Medical Laboratory Observer - March 2026

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Vol. 58, No. 2

Shadow AI in the lab

By Christina Wichmann

Editor in Chief

This month, we are sharing the results of our State of the Industry survey on Lab Data Analytics. Thank you to all who participated in this survey. For the article, Mike Hampton, chief commercial officer at Sapio Sciences shared, “The labs making progress are embedding AI tools into workflows and applying platform-level intelligence, so context, governance, and decision-making remain connected. Disconnected tools can drive shadow AI and fragment workflows.”

I’ve noticed that shadow AI is becoming more talked about this year. In the February 9th issue of our newsletter, LABline, we shared an interview on shadow AI with Alex Tyrrell, PhD, who is head of the Wolters Kluwer AI Center for Excellence.1 Dr. Tyrrell said that in 2025, they started to hear anecdotally about shadow AI becoming more prevalent. In Wolters Kluwer’s new survey with hospitals and health systems, 40% of respondents encountered an unauthorized AI tool in their organizations and nearly 20% have used them. In healthcare, shadow AI refers to unsanctioned use of artificial intelligence tools outside of an organization’s approved governance framework. Tools such as ChatGPT or transcription applications provide real value; but when used without organizational/IT oversight, cybersecurity experts warn they can introduce risk on a scale that most healthcare leaders and staff underestimate. These risks include maintaining privacy of patient data and accuracy of information provided by the tool.

Shadow AI uses

Labs can be a hotspot for shadow AI for the following reasons:

• M assive documentation burden: AI is incredible at documentation

• Regulatory language: AI translates and summarizes instantly

• SOP writing and revising: AI does this in seconds

• QC data analysis: AI can interpret trends

• Understaffing and burnout: AI feels like a secret assistant

• No formal AI policy: People assume “it’s probably fine”

Examples specific to the lab

Shadow AI in the lab looks like:

• A l aboratory professional using AI to write a QC corrective action

• A supervisor pasting a CAP deficiency into AI to draft the response

• A manager asking AI to create a validation plan for a new analyzer

• A n educator using AI to create competency questions

• A quality coordinator summarizing 30-page regulations

• A d irector using AI to write policies faster

Shadow AI risks

Shadow AI use doesn’t look like a potential attack; it looks like productivity. But when entering data into an external AI platform, it effectively leaves the organization’s control. As explained by Fortified Health Security, “Anyone using shadow AI can unknowingly exfiltrate sensitive information to third-party systems where it becomes part of external models. Shadow AI doesn’t just leak data; it donates it to someone else’s model. Once uploaded, it cannot be retrieved or deleted.”2 I welcome your comments and questions — please send them to me at cwichmann@mlo-online.com.

REFERENCES

1. Raths D. Navigating shadow AI: An interview with Wolters Kluwer’s Dr. Alex Tyrrell. MLO Online. February 9, 2026. Accessed February 10, 2026. https://mlo-online.com/55356115.

2. Fortifiedhealthsecurity.com. Accessed February 10, 2026. https://fortifiedhealthsecurity.com/ horizon-report/2026-Horizon-Report.pdf.

EDITOR IN CHIEF Christina Wichmann cwichmann@mlo-online.com

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Medical Laboratory Observer USPS Permit 60930, ISSN 0580-7247 print, ISSN 2771-6759 online is published 10 times annually (Jan, Mar, Apr, May, Jul, Jul-CLR, Aug, Sep, Oct, Nov) by Endeavor Business Media, LLC. 201 N Main St 5th Floor, Fort Atkinson, WI 53538. Periodicals postage paid at Fort Atkinson, WI, and additional mailing offices. POSTMASTER: Send address changes to Medical Laboratory Observer, PO Box 3257, Northbrook, IL 60065-3257. SUBSCRIPTIONS: Publisher reserves the right to reject non-qualified subscriptions. Subscription prices: U.S. $164.80 per year; Canada/Mexico $199.56 per year; All other countries $284.54 per year. All subscriptions are payable in U.S. funds. Send subscription inquiries to Medical Laboratory Observer, PO Box 3257, Northbrook, IL 60065-3257. Customer service can be reached toll-free at 877-382-9187 or at MLO@ omeda.com for magazine subscription assistance or questions Printed in the USA. Copyright 2026 Endeavor Business Media, LLC. All rights reserved. No part of this publication may be reproduced or

By Abdullah Kilic, MD, D(ABMM); Jacinda Abdul-Mutakabbir PharmD, MPH; Dusten T. Rose, PharmD, BCIDP

Ronald A. Blum, PhD

Raymond Lu

Connie Savor, MD, MBA

Outpatient diagnostics, antimicrobial stewardship, and health equity

Closing gaps in the fight against antimicrobial resistance

By Abdullah Kilic, MD, D(ABMM); Jacinda (JAM) Abdul-Mutakabbir PharmD, MPH; Dusten T. Rose, PharmD, BCIDP

The spread of antimicrobial-resistant (AMR) infections poses a global public health threat, with over 1 million resistant infections diagnosed annually.1 With more than 200 million antimicrobials prescribed in outpatient settings, including primary care clinics, urgent care centers, emergency departments (ED), and skilled nursing facilities, it is evident that these treatment settings facilitate the spread of AMR infections. 2,3 These are areas of unmet need as most antimicrobial stewardship (AMS) programs, designed to optimize unnecessary antimicrobial prescribing, have traditionally focused on addressing gaps in inpatient settings.4 Given the lack of oversight in outpatient AMS, it is unsurprising that there have been growing reports of inequities in the diagnosis and management of AMR infections, specifically among marginalized populations. 3,5,6

While identifying as part of a marginalized group is not a biological risk

factor for developing an AMR infection, marginalization is often accompanied by systems of oppression such as racism and classism.7 These systems can lead to inequities in the social determinants

Earning CEUs

of health (SDoH), such as education, socioeconomic status (SES), and access to healthcare.8,9 For example, individuals who identify as racially and ethnically marginalized (REM) are

See test online at https://ce.mlo-online.com/courses/ Outpatient-diagnostics-antimicrobial-stewardshipand-health equity

Passing scores of 70 percent or higher are eligible for 1 contact hour of P.A.C.E. credit.

lEarning obJECtiVES

Upon completion of this article,the reader will be able to:

Scan code to go directly to the CE test.

