From Cells to Spells (AACC)

May 12, 2022

 

A Brief History of HLA Testing in the Clinical Laboratory

Human leukocyte antigen (HLA) testing has been a staple of transplant medicine since the 1960s, when researchers discovered that crossmatches could reliably predict transplant allograft rejection (1). Although methods have changed dramatically since then, the premise that it is unethical to perform a transplant in the absence of HLA testing remains.

Interest in transplant immunology, specifically in the understanding of HLA and its implications for transplantation, has only increased over the past 60 years. Early on, the understanding was that the donor had to be a “match” for the recipient. While this concept is correct overall, in that the donor and recipient must be compatible, our understanding of what compatibility looks like has evolved considerably.


Let us take a brief tour of the history of HLA testing and its evolution from cells to spells.


MAKING A MATCH


From the late 1960s through the early 1980s, compatibility was determined by cytotoxicity dependent crossmatch (CDC). Donor serum was added to recipient cells, and if the cells remained viable, then the pair was considered compatible—a “match.” This method worked remarkably well, with transplant outcomes improving from ~35% mortality within the first year of transplant in the pre-crossmatch era (1963–1969) to <18% in the immediate years following implementation of the CDC (2). Notably, mortality within the first year post-transplant is ~5% today (3).


The basic premise of the CDC is that the presence of donor-specific anti-HLA antibody in the recipient serum induces complement fixation resulting in donor cell death (Figure 1). The production of HLA antibody in the context of a foreign graft relies on allorecognition. Various antigen-presenting cells present processed antigen to CD4+ T-cells that trigger an immune response. Upon T-cell activation, the CD4 helper T-cells release various cytokines that, in addition to activating CD8 killer T-cells, also activate progenitor B-cells that will begin to produce antigen-specific antibodies. In most cases this is a donor HLA peptide, leading to the production of donor-specific HLA antibodies.


Vascular endothelial cells are the preferential target of the immune response due to the abundance of antigens they express. When antibodies bind to antigens within the graft endothelium, complement molecules, particularly C1q, bind to the antigen-antibody complex and activate an intricate cascade of reactions. These result in the formation of the membrane attack complex (MAC) that disrupts the integrity of the cellular membrane resulting in cell lysis. 


Cell death in situ in the CDC is certainly predictive of a poor outcome for the allograft in vivo, where activated complement can also be responsible for the recruitment of neutrophils, macrophages, and inflammatory markers that further damage surrounding tissue. This process results in inflammation, tissue injury, and thrombosis, leading to antibody mediated rejection and, ultimately, graft failure (4).


IMPROVING SENSITIVITY WITH FLOW CYTOMETRY


The CDC became the cornerstone of compatibility in transplantation. In the mid-1980s, however, a new flow cytometric crossmatch (FLXM) technique was developed that was found to be far more sensitive than the CDC (5). In this method, donor serum is still added to recipient cells, but now instead of adding exogenous complement to facilitate antibody-mediated cell death, an antihuman IgG antibody with a fluorescent tag is added. The mixture is then run through a flow cytometer, and increased fluorescence is indicative of incompatibility between donor and recipient (e.g., recipient has donor-specific HLA antibodies). The FLXM was more sensitive than the CDC; however, in 1999 an article was published highlighting the lack of specificity and questioning the clinical utility (6). At that time, an understanding was emerging that not all antibodies are created equal.


Until the lack of specificity of the FLXM was understood, the HLA was thought of as the only antigen on the cell surface. We now know that there are many antigens on the surface of a cell, all of which can bind antibodies of certain specificities (Figure 2). It is these other antigens that contribute to FLXMs that appear to be clinically irrelevant. These particular, non-HLA antibodies generally do not cause damage to the allograft, so a transplant between a donor and recipient that demonstrates a positive FLXM can still have outcomes identical to those of a pair with a negative FLXM. Therefore, it is critical to identify when a FLXM is positive due to HLA antibodies versus non-HLA antibodies.


