all elements of this area of laboratory medicine from testing to understanding the impacts of the results. In simple terms I would breakdown areas that could lead to uncertainty in the following way:
1. Sample…
Poorly obtained
Poorly processed
Poorly stored
Poorly tested
Poor patient history prior to phlebotomy
2. Tech skills/experience…
Inexperience
Multitasking/rotation
Training
3. Reagents…
Sensitivity
Responsiveness
Stability
Lot to lot consistency
4. Instrumentation..
Full automation (like in Chemistry lab)
MU calculations don’t take into consideration the impact of #2 and perhaps #1 above. I am sure we could add to each area, but the reason I break it down this way is to focus on areas where we have made significant improvements towards certainty and those areas where uncertainty still resides regardless of the laboratory department. We’ve helped manufacturers significantly improve the performances of reagents and instrumentation to now rival Chemistry lab combinations.
On the other hand issues related to samples and tech skills and experience will be in my opinion perpetual contributions to potential uncertainty. This is becoming more pronounced as department specialization is changing to multitasking. We ran specialized coagulation departments where all aspects were at the top of the game. I never had any reason to doubt a final result that left my lab be it numerical or yes/no. Of course if there was an unknown sample issue we may not have been able to catch it, but most of the time we did so that the results generated were accurate.
The CLIA requirements have also aided in making results better. We’ve all worked very hard to bring coagulation out of the dark ages and we did this without attaching MUs to our results! In a way I would consider this action as an insult to all of our hard work. Promoting this concept of MUs would certainly destroy all progress that has been made especially with providers who use our results to manage their patients. I can’t imagine trying to explain to these people how to look at a result and interpret it along with a MU attached.Emergency docs and surgeons would kick us out of the hospital.
I guess that you can figure out that I am a strong no to attaching MUs to any coagulation result! It will kill all of the progress that we’ve been part of and may cause irreparable harm to the discipline that we all love. Dan
Measurement of Uncertainty (MU) is gaining US traction for unclear reasons, as EJF noted, they have been dealing with this for a while, likewise the Europeans. What is unclear, at least to me, is the minimum number of QC events required to create an MU for each assay. Using periods of time is not sufficient, as some QC is performed 1–3 times a day, others weekly, or even monthly. The International Council for Standardization in Hematology (ICSH) will be publishing (soon or in 2026) provisional guidance for determining hemostasis MU. This document is led by Stephan MacDonald, a brilliant lad from the UK, and I would strongly advise listening to any webinar or session he might give for IVD or conferences. The CLSI guidance document (EP-29A) is not really applicable to hemostasis testing. While we all know about the limitations and relative imprecision issues we have in hemostasis, as compared to our chemistry colleagues, I concur with Dr Favaloro that this information should not accompany each reported result, but still struggle with how to share the utility of this value. I have asked whether there should be different MUs for a given test when applied to different indications. I think our pharmacy colleagues would benefit from knowing APTT MUs when deciding dose adjustments based on the heparin therapeutic range. Unclear how qualitative (pos/neg) tests that have numeric values (i.e. HIT assays) are affected by MU around the designated cutoff. For me, there is uncertainty of this measurement.
Hi George, this is one of those conversations where we would preface the comment with “In an ideal world…” It is funny that Measurement Uncertainty has resurfaced as a ‘hot topic’ in 2025. In Australia, Measurement Uncertainty (MU) became a big thing in the mid 2000s. I even wrote a review paper on this topic in 2006 for our National Medical Scientist journal (Favaloro EJ. Uncertainties in ‘Measurement of Uncertainty’ Measurements: A commentary from the perspective of a specialist haemostasis laboratory. Aust J Med Sci 2006; 27: 72-83.). The local accreditation body (NATA) wanted to see everyone’s data for MU before they were granted accreditation. The initial hype gradually waned, and although this is still a requirement of accreditation, we no longer lose any sleep over this. We discussed at length at various forums whether to include MU data in reports. The general consensus was that although it was important to do and have data on hand in case the clinicians wanted to see the data, it would not be included in reports. There are two major caveats: 1. The clinicians are already overwhelmed with data on their patient reports, including a long list of tests with patient results over time and normal ranges. We assist the clinicians by highlighting abnormal results. However, it was felt that the inclusion of MU data would overwhelm doctors too much. No clinician has ever asked for a formal report with MU data included in my years of practice. Occasionally, a clinician may ask how relevant a result is around the cut off, and we would have a professional discussion. 2. It was thought that the inclusion of MU data may give the clinicians an incorrect impression of high test imprecision (or ‘crappy results from the lab’). No lab service wanted to do this; and indeed, lab services could compete on the basis of their MU data, giving false impression that lab A yielded more accurate test data than lab B–just based on how they calculated the MU.