1. Discuss how gaps in outpatient antimicrobial stewardship (AMS) have contributed to antimicrobial resistance and health inequities.

2. List and describe the various tests used in rapid detection of microbial infections and the benefits of diagnostic advancements in the outpatient space.

3. Discuss potential gaps in the use of rapid diagnostics tests in outpatient settings.

4. Describe equitable strategies and solutions that can be integrated for successful AMS efforts in outpatient settings.

underrepresented among college graduates.10 This highlights potential barriers to health literacy and understanding of diagnosis severity and instructions for antimicrobial use.11 Additionally, areas of low SES are more vulnerable to shortages in healthcare providers and associated resources.12 Ultimately, limited access to care can lead to treatment delays or the absence of treatment for chronic and acute infectious illnesses. Integrating diagnostics and appropriate stewardship principles has revolutionized inpatient AMS programs.4 With the evolution of existing diagnostics and the emergence of innovative rapid diagnostics tests (RDTs), including rapid antigen tests (RADTs) and molecular diagnostics, there is an opportunity to optimize AMS in outpatient settings. Furthermore, point-of-care tests (POCTs), often defined as those RDTs not performed in a centralized laboratory and run with a Clinical Laboratory Improvement Amendments (CLIA) waiver or that are moderately complex, also have accelerated management capabilities the closer they get to the patient.13 Ultimately, if integrated and utilized appropriately, RDTs may lead to a reduction in antimicrobial usage and further inequitable impacts of resistant infections across marginalized groups. Here, we provide an overview of the Centers for Disease Control and Prevention (CDC) guidance on outpatient AMS programs and insight into the microbiology laboratory’s role in integrating RDTs into AMS procedures. We also provide insight into the use of RDTs in outpatient settings. Finally, we conclude with strategies for integrating these diagnostic modalities into outpatient AMS programs to narrow AMR-related health equity gaps by reducing inappropriate antimicrobial prescribing and use.

Overview of the CDC outpatient antimicrobial stewardship framework

To address the estimated 30–50% of unnecessary prescriptions in the outpatient community, the CDC published ambulatory AMS guidance in 2016 with the following core elements: commitment, action for policy and practice, tracking and reporting, and education and expertise.14 Despite The Joint Commission endorsing outpatient stewardship initiatives the following year, widespread adoption has been slow due to barriers such as variable governance and data structures, diverse models of care, lack of administrative commitment, and

disparities in resource allocations.15 A survey of Vizient member hospitals, representing 20% of the country’s ambulatory market, reported that only 7% had a fully functioning ambulatory AMS program compared to 88% of inpatient settings.16 Analogous to inpatient clinical laboratories, RDTs (including RADTs and molecular diagnostic tests) can augment AMS efforts in the outpatient setting

RADTs

advantages• high specificity

• low cost

• rapid tat (5-24m)

• Easy to perform

• minimal equipment required

disadvantages• low sensitivity

• Variable sensitivity**

• Culture follow-up for gaS in children >3 years of age

85.6% and 95.4%, respectively, compared to throat culture.18 While high specificity may support actionable results when positive, the moderate sensitivity raises questions about back-up throat cultures in children aged three and older, negating the quick turnaround time, or whether the cause of pharyngitis is secondary to a viral pathogen or non-infectious etiology.

Molecular RDTs

• high sensitivity and specificity

• rapid tat (15-90m)

• multiplex capability (detects multiple pathogens simultaneously, often >15

• demonstrated amS and clinical benefits in outpatient setting

• Expanding specimen types (npS, tS, anS) for easier collection

• detects low organism low (early infection)

• reduces need for confirmatory culture in many cases

• inability to rule out non-viable organism, colonization

• higher cost

• inability to rule out colonization (gaS radt)

• Single pathogen detection

• limited specimen types per test

• False negatives can occur in early infection

• requires specialized equipment and trained personnel

• may detect clinically irrelevant organisms (overdiagnosis risk)

• limited availability in some settings

** reduced (self-collection, children, low viral load); increased (symptomatic, early in disease state). amS: antimicrobial stewardship; anS: anterior nares swab; gaS: group a Streptococcus; npS: nasopharyngeal swab; radt: rapid antigen detection test; tat: turnaround time; tS: throat swab

Table 1. Comparison of radts and molecular rdts.

and provide clinicians with timely and actionable information by differentiating commonly encountered pathogens implicated in the greatest driver of unnecessary outpatient antibiotic prescriptions: upper respiratory tract infections (URIs).

Diagnostic advancements

Rapid antigen diagnostic tests (RADTs)

RADTs are commonly used in pointof-care settings as they provide results within 5-30 minutes for frequent URI pathogens such as group A Streptococcus (GAS), influenza viruses, and SARSCoV-2. These tests are inexpensive lateral flow immunoassays without specific storage constraints that produce a visible signal from migrating antigenantibody complexes by capillarity.17 More information on RADTs is available in Table 1

Many guidelines recommend using RADTs for GAS, which demonstrate pooled sensitivities and specificities of

Similar to RDTs for bacterial pathogens, viral RADTs are also not without limitations. SARS-CoV-2 demonstrates pooled sensitivities and specificities of 71–82% and 99%, respectively; however, performance is dependent on several factors.19 Rapid influenza diagnostic tests (RIDTs) also report variable performance with sensitivities and specificities of 61–69% and 98–99%, respectively; however, real-world practice often records sensitivities as low as 25–50%.20 These poor sensitivities reduce diagnostic certainty, thereby limiting antibiotic prescriptive confidence resulting in antimicrobials “just in case” for negative tests and/or additional confirmatory PCR testing when clinical suspicion is high.