SOLID PHASE TESTING ADDS SPECIFICITY


In the mid-1990s, researchers developed the solid phase testing methodology in which recombinant HLA antigens are conjugated to polystyrene microspheres (Figure 3). These beads can then be added to a patient’s serum, and any HLA antibody specific to the antigens represented will bind to the beads. A fluorescently labeled secondary anti-human IgG antibody can then be used to identify which beads—and therefore, which antigens—are positive (i.e., which specific HLA antibodies a patient has in circulation). Notably, upon the widespread utilization of solid phase testing, it was possible to distinguish exactly which HLA a recipient had antibody against at the antigen level.


In parallel to the development of solid phase testing, many laboratories began using molecular methods for HLA typing. These methods revealed that there was much more to HLA antigens than initially understood. Far more polymorphisms were discovered by molecular methods than had previously been distinguished by serological methods. For example, one of the first HLA antigens identified by serology was designated HLA-A2. However, when molecular methods entered, it was discovered that A2 had several polymorphisms that had not been serologically determined. Thus, these were designated as alleles of A2 (HLA-A*02:01, HLA-A*02:06, etc.).


The nomenclature went from a locus- (e.g., A) and antigen- (e.g., A2) based system to an allele-based system of locus (A), antigen (A*02), and allele represented by the four-digit designation (A*02:06). Notably, while >25,000 HLA alleles have been characterized, only the most frequently occurring 60 to 70 serologically determined HLA antigens are currently identified by solid phase testing.


THE ERA OF VIRTUAL CROSSMATCH


As a complement to the great specificity of the solid phase HLA antibody testing and molecular typing methods, the mid-2000s ushered in the era of the virtual crossmatch (VXM). By knowing the specific HLA antibodies in the circulation of the recipient and the HLA genotype of the donor, the compatibility of the pair could easily be predicted. It was found that the VXM had better specificity than the FLXM and that outcomes of transplants that proceeded based on VXM had equally good outcomes (7).


Currently, as we begin the 2020s, the assessment of donor/recipient compatibility relies on VXM-acceptable mismatch strategies, with positive VXM/unacceptable mismatches defined by the presence of donor-specific HLA antibodies targeting the HLA antigens of the donor as determined by the HLA genotype. It is important to remember, however, that a negative VXM—indicating a compatible donor/recipient pair—does not mean that the pair is HLA matched. In fact, it has been demonstrated that increasing the HLA mismatch results in development of de novo donor-specific HLA antibodies (DSA) post-transplant. These are correlated with antibody mediated rejection and worse outcomes (8).


For this reason, the VXM/acceptable mismatch approach to deceased donor kidney allocation has been challenged by proponents of HLA epitope matching algorithms that claim to offer a more precise assessment of compatibility.


UNDERSTANDING EPITOPES


To date, HLA has been primarily thought of as a group of antigens. However, as understanding of antigen/antibody interactions has progressed, HLA perhaps should be recognized as a grouping of epitopes. An epitope is defined as the region of an antigen to which an antibody binds (Figure 3). Each antigen can have multiple epitopes; conversely, a single epitope may be present on multiple antigens.


Each individually identified HLA antigen will carry a “private” epitope. This is the single nucleotide polymorphism, resulting in a single amino acid change, that will distinguish the allele from others of the same serological group. However, cross reactive groups (CREGs)—where several antigens will react serologically with a single serum—have long been recognized among HLA antigens. Understanding the presence of epitopes has now revealed that many of these CREGs represent a single epitope binding to a single antibody. It is now easier to think of an HLA antigen as a collection of epitopes, all of which are shared with other HLA antigens. Under this framework, it has become clear that “matching” donors and recipients at the antigen level is insufficient.


The concept of epitopes within the field of transplant immunology was brought to the forefront by the work of Rene Duquesnoy (9). However, for many years the field was skeptical of this new point of view. It wasn’t until almost a decade later, when epitopes were proven to be predictable based on the structural, physiochemical properties of the amino acid polymorphisms, that the epitope-based theory of HLA became widely accepted (10). Not long after, several software algorithms were developed to help better understand the level of epitope matching, or mismatching, between donor/recipient pairs. The first was HLA Matchmaker by Duquesnoy (9) which was soon translated to the Epitope Registry (11).