Molecular diagnostic tests

To overcome some limitations of RADTs, molecular RDTs for GAS and respiratory viruses use either thermocycling or isothermal amplification, with PCR

being the most common thermocycling method. Newer RDTs employ isothermal techniques such as Nicking Enzyme Amplification Reaction, LoopMediated Isothermal Amplification, and Helicase-Dependent Amplification.18 Pooled sensitivities and specificities are significantly higher at 97.5% and 95.1%, respectively, for GAS.21,22 Sensitivities for viral analytes may be as high as 100% depending on the analyte and test.22 Certain molecular RDTs can simultaneously detect viral and bacterial targets from nasopharyngeal, anterior nares, and throat swabs, providing integrated sample-to-answer systems that identify multiple pathogens within 15–90 minutes.23

Molecular tests in pointof-care settings

Recent data suggest promising outcomes, particularly among marginalized patients, when newer POCT diagnostics are leveraged in the outpatient space. Meltzer and colleagues compared a multiplex respiratory POCT with a ~15minute turnaround time to an observational control for the management of URIs in the ED.24 Notably, REM patients were less likely to receive antibiotics with confirmed viral infections (6.5% versus 20.2%; p=0.009) and median length of ED stay was shortened (4.3 hours versus 6.5hours; p<0.001). Moreover, providers noted increased diagnostic confidence, and patients reported higher satisfaction with result timeliness. Utilizing the same POCT, improved patient outcomes and reduced prescriptions were reproducible in additional outpatient cohorts.25,26 Based on these recent studies, molecular RDTs offer significant opportunities for reducing unnecessary antibiotic use in the outpatient arena to combat AMR; however, notable barriers to increase community access and AMS integration need to be considered.

Current and anticipated gaps in the use of RDTs in outpatient settings

The COVID-19 pandemic exposed barriers that can hinder the equitable use of RDTs to enhance outpatient AMS initiatives. By using deprivation indices like the social vulnerability index (SVI) and area deprivation index (ADI), which assess the effects of social, material, and economic disadvantages on health outcomes, researchers have obtained intriguing findings.27-29 Several studies have shown disparities in the availability of RDTs, with high social vulnerability

areas less likely to have access to testto-treat locations; a situation likely to worsen due to shifting government funding priorities.30,31

The shortage of test-to-treat sites is a significant concern because socially vulnerable areas—often inhabited by marginalized groups—are expected to face increased burdens from vaccine-preventable illnesses in upcoming viral seasons. This is due to changes in the dissemination of reliable vaccine information and evolving vaccine recommendations, which could influence the future accessibility and affordability of immunizations. These health systems, frequently categorized as safety-net institutions, tend to be understaffed and underfunded.32 Such errors could lead to delayed or missed treatment of viral infections, potentially fostering the development of infections caused by AMR bacteria.33 Even more concerning, these limitations in diagnosis and management might erode trust in future clinician diagnoses and the perceived effectiveness of antimicrobial therapy prescribed in outpatient settings.33

Other operational concerns regarding the deployment of RDTs in outpatient settings were also raised during the pandemic.34 These concerns include difficulty in complying with the manufacturers’ specifications and storage requirements, staff training and competency validation, and regulatory compliance with laboratory accreditation and regulatory standards. These issues are likely to be more prevalent and harder to address in outpatient settings in vulnerable areas, where healthcare shortages and turnover are most pronounced.

Financial reimbursement for RDTs is also a point of contention, as batch testing is often cheaper.34 There may be variability in the tests for which insurance programs are willing to provide coverage, which may affect the reliability of the results and the treatment prescribed based on the test output.

Strategies, solutions, and how to augment current successes in outpatient antimicrobial stewardship efforts

Integrating RDTs into outpatient AMS programs can play a major role in addressing inequities in AMR infections.

Outpatient providers believe published local resistance patterns would incentivize ambulatory stewardship implementation

Nonetheless, this effort will not be without challenges. Therefore, in this section we provide evidence-based strategies for clinicians to consider as guidance for the equitable inclusion of RDTs in outpatient stewardship programs.

Notable resource-limited interventions include antibiotic commitment posters or screensavers, delayed prescribing prescription pads, and signed antibiotic commitment letters by office and clinic staff.35,36 With increased sensitivity of molecular RDTs compared to

RADTs, one increasingly utilized strategy is pairing clinical prediction rules with patient assessment. One group embedded the Centor score into the electronic health record with pharyngitis testing to improve pre-test probability.37

While information technology plays a key role in AMS success, not every outpatient setting may have this resource. Risk assessment scoring tools could be available in posted guidance documents for pharyngitis, which would align with the recently updated Infectious Diseases Society of America (IDSA) GAS Pharyngitis guideline.38 It is outside the scope of this article to list all supplemental strategies for outpatient stewardship programs, though additional resources can be found on the CDC’s Outpatient Stewardship and the Agency for Healthcare Research and Quality (AHRQ) websites.

Another notable barrier to successful instrumentation deployment is lack of awareness of availability of testing and the valuable information and outcomes that can be harnessed from specific platforms for key stakeholders (e.g., providers, patients and care givers, insurers). Outpatient providers believe published local resistance patterns would incentivize ambulatory stewardship implementation.39 Local epidemiology could come from state health departments, regional clinical microbiology laboratories, or de-identified reports directly from RDTs platforms. One such surveillance system is BioFire Syndromic Trends by bioMérieux who publishes respiratory pathogen and gastrointestinal trends publicly. This data provides near real-time information on circulating pathogens to guide management decisions. 40 Compared to the CDC’s Respiratory Virus Hospitalization Surveillance Network (RESP-NET) detailing national trends for influenza, COVID-19, and RSV, Syndromic Trends includes results with additional viruses (e.g., adenovirus, seasonal coronaviruses, entero/rhino virus, parainfluenza, human metapneumovirus) from a comprehensive multiplex panel directly from U.S. clinical laboratories using this technology.

Patients and caregivers are also major determinants of antibiotic prescriptions in the community. While this is multifactorial, one potential driver is that the public is largely unaware of the risks associated with antibiotic use, especially those with marginalized identities. 41 Nearly 4 in 5 providers agree that stewardship efforts would be

ineffective unless paired with efforts to educate patients on resistance and the importance of de-prescribing antibiotics for viruses.39

In addition to clinic stewardship commitment pledges, providers can explain the value of broader multiplex panels that help detect yearly circulating respiratory viruses like rhinovirus and enterovirus. By providing targets beyond the traditional quadraplex (e.g., Influenza A/B, SARS-CoV-2, RSV), 44% more detections were identified in one study with a multiplex system, which allows for more comprehensive management and de-prescribing of antibiotics for viral infections.42 Lastly, external market access stakeholders (e.g., government and regulatory agencies, payors) must be informed of the clinical value and patient benefit of IVD technology in the outpatient setting for updating coverage policies associated with test utilization.43

For addressing RDT accessibility concerns, the Prioritizing Equity in Antimicrobial Stewardship Efforts (EASE) framework, aligned with Joint Commission and CMS Health Equity principles may represent an effective strategy. 44 The framework, which includes five focus areas, states that reviewing institutional data should be the starting point when designing an intervention to create change. Following this guidance, investigators could identify an outpatient setting and a disease area to review data for. With the growing reports of S. pneumoniae inequities in the diagnosis of AMR S. pneumoniae infections, this may be an ideal starting point for clinicians and researchers.6 Following the guidance provided in the EASE framework, researchers could begin with extracting data on S. pneumoniae infections treated in their affiliated outpatient settings. The investigators could further disaggregate the data by levels of deprivation (using the ADI or SVI), race/ethnicity, or insurance status to see whether differences in AMR S. pneumoniae infections exist. Investigators have used non-susceptibility to at least one of the 27 antimicrobials clinically used to treat pneumococcal infections as specified in the National Healthcare Safety Network (NHSN) Antimicrobial Use and Resistance (AUR) reporting module as an indicator for S. pneumoniae resistance, which other researchers can consider as their definition for an AMR

S. pneumoniae infection.45 Based on these findings, investigators and clinicians can design an intervention to address uncovered inequities, with accessibility as a focus. The intervention should consider operational barriers, including staff workload and competency. Costs and insurance coverage should also be evaluated when deciding who should be tested, when tests should be used, and which RDTs should be prioritized for use. With these considerations, a possible intervention could involve deploying RDTs only for individuals at higher risk for AMR pneumococcal infections. This approach could ensure that patients at increased risk receive the right antimicrobials promptly, thereby reducing the development and propagation of resistant infections among high-risk groups.

Conclusion

Scan code to go directly to the CE test.

The evolution of diagnostics for infectious diseases has increased accuracy, reduced turnaround times, and broadened the spectra of detections with one test. RDTs boost diagnostic certainty, translating into improved antimicrobial use and clinical outcomes in the inpatient and outpatient settings alike. Health disparities present predictable barriers to ensuring access to RDTs in marginalized populations, though these challenges can be met. The spread of AMR is not constrained by geography or socioeconomic status. Availability of outpatient RDTs for all communities ultimately align with the CDC’s Ambulatory Stewardship guidance, strengthening antibiotic prescribing practices and protecting population health at large—reflecting the principle: “Whatever affects one directly, affects all indirectly.”

REFERENCES

1. GBD 2021 Antimicrobial Resistance Collaborators. Global burden of bacterial antimicrobial resistance 1990-2021: A systematic analysis with forecasts to 2050. Lancet. 2024;404(10459):1199-1226. doi:10.1016/S0140-6736(24)01867-1.

2. Outpatient Antibiotic Prescriptions - United States, 2022. CDC. November 13, 2023. Accessed January 22, 2026. https://archive. cdc.gov/#/details?url=https://www.cdc.gov/ antibiotic-use/data/report-2022.html.

3. Thure KA, Mutamba G, Wren CM, Evans CD. Assessing disparities in inappropriate outpatient antibiotic prescriptions in Tennessee. Antibiotics (Basel). 2025;14(6):569. doi:10.3390/antibiotics14060569.

4. Claeys KC, Johnson MD. Leveraging

Continuing Edu C ation :: a ntimi C robial St E ward S hip

diagnostic stewardship within antimicrobial stewardship programmes. Drugs Context. 2023;12:2022-9-5. doi:10.7573/dic.2022-9-5.

5. McLeod CC, Al-Fayiz H, Rodriguez S, Tan KK, Abdul-Mutakabbir JC. Examining racial and social vulnerability disparities in the outpatient treatment of uncomplicated cystitis at a Southern California Academic Hospital. Antimicrob Steward Healthc Epidemiol. 2023;3(1):e214. doi:10.1017/ash.2023.469.

6. Mohanty S, Ye G, Sheets C, et al. Association between social vulnerability and streptococcus pneumoniae antimicrobial resistance in US adults. Clin Infect Dis. 2024;79(2):305-311. doi:10.1093/cid/ciae138.

7. Abdul-Mutakabbir JC, Abdul-Mutakabbir R. Syndemics of antimicrobial resistance: Non-communicable diseases, social deprivation, and the rise of multidrug-resistant infections. Infect Dis Ther 2025;14(8):1561-1575. doi:10.1007/s40121-025-01188-1.

8. Brown TH, Homan P. The future of social determinants of health: Looking upstream to structural drivers. Milbank Q. 2023;101(S1):36-60. doi:10.1111/1468-0009.12641.

9. Marcelin JR, Hicks LA, Evans CD, et al. Advancing health equity through action in antimicrobial stewardship and healthcare epidemiology. Infect Control Hosp Epidemiol. 2024;45(4):412-419. doi:10.1017/ ice.2024.7.

10. Libassi CJ. The neglected college race Gap: Racial disparities among college completers. CAP. May 23, 2018. Accessed January 22, 2026. https://www.americanprogress.org/article/neglected-college-race-gapracial-disparities-among-college-completers/.

11. Muvuka B, Combs RM, Ayangeakaa SD, et al. Health literacy in African-American communities: Barriers and strategies. Health Lit Res Pract. 2020;4(3):e138-e143. doi:10.3928/24748307-20200617-01.