Development of de novo DSA post-transplant correlates with the level of epitope mismatch between the donor and recipient, also known as epitope load (12). However, HLA Matchmaker and the Epitope Registry only account for the antigenicity of the epitope—how the epitope interacts with an antibody. In the context of de novo DSA, it is also critical to consider the immunogenicity of the epitope or its ability to induce an antibody response (12).


In a 2011 publication, Kosmoliaptsis et al. reported that the physicochemical polymorphisms of amino acids, such as hydrophobicity and electrostatic properties, were also predictors of an alloantibody response (10). They found that the HLA amino acid mismatch score (AMS) and electrostatic mismatch score (EMS) were associated with the development of DSA against donor HLA Class II mismatches after renal transplant, but only the EMS correlated with the risk of HLA Class I DSA development. These data indicate that differences between donor and recipient HLA amino-acid sequences—as well as the physicochemical properties of the epitope mismatches—enable better assessment of the risk of de novo DSA development and subsequent graft failure than conventional HLA matching.


TIME TO REDEFINE DONOR/RECIPIENT COMPATIBILITY?


The impact of epitope load on DSA formation and graft survival has led to the suggestion that compatibility of donor/recipient pairs be redefined as epitope matching or the level of epitope load. Indeed, there may be several advantages to this approach. Firstly, it may allow increased access to transplantation for highly sensitized individuals—those with high levels of pre-existing anti-HLA antibodies. Determining compatibility based on the epitope load would, theoretically, allow for organ allocation to highly sensitized patients despite presence of pre-exiting DSA. The donor epitope repertoire would be considered for compatibility, rather than simply the mismatched antigens. This would potentially allow for more acceptable allele combinations, thereby expanding the donor pool (13).


Epitope considerations may also be beneficial for recipients who are less sensitized. Perfect donor/recipient HLA allele matching is clinically impractical in the context of over 25,000 HLA alleles across 11 HLA gene loci. In contrast, with a smaller number of epitopes that may be shared across different HLA alleles, accomplishing compatibility at the level of the epitope may be more feasible (14). However, the overall feasibility of determining compatibility based on epitope load still faces many challenges.


The first step toward implementing epitope matching relies on the availability of allele-level HLA genotyping. Genotyping of a deceased donor is highly time sensitive, and for this reason, laboratories choose their methods primarily for a rapid turnaround time and offer only intermediate level typing at best. That is, these methods often cannot resolve between common alleles.


At times, the allele-level typing is imputed based on associations between alleles at other loci that are well documented in large populations. However, recent studies have shown that imputations are often inaccurate, and the inaccuracies are more pronounced when applied among patients of non-Caucasian self-reported ancestry (14). This limits the accurate assignment of epitopes in deceased donors as well as in recipients being typed by low resolution methods, which is still common at many centers.


The feasibility of epitope matching in the context of deceased-donor transplant is also limited by time. It is often necessary to utilize more than one software package to both identify the epitopes and then assign the epitope load of the donor. The laboratory must then cross-reference this information with the pre-formed DSA to completely rule out those epitopes, as well as determine the remaining epitopes of most concern to inform acceptable mismatching—a time-consuming endeavor. Moreover, while increased donor epitope load has been correlated with worsened outcomes, not all epitopes have thus far been shown to be deleterious. That is, the antigenicity of some identified epitopes is still in question; antibodies are likely to bind strongly to some epitopes and only very weakly to others. Understanding which epitopes are which is going to be critical to an acceptable mismatching strategy.


Finally, while efforts are underway to identify the most immunogenic epitopes, what has not been considered is the risk of allograft injury associated with re-exposure to epitopes, which may accelerate immune response and injury (14). Patient sensitization after prior transplant, transfusions, pregnancies, etc. is difficult to account for, and it is possible that recipients may experience a strong memory response to highly immunogenic donor epitopes even in the absence of detectable existing DSA. It is equally likely that a recipient may have no response to previously encountered epitopes that are not very immunogenic.


Our understanding of transplant immunology has evolved tremendously from the days of the CDC into the current epitope era. The concept of compatibility itself has evolved from relatively simple in terms of “matching” at the cell level to something incredibly complex in the context of epitopes and acceptable mismatching.