12. Jones CH, Dolsten M. Healthcare on the brink: Navigating the challenges of an aging society in the United States. NPJ Aging 2024;10(1):22. doi:10.1038/s41514-024-00148-2.

13. Lisby JG, Schneider UV. Point of care testing for infectious disease: Ownership and quality. J Antimicrob Chemother. 2021;76(Suppl 3):iii28-iii32. doi:10.1093/jac/dkab247.

14. Sanchez GV, Fleming-Dutra KE, Roberts RM, Hicks LA. Core elements of outpatient antibiotic stewardship. MMWR Recomm Rep. 2016;65(6):1-12. doi:10.15585/mmwr.rr6506a1.

15. Frost HM, Hersh AL, Hyun DY. Next steps in ambulatory stewardship. Infect Dis Clin North Am. 2023;37(4):749-767. doi:10.1016/j. idc.2023.07.004.

16. Eudy JL, Pallotta AM, Neuner EA, et al. Antimicrobial stewardship practice in the ambulatory setting from a national cohort. Open Forum Infect Dis. 2020;7(11):ofaa513. doi:10.1093/ofid/ofaa513.

17. Budd J MB, Weckman NE, et al. Lateral flow test engineering and lessons learned from COVID-19. Nat Rev Bioeng. 2023;1:13-31. doi:https:// doi.org/10.1038/s44222-022-00007-3.

18. Cohen JF, Tanz RR, Shulman ST. Group A streptococcus pharyngitis in children: New perspectives on rapid diagnostic testing and antimicrobial stewardship. J Pediatric Infect Dis Soc. 2024;13(4):250-256. doi:10.1093/jpids/piae022.

19. Bachelet VC, Lizana FJ, Andrades CO, et al. Estimates for diagnostic accuracy of rapid antigen tests for SARS-CoV-2 in systematic reviews are consistently similar despite poor methodological rigor: a methodological overview. J Clin Epidemiol. 2024;176:111547. doi:10.1016/j. jclinepi.2024.111547.

20. Nairz M, Weiss G. How to identify respiratory pathogens in primary health care - a review on the benefits, prospects and pitfalls in using point of care tests. Infection. 2025;53(6):2321-2340. doi:10.1007/ s15010-025-02600-1.

21. Dubois C, Smeesters PR, Refes Y, et al. Diagnostic accuracy of rapid nucleic acid tests for group A streptococcal pharyngitis: systematic review and meta-analysis. Clin Microbiol Infect. 2021;27(12):1736-1745. doi: 10.1016/j.cmi.2021.04.021.

22. Matic N, Lawson T, Ritchie G, Lowe CF, Romney MG. Testing the limits of multiplex respiratory virus assays for SARS-CoV-2 at high cycle threshold values: Comparative performance of cobas 6800/8800 SARS-CoV-2 & Influenza A/B, Xpert Xpress SARS-CoV-2/Flu/RSV, and cobas Liat SARS-CoV-2 & Influenza A/B. J Assoc Med Microbiol Infect Dis Can. 2024;8(4):328-335. doi:10.3138/jammi-2022-0039.

23. Information on rapid molecular assays, RT-PCR, and other molecular assays for diagnosis of influenza virus infection. CDC. Oct 21, 2019. Accessed January 23, 2026. https://www.cdc.gov/flu/hcp/ testing-methods/molecular-assays.html.

24. Meltzer AC, Payette C, Heidish R, et al. Point-of-care respiratory diagnosis and antibiotic utilization in the emergency department: A prospective evaluation of multiplex PCR. Acad Emerg Med. 2026;33(1):e70156. doi: 10.1111/acem.70156.

25. Bigaud B, Marjanovic N, Deroche L, et al. Impact of multiplex PCR point-of-care platform implementation for respiratory pathogen detection in an emergency department with high daily patient volume. J Clin Microbiol. 2026;64(1):e0131325. doi:10.1128/jcm.01313-25.

26. Arnold CG, Furtado T, Bang H, Harnett G, May LS. Combining an antibiotic stewardship program with a 15-pathogen viral panel to reduce inappropriate antibiotic prescribing. Microbiol Spectr. 2026;14(1):e0219525. doi:10.1128/spectrum.02195-25.

27. Boehmer TK, Koumans EH, Skillen EL, et al. Racial and Ethnic Disparities in Outpatient Treatment of COVID-19 - United States, January-July 2022. MMWR Morb Mortal Wkly Rep. 2022;71(43):1359-1365. doi:10.15585/mmwr.mm7143a2.

28. Mullachery PH, Li R, Melly S, et al. Inequities in spatial accessibility to COVID-19 testing in 30 large US cities. Soc Sci Med. 2022;310:115307. doi:10.1016/j.socscimed.2022.115307.

29. Meyer AND, Giardina TD, Khawaja L, Singh H. Patient and clinician experiences of uncertainty in the diagnostic process: Current understanding and future directions. Patient Educ Couns. 2021;104(11):2606-2615. doi:10.1016/j.pec.2021.07.028.

30. Hohenstein L, Maloney M, Banach DB. Paxlovid utilization and social vulnerability: trends in Connecticut from 2022 to 2023. Antimicrob Steward Healthc Epidemiol. 2025;5(1):e275. doi:10.1017/ash.2025.10193.

31. Smith ER, Oakley EM. Geospatial Disparities in Federal COVID-19 Test-to-Treat Program. Am J Prev Med. 2023;64(5):761-764. doi:10.1016/j.amepre.2023.01.022.

32. McHugh MD, Brooks Carthon M, Sloane DM, et al. Impact of nurse staffing mandates on safety-net hospitals: Lessons from California. Milbank Q. 2012;90(1):160-86. doi:10.1111/j.1468-0009.2011.00658.x.

33. McDonald KM, Gleason KT, Grob RN, et al. Exploring sociodemographic disparities in diagnostic problems and mistakes in the quest for diagnostic equity: Insights from a national survey of patient experiences. Front Public Health. 2025;13:1444005. doi:10.3389/ fpubh.2025.1444005.