As we consider the current obstacles to allocating organs based on epitope load, it may seem akin to casting a magic spell. However, in the 1960s, predicting transplant outcome based on mixing serum and cells seemed like magic as well. There is only a thin line of understanding between magic and science, and as the field of transplantation develops a laser focus on improving long term outcomes, it is only a matter of time before our understanding evolves again. 


Tiffany Bratton, PhD, DABCC, FAACC, FACHI, is the director of laboratory services at Clinical Trial and Consulting Services in Covington, Kentucky. +Email: tkroberts56@outlook.com


HLA AND COVID-19


A January 2022, advance online publication titled ‘Association of HLA gene polymorphism with susceptibility, severity, and mortality of COVID-19: A systematic review’ evaluates the extent to which HLA may contribute to COVID-19 susceptibility, severity, and mortality. The review is a meta-analysis of 36 published articles (HLA 2022; doi: doi.org/10.1111/tan.14560).

HLA contributes to the outcomes of several infectious diseases and can cause variation in vaccine immune responses. Researchers worldwide have found significant associations among HLA alleles and severity of SARS-CoV-2 infection. The presence of certain HLA alleles may aggravate COVID-19 disease outcome while others have a protective effect. However, studies are limited by heterogeneity in study populations and methods, yielding inconsistent results.


Upon infection, SARS-CoV-2 peptides are presented to T-Cells by antigen presenting cells (APCs). Some peptides, which are carried by specific HLA antigens, may be better presented than others resulting in more robust immune responses. By identifying these “protective” HLA alleles, it may be possible to incorporate them into epitope-based vaccine design, allowing for an immunization response that mimics naturally mounted resistance.


Conversely, an exaggerated immune response is one of the indicators of poor prognosis and long-term effects of COVID-19. Because the immune response varies from person to person, it is crucial to curate a more thorough understanding of the involvement of HLA in the immune response to SARS-CoV-2 infection.


REFERENCES


1. Patel R and Terasaki PI. Significance of the positive crossmatch test in kidney transplantation. N Engl J Med 1969; 280:735-739.

2. Stenzel KH, Whitsell JC, Stubenbord WT, et al. Kidney transplantation: Improvement in patient and graft survival. Ann Surg 1974;180(1):29-34.

3. Hart A, Lentine KL, Smith JM, et al. OPTN/SRTR 2019 Annual Data Report: Kidney. Am J Transplant 2021; 21 Suppl 2: 21–137.

4. Colvin RB, Smith RN. Antibody-mediated organ-allograft rejection. Nat Rev Immunol 2005;5:807-17.

5. Bray RA, Lebeck LK, Gebel HM. The flow cytometric crossmatch. Dual-color analysis of T cell and B cell reactivities. Transplantation 1989;48:834-840.

6. Kerman RH, Susskind B, Buyse I, et al. Flow cytometry-detected IgG is not a contraindication to renal transplantation: IgM may be beneficial to outcome. Transplantation 1999;68:1855–1858.

7. Roll GR, Webber AB, Gae DH, et al. A virtual crossmatch-based strategy facilitates sharing of deceased donor kidneys for highly sensitized recipients. Transplantation 2020;104:1239-1245.

8. Lim WH, Chadban SJ, Clayton P, et al. Human leukocyte antigen mismatches associated with increased risk of rejection, graft failure, and death independent of initial immunosuppression in renal transplant recipients. Clinical Transplantation 2012;26:E428–E437.

9. Duquesnoy RJ. HLAMatchmaker: a molecularly based algorithm for histocompatibility determination. I. Description of the algorithm. Hum Immunol 2002;63:339-52.

10.Kosmoliaptsis V, Sharples LD, Chaudhry AN, et al. Predicting HLA class II alloantigen immunogenicity from the number and physiochemical properties of amino acid polymorphisms. Transplantation 2011; 91:183-90.

11.HLA Epitope Registry. http://www.epregistry.com.br/ (Accessed February 5, 2022).

12.Kumru Sahin G, Unterrainer C, and Süsal C. Critical evaluation of a possible role of HLA epitope matching in kidney transplantation. Transplant Rev (Orlando) 2020;34:100533.

13.Duquesnoy RJ, Howe J, and Takemoto S. HLAmatchmaker: a molecularly based algorithm for histocompatibility determination. IV. An alternative strategy to increase the number of compatible donors for highly sensitized patients. Transplantation 200327;75:889-97.

14.Lemieux W, Mohammadhassanzadeh H, Klement W, et al. Matchmaker, matchmaker make me a match: Opportunities and challenges in optimizing compatibility of HLA eplets in transplantation. Int J Immunogenet 2021;48:135-144.

15. Deb, P., Zannat, K. E., Talukder, S., Bhuiyan, A. H., Jilani, M., & Saif-Ur-Rahman, K. M. (2022). Association of HLA gene polymorphism with susceptibility, severity, and mortality of COVID-19: A systematic review. HLA, 10.1111/tan.14560. Advance online publication. https://doi.org/10.1111/tan.14560


25 Apr, 2022
Does your lab report threshold cycle (Ct) values with its SARS-CoV-2 results? Have you been asked to do so by customers/clients? Just because you can, does that mean you should? This is a question that I get A LOT from labs that I work with. Many customers want Ct values because they believe, erroneously, that they can make some sort of determination around infection status from those values. I don't know where they actually got this idea in the first place, but they will use the "well, the other lab will give us the Ct values" as a reason to (1) exclude your lab as a provider and/or (2) pressure you into providing the information. Here is some information you can use to overcome those objections. Firstly, different laboratories use different methods and these methods may have different Ct cutoffs. A Ct of 37 may be very different in an assay that runs for 45 cycles with a cutoff of 40 than in an assay that runs for 40 cycles with a cutoff of 38. Its difficult to say what the difference is unless the methods have been directly compared and correlated with clinical status. Additionally, I've found that many laboratories do not validate their cutoffs in house and simply use what has been published in the EUA. I believe this goes against CLIA regulations, but who am I to judge. Regardless, it has implications for what Ct values mean from various laboratories performing the same test. Ct values can be heavily technique dependent and may differ between laboratories using a lot of automation vs those that are more manual, even if they are using the same method. Moreover, there are numerous peer-reviewed publications addressing this issue (references below). But, to summarize them, individual sample Ct values should not be used as an absolute marker of length of time post-infection or to exclude infectivity where date of symptom onset is unavailable (Fox-Lewis et al). Notably, this also indicates that the Ct value has even less usefulness in asymptomatic patients. Ct values cannot differentiate between patients early in the infectious process and those who are recovering. Additionally, they cannot distinguish new infections from re-infections or simply prolonged shedding of virus. In the context of a known date of symptom onset, they can potentially be prognostic of disease severity, but again this is useless in asymptomatic patients. In my opinion, Ct values in the context of SARS-CoV-2 testing are almost useless, unless they are obtained under well controlled conditions and in the context of appropriate clinical information. So, just because you can…. You shouldn't. 1. Fox-Lewis A, Fox-Lewis S, Beaumont J, Drinković D, Harrower J, Howe K, Jackson C, Rahnama F, Shilton B, Qiao H, Smith KK, Morpeth SC, Taylor S, Blakiston M, Roberts S, McAuliffe G. SARS-CoV-2 viral load dynamics and real-time RT-PCR cycle threshold interpretation in symptomatic non-hospitalised individuals in New Zealand: a multicentre cross sectional observational study. Pathology. 2021 Jun;53(4):530-535. doi: 10.1016/j.pathol.2021.01.007. Epub 2021 Mar 20. PMID: 33838922; PMCID: PMC7980174. 2. Julian K, Shah N, Banjade R, Bhatt D. Utility of Ct values in differentiating COVID-19 reinfection versus prolonged viral shedding in an immunocompromised patient. BMJ Case Rep. 2021 Jul 27;14(7):e243692. doi: 10.1136/bcr-2021-243692. PMID: 34315745; PMCID: PMC8317077. 3. Shah S, Singhal T, Davar N, Thakkar P. No correlation between Ct values and severity of disease or mortality in patients with COVID 19 disease. Indian J Med Microbiol. 2021 Jan;39(1):116-117. doi: 10.1016/j.ijmmb.2020.10.021. Epub 2020 Nov 3. PMID: 33610241; PMCID: PMC7667391. 4. Sule WF, Oluwayelu DO. Real-time RT-PCR for COVID-19 diagnosis: challenges and prospects. Pan Afr Med J. 2020 Jul 21;35(Suppl 2):121. doi: 10.11604/pamj.supp.2020.35.24258. PMID: 33282076; PMCID: PMC7687508.
12 Apr, 2022