34. Oyefolu O, Gronvall GK. Exploring challenges and policy considerations in point-of-care testing for hospital preparedness ahead of infectious disease emergencies: A qualitative study. Infect Dis Health 2025;30(2):111-118. doi:10.1016/j.idh.2024.10.001.

35. Meeker D, Knight TK, Friedberg MW, et al. Nudging guideline-concordant antibiotic prescribing: a randomized clinical trial. JAMA Intern Med. 2014;174(3):425-31. doi:10.1001/ jamainternmed.2013.14191.

36. Core elements of outpatient antibiotic stewardship. CDC. August 21, 2025. Accessed January 23, 2026. https://www.cdc.gov/antibiotic-use/ hcp/core-elements/outpatient-antibiotic-stewardship.html.

37. Aalbers J, O’Brien KK, Chan WS, et al. Predicting streptococcal pharyngitis in adults in primary care: a systematic review of the diagnostic accuracy of symptoms and signs and validation of the Centor score. BMC Med. 2011;9:67. doi:10.1186/1741-7015-9-67.

38. Linder JA, Watson ME, Wessels MR, et al. 2025 Clinical Practice Guideline Update by the Infectious Diseases Society of America on Group A Streptococcal (GAS) Pharyngitis: Risk assessment using clinical scoring systems in children and adults. Clin Infect Dis. 2025:ciaf668. doi:10.1093/cid/ciaf668.

39. Zetts RM, Garcia AM, Doctor JN, et al. Primary care physicians’ attitudes and perceptions towards antibiotic resistance and antibiotic stewardship: A national survey. Open Forum Infect Dis. 2020;7(7):ofaa244. doi:10.1093/ofid/ofaa244.

40. Meyers L, Ginocchio CC, Faucett AN, et al. Automated real-time collection of pathogen-specific diagnostic data: Syndromic infectious disease epidemiology. JMIR Public Health Surveill. 2018;4(3):e59. doi:10.2196/publichealth.9876.

41. Szymczak JE, Klieger SB, Miller M, Fiks AG, Gerber JS. What parents think about the risks and benefits of antibiotics for their child’s acute respiratory tract infection. J Pediatric Infect Dis Soc. 2018;7(4):303-309. doi:10.1093/jpids/pix073.

42. Banerjee D, Sasidharan A, Gummersheimer S, et al. Head-to-head comparison of the performance of BIOFIRE(R) SPOTFIRE(R) Respiratory/Sore Throat Panel, Cepheid Xpert(R) Xpress SARS-CoV-2/Flu/ RSV and Cobas(R) SARS-CoV-2 & Influenza A/B assay for detection of respiratory viruses. J Clin Virol. 2025;182:105902. doi:10.1016/j. jcv.2025.105902.

43. Hill BK, Prinzi AM, Kane JR, Corby AK, Powe BD. Navigating and advancing market access for in vitro diagnostics: Understanding the roles of key stakeholders and policy. Open Forum Infect Dis. 2025;12(Suppl 2):S1404-S1412. doi:10.1093/ofid/ofaf444.

44. Abdul-Mutakabbir JC, Tan KK, Johnson CL, et al. Prioritizing equity in antimicrobial stewardship efforts (EASE): A framework for

infectious diseases clinicians. Antimicrob Steward Healthc Epidemiol. 2024;4(1):e74. doi:10.1017/ash.2024.69.

45. Rozenbaum MH, Tort MJ, Chapman R, et al. Conceptual methodological framework for incorporating antimicrobial resistance considerations in economic models for pneumococcal conjugate vaccines. Infect Dis Ther. 2025;14(12):2853-2868. doi:10.1007/s40121-025-01243-x.

Abdullah Kilic, MD, D(ABMM) is an a s sistant p r ofessor in Clinical m icrobiology at Wake Forest School of Medicine he is board-certified by the a merican b oard of medical m icrobiology and has extensive experience in antimicrobial resistance, rapid diagnostics, and molecular microbiology. his research focuses on improving diagnostic accuracy and antimicrobial stewardship through advanced laboratory methods.

Jacinda (JAM) Abdul-Mutakabbir PharmD, MPH is an a ssociate professor of Clinical pharmacy at UC San Diego whose research focuses on antimicrobial resistance, stewardship, and health disparities in infectious diseases. She has published more than 70 peer-reviewed articles and has received numerous national and international honors, including awards from idS a , aC Cp, Sidp, E SC mid, and the u S. public health Service. She currently serves as an editor for Clinical Microbiology Reviews and is an active member of aC Cp, a Sm, idS a , and ShE a

Dusten T. Rose, PharmD, BCIDP is a medical Science l iaison in u S. medical a f fairs at bioMérieux he is a board-certified infectious diseases pharmacist with nearly 15 years of inpatient clinical experience. his interests include antimicrobial stewardship, clinical impact of emerging diagnostics, and antimicrobial resistance.

From glass to gigapixels A GI pathology lab’s journey into digital pathology

By Ronald A. Blum, PhD

When I joined OmniPathology, an independent gastrointestinal (GI)–focused pathology laboratory, a little over a year ago as Vice President of Science & Technology, one of the first initiatives I was eager to explore was the adoption of digital pathology. Like many independent laboratories, we had been watching the space carefully for years. Digital pathology had long promised efficiency and scalability, but until recently, the technology, regulatory environment, and cost structure made widespread adoption challenging for a traditional, high-volume anatomic pathology practice.

Over the past few years, however, digital pathology has advanced dramatically. Improvements in whole-slide imaging, faster scanners, more sophisticated image management systems (IMS), and most notably, the rapid maturation

of artificial intelligence (AI) tools have fundamentally changed what is possible. AI-enabled digital pathology platforms can now automatically identify regions of interest, perform measurements and cell counts, flag potential diagnostic features, and streamline case navigation in ways that were unimaginable even a decade ago. These capabilities have transformed digital pathology from a promising concept into a practical, powerful, operational tool.