Most people think that a COVID test is a COVID test. They couldn't be more wrong. My mother lives on a small island in the Bahamas. They get A LOT of tourists from the US. Currently, in order for anyone to return to the US from the Bahamas, they need a negative COVID test within 48hr of arrival. Because of their limitations from a healthcare perspective - not a lot of facilities on a 3sq mi island - they are running a rapid antigen test. I have no idea which one, but for our purposes it doesn't matter. That test has flip-flopped on numerous individuals from one day to the next… its completely unreliable. I've always kind of jokingly said that I could flip a coin and be just as accurate… turns out I was actually right. In an article published on HealthLine in January the most recent study data is summarized ( How Accurate Are Rapid COVID Tests? What Research Shows (healthline.com) ). Turns out that most of the rapid antigen tests only detect a true positive about 50% of the time. So rapid tests are useless except for the purposes of "safety theater" -- to make one feel better that they've been tested. But… certainly PCR tests don’t have these issues. Well, yes and no… Not all COVID PCR tests are created equal. And even the ones that are, might not be comparable from laboratory to laboratory. Some labs use extraction-less methods, others don’t. Its known that methods that use extracted RNA are more sensitive than those that don’t. Some labs use automation resulting in more reproducible test results. Some labs use a cutoff of 40 Ct as stated by the manufacturer and some actually validate their tests in house (like they're supposed to) and learn that lower cutoffs are more accurate. Because labs use different reagents from different manufacturers, Ct values can't be compared either (that's another topic to be addressed later). Sample type also makes a difference; its been shown that saliva offers a much more sensitive and reliable result (gross to work with though!). I guess the bottom line is… if you want accurate and reliable COVID testing: 1) go with PCR and 2) pick a lab and stick with them.
28 Mar, 2022
Beyond the imminent pivots away from COVID, there is going to be a larger shift within healthcare that has been long anticipated. Healthcare as a larger field will be transitioning from a fee-for-service model towards an integrated care/value-based model. I believe that independent laboratories will need to be the primary drivers of sustainability within the diagnostic laboratory space as this shift occurs. For a long time, laboratories have operated by producing results and "throwing them over the wall" to clinicians for them to figure out, interpret, and draw their own conclusions. That has hurt the perceived value of the laboratory, which is capable of bringing so much more to the table. Laboratorians are highly trained experts in both the technical aspects of testing methodologies as well as the physiological implications of the results they produce. In that respect, they can bring so much more value to clinical practice. Some laboratories have already begun to adopt this kind of role. In molecular infectious disease testing, it’s no longer enough to simply provide positive/negative results… it’s just not feasible to remain competitive. Physicians are looking for more interpretation… if positive, what is the extent of the infection, what drugs might be useful in treating it, and, even, what dosage should be considered. This contribution to driving improved patient outcomes make the laboratory much more valuable to clinicians and it’s this kind of contribution that will drive sustainability. The question becomes, beyond infectious disease testing, how is this accomplished? Get started with Bratton LabWorx today!
14 Mar, 2022
Qualified, trained, laboratory testing staff are in frighteningly short supply. The COVID-19 pandemic driven demand for lab testing has highlighted that, even in main stream media. So, given supply and demand dynamics, keeping the staff you already have is going to be critical… recruiting additional staff is another topic for another time. I've seen many articles recently that advocate for automation as a critical factor in retaining staff. I can partially get behind that. No highly trained staff member wants to spend 8 (or more) hours manually pipetting or other "low level" tasks that are easily automated using liquid handlers or other types of instrumentation. They want, and should be encouraged, to put their focus on "higher level tasks" such as interpreting data, troubleshooting issues, and maintaining quality. I would argue that another reason to invest in automation is reducing variability. You are much more likely to get consistent results if as much of the testing process is automated as is possible. I am totally on board with automating. However, I don't think automation is the end all, be all of staff retention. People have an innate desire for advancement and recognition. Every single team member at every single lab that I've worked with in the past five years has told me the same thing: they want a growth and advancement pathway AND they want to be recognized for their contribution. Having a career ladder to climb is imperative to career satisfaction. No one wants to feel "stuck" and I think lab careers have been notoriously bad at providing ways for their team members to grow. I know providing an advancement ladder can be challenging in a lab environment, but we all have goals. Do your best to figure out how to