Why digital pathology— and why now

OmniPathology is built on an exceptional foundation: a team of seasoned, world-class, GI fellowship–trained pathologists who collectively have interpreted more than one million biopsies. Over the years, the laboratory developed a highly effective workflow

with strong communication between histology, laboratory operations, and pathologists. The rhythm of the lab worked, and it worked well.

At the same time, we recognized that our existing model, like that of many traditional pathology practices, had inherent limitations. Scaling volume required proportional increases in physical space, microscopes, and on-site staffing. Expanding into new subspecialties or service lines could take months or years. Geographic constraints limited how and where pathologists could contribute.

To take advantage of new opportunities, both within GI pathology and in adjacent or emerging diagnostic services, we needed a workflow that was more scalable, more flexible, and less constrained by the physical realities of glass slides and microscopes. Digital pathology offered a path forward.

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I was tasked with leading the evaluation process, with the goal of selecting a digital pathology system within a few months. While I had experience with digital tools and laboratory informatics, I had never evaluated or implemented an end-to-end digital pathology ecosystem. My first step was to seek advice from people who had already traveled this road.

Learning from experts

I reached out to two trusted colleagues with deep, real-world expertise: Dr. Eric Glassy, a true pioneer in digital pathology, and Lisa-Jean Clifford, a seasoned leader in high-technology healthcare information solutions. Their guidance was invaluable, helping me understand not only the technology itself, but also the operational, cultural, and strategic implications of going digital.

They emphasized several key principles that shaped our approach:

• Be explicit about your goals and expectations—“digital pathology” means very different things to different laboratories.

• Develop a clear list of critical evaluation criteria and prioritize what matters most to your organization.

• Remember that digital pathology is an ecosystem, not a single product. Scanners, image management systems, viewers, storage, LIS integration, and monitors must all work together.

• Evaluate each component independently and as part of the whole system.

• Bring vendors on site for in-laboratory demonstrations using real cases.

• I nvolve all stakeholders early—histology, IT, pathologists, and operations staff understand workflow challenges better than anyone.

• Ensure compatibility and ease of integration among the digital pathology platform, image management system (IMS), laboratory information system (LIS), and display hardware.

Armed with this framework, we began a structured, methodical evaluation.

Understanding the digital pathology ecosystem

At its core, any digital pathology solution consists of three primary components:

• D igital pathology scanners that convert glass slides into high-resolution whole-slide images.

• A n image management system (IMS) that stores, organizes, displays, and analyzes those images while interfacing with the laboratory information system (LIS).

• D iagnostic-grade monitors that allow pathologists to view digital slides with confidence.

Within this landscape are both FDA-cleared and non–FDA-cleared platforms. FDA-cleared systems provide regulatory reassurance but are often more “locked down,” making customization and rapid innovation more difficult. In contrast, more flexible platforms may allow faster integration of new AI tools and workflow optimizations but require careful validation and governance.

Evaluating digital pathology scanners

Modern scanners have improved significantly in image quality, resolution, and reliability. As a result, throughput and operational resilience became major differentiators in our evaluation. Key criteria included the following:

• Scanning speed, image quality, and resolution

• Slide capacity and degree of automation

• Ease and reproducibility of slide loading

• Reliability and redundancy in case of downtime

• Availability and responsiveness of service support

• Service and maintenance costs

• M anufacturing location and supply chain considerations

• P hysical footprint in the lab

• P rice and vendor references

Throughput was particularly important. To meet our goal of having cases ready for pathologist review each morning, scanning could not become a bottleneck.

The central role of the image management system

If scanners are the engine of digital pathology, the IMS is the nervous system. It is the software environment in which pathologists review, analyze, and sign out cases, often with AI-assisted tools layered into the workflow.

We paid close attention to:

• Compatibility with multiple scanners

• Ease of integration with our existing LIS

• Robust and high-speed network infrastructure, storage architecture, bandwidth, and scalability

• Short- and long-term image storage options and pricing

• Availability and maturity of AI tools

• F lexibility to integrate third-party or internally developed AI algorithms

• Customization of the pathologist user experience

• Vendor location, support model, and long-term roadmap

• Cost and references

Whole-slide images are large, often around 1 GB per slide, making storage strategy a nontrivial consideration. Most vendors offer tiered storage models, balancing cost against retrieval speed. Selecting the right approach requires a clear understanding of clinical needs, client expectations, and regulatory requirements.

Trial testing in the real world

Rather than relying solely on vendor demonstrations, we arranged week-long, in-lab trials for each scanner under consideration. Instruments were installed sequentially, allowing our histology staff and pathologists to work with each system using real cases and real workflows.

This hands-on experience proved invaluable. Technologists evaluated slide loading, scanning reliability, and ease of use. Pathologists compared digital images directly with glass slides, assessing image fidelity and diagnostic confidence. Reviewing platforms back-to-back helped clarify differences that might otherwise have been subtle.

Similarly, IMS vendors were invited to present their platforms in depth, focusing on workflow integration, customization, AI capabilities, and long-term flexibility. These sessions sparked productive discussions about future use cases that extended well beyond our initial implementation.

Validation: Building diagnostic confidence

Validation is a critical step in implementing digital pathology for primary diagnosis. The College of American Pathologists (CAP) provides clear guidelines for validating whole-slide imaging systems. In essence, selected cases are reviewed on glass and then re-reviewed digitally by the same pathologist after a washout period of at least two continued on page 20

Erica Chandler Sysmex Clinical Applications Specialist

Erica spends much of her free time at the Women’s and Children’s homeless shelter in Nashville, serving meals and offering encouragement to those who are homeless, hurting, and hungry. For her, it’s more than volunteering — it’s about reminding people they matter. And when it comes to lab techs, her message is the same: “The work you do is valuable, you are important and I’m here to help.”

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In cardiac marker testing, choosing the right controls is critical

By Raymond Lu

If there is one scenario common to all emergency rooms, it is probably the patient presenting with some combination of chest pain and shortness of breath. That is why clinical laboratories have to be prepared to run cardiac biomarker tests day and night. And since cardiac troponin tests are counted on to help distinguish between life-threatening heart attacks and relatively harmless panic attacks, they also have to be completely reliable.