help your team meet theirs both professionally and personally. Lastly, teams and team members want to be recognized for the contributions they make to company success. A lot of companies think a pizza party during lab week is "recognizing the lab". I think that's a cop out. Pay your people what they are worth and make sure you keep adjusting with the market. Otherwise, your team will move on to greener ($$$) pastures. Let's face it, compensation is WHY we all get up and go to work every day and, if it’s not right, no one will feel truly fulfilled by their job. So, if you really want to retain your qualified and highly trained clinical laboratory personnel, find interesting ways to help them reach their goals and pay them what they are worth.
28 Feb, 2022
I've seen two trends in the market: A pivot to offer "bread and butter" automated chemistry and immunoassay. A pivot to expanded molecular infectious disease (ID) testing. As for Option #1, I'm not sure why people think they can make money this way. It’s a known reality that hospital labs are money losers… if they can't pull it off, what are you doing differently. Beyond that, you will never be able to offer it faster, cheaper, better than the big commercial players. As far as I'm concerned, you're flushing your money buying those analyzers. There is no space to compete there and no money to go around even if you could. Option #2 is a bit more appealing. It seems a simple pivot as its technically similar to COVID testing and the output is actually in demand. In an era of antibiotic resistance, clinicians are more resistant themselves. They are far less likely to treat with broad-spectrum antibiotics without understanding what they are dealing with. For this reason, they want specific information on what "bugs" they are trying to kill. Along with that, they need guidance on which drugs to use and at what levels for how long. And, if that's not enough, they need the info yesterday… only an ultra-rapid turnaround time (TAT) will do. COVID labs will be adept at specificity and TAT, but may struggle with interpretive guidance and making reports valuable to the end user. This is where a lot of lab consulting firms are stepping in. They will help you set up and validate your ID panels. They MAY also help you with making your report utilitarian. However, those reports will likely be designed the way lab reports have been for decades… to throw data over the fence. That won't help you survive in this new competitive market. In order to survive post-COVID, small independent labs will have to figure out what they can do that no one else can. That may be a particular test/method based on the expertise and values of the owners and staff. OR, they will need to do what everyone else is doing, only better. Are you ready to get started? Contact us today! 
16 Feb, 2022
There are several issues facing the field of laboratory medicine right now:  The influx of laboratories and capacity specifically for COVID testing. The shortage of trained and qualified testing personnel. The larger shift within healthcare away from fee for service and towards an integrated care/value-based model. The question is how do smaller, independent labs, without the capital backing of a huge corporate enterprise or a hospital, survive the seismic shifts that are coming? I think each issue needs to be addressed individually. In this series of three articles, I will share my thoughts on each issue and how it might be addressed (there's never only one way to do anything, right?). What happens when COVID volume drops precipitously? You're fooling yourself if you think COVID testing is here to stay, at least at current throughout. While COVID itself may not be going anywhere anytime soon, it would surprise me if the testing levels didn't shift to resemble flu testing. There will likely come a time when COVID is accepted as another flu-like illness; as with the flu, each year a number of people will contract it and a number of people will die and THAT will be the "new normal". In line with that, laboratory testing will only be requested for symptomatic patients as opposed to the current level of asymptomatic surveillance. What, then, happens to all the small laboratories that opened their doors for the sole purpose of COVID testing? Did you know that only 3.4% of clinical laboratories are in hospitals? That number surprised me. While the majority of CLIA accredited laboratories are physician office labs (41.6%). A staggering 14.5% are commercial laboratories. As those data are from 2020, its difficult to say how many of those are a direct result of the COVID-19 pandemic driven need for increased capacity and ultra-rapid turnaround time. But I bet it’s a lot of them. So, how do they manage a precipitous drop in COVID testing? The obvious answer is that a lot of them will not survive. Those that are determined to do so will need to get creative!
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