With widely available cardiac troponin tests, that reliability may seem like a given. It isn’t. In fact, there are a number of challenges for assuring quality in the cardiac marker testing process. Perhaps most important is there is no established reference standard for troponin quality controls, making it difficult for laboratory professionals to know that they are using the best testing components. It is also tough to compare test results across laboratories — even labs in the same healthcare system — because testing

ranges can vary by manufacturer and platform. Another factor is that normal and abnormal cardiac troponin levels are different in males and females, in older and younger individuals, and in the same people at different times of day. This limits the leeway that can be permitted in test results and increases the pressure to ensure exact answers.

The upshot is that clinical lab teams must find ways to perform the best quality control steps to keep their cardiac testing results as rigorous and reliable as possible.

Troponin testing

In the aftermath of a myocardial infarction, damage to the heart will cause cardiac-specific troponin levels in the bloodstream to surge, spiking within a few hours and remaining elevated for several days. There are two isoforms of the troponin protein relevant to this situation that can be detected with clinical cardiac assays: troponin I, which is only produced in the heart, and troponin T, which is also produced in the heart

but is present at low quantities in other muscles (a third form, troponin C, is not specific to the heart and is not useful for cardiac marker testing). The higher the levels of cardiac troponin, the more severe the heart attack.

Evidence has underscored the need to act quickly in the case of myocardial infarction, which requires generating rapid results from cardiac troponin tests. Fortunately, tests have gotten faster and more sensitive in recent years, giving clinical teams the opportunity to diagnose cardiac events sooner, delivering appropriate interventions earlier and leading to better outcomes for patients.

Modes of detection

The advent of high-sensitivity and ultra-high-sensitivity testing for cardiac troponin has been a significant leap forward for the clinical laboratory community. This follows years of continued improvements in sensitivity for troponin tests; the most sensitive options now have detection limits 100-fold lower

than conventional assays.1 Even tests that don’t meet this mark are about ten times more sensitive than assays that were once common in clinical labs. Still, manufacturers continue to aim for even lower limits of detection, with publicly stated goals of detecting troponin levels at less than 1 ng/L.1 With higher levels of sensitivity, troponin testing can be performed sooner: there’s no need to wait for levels to get high enough for detection. This enables faster results and earlier intervention. Today, highsensitivity immunoassays are available from several commercial manufacturers.

Recently, clinical researchers have begun to evaluate a new generation of cardiac troponin tests designed to be used at the point of care. In one clinical trial, researchers reported using a rapid point-of-care test to safely discharge hospital patients sooner.2 They used the test to identify patients with very low risk of experiencing a myocardial infarction in the next 30 days, finding that the approach was successful and offered an opportunity to get low-risk patients back home more quickly. Although high-sensitivity and point-of-care assays are shaping the future of cardiac troponin testing, many clinical laboratories still rely on conventional methods due to established workflows and long-standing clinical validation. High-sensitivity cardiac troponin assays use advanced immunoassay techniques to detect very low concentrations of troponin with high precision. In core laboratory settings, common detection modes include chemiluminescent microparticle immunoassays (CMIA) and electrochemiluminescence immunoassays (ECLIA), which provide automated, ultra-sensitive measurements. For point-of-care applications, lateral flow and microfluidic devices are increasingly used to deliver rapid results near the patient. In parallel, emerging technologies — such as electrochemical immunosensors, optical fluorescence-based platforms, and impedance-based sensors — are being developed to combine portability with high analytical sensitivity, supporting faster diagnosis and broader clinical access.

Better QC needed

While highly sensitive assays offer real benefit for patient care, they also create even more need for robust quality control in troponin testing. Highsensitivity assays can detect cardiac troponins even in healthy individuals,

underscoring the importance of establishing clear threshold levels to identify situations where intervention is required. For example, it is essential to understand how results from highsensitivity assays compare to those from conventional tests so they can be interpreted in the context of historical data.

Identifying the values that count as elevated is not a new challenge. Joint guidelines from the American College of Cardiology and the European Society of Cardiology determined that anything higher than the 99th percentile of troponin results in a healthy reference population should be considered elevated. 3 But due to the lack of a reference standard, it is impossible to pinpoint a specific troponin value that reflects the 99th percentile across all tests.1 With so many cardiac troponin assays available and no reference standard to align their values, studies have found that troponin values at the 99th percentile within the same population can vary up to five-fold.1 (Some recent progress has been made, with Standard Reference Material 2921 now available from the National Institute of Standards and Technology; however, this reference material alone does not guarantee full harmonization across commercial assays.)

This inconsistency highlights the need for reliable quality controls to help lab teams ensure that the results they produce are accurate and comparable. But it can be a challenge to identify the best control: Recombinant or native? Dried-down or liquid format? Manufacturer-provided or third-party? The ideal control is one that can be run across multiple test platforms and assays from any vendor. It should be highly stable for ease of use, streamlined workflows, and minimal storage constraints.

Manufacturers often include calibrators and controls with troponin assay kits, along with recommended schedules for their use, to verify basic assay performance under defined conditions. However, regulatory and accreditation bodies such as CLIA and CAP require clinical laboratories to demonstrate ongoing quality control that reflects real-world use, including multiple operators, reagent lots, and instrument conditions. As a result, most laboratories establish their own QC schedules using third-party controls to provide an independent assessment of assay performance and to meet regulatory expectations for objectivity and robustness. These controls may be run daily,

when a new operator begins using an instrument, following maintenance or calibration events, or at other critical workflow points. Controls are also commonly used for end-to-end workflow validation.

As a general rule, the best third-party controls should be as close as possible to patient samples being tested. Native controls tend to out perform recombinant ones because the latter may have different epitopes that don’t match patient materials. Controls that are value-assigned across multiple instrument manufacturers create commutability and a consistent benchmark for enabling reliable comparison of results and streamlined quality control across the laboratory network.

The need for shelf-stable quality control is essential for reliable assay monitoring, but ease of use is also a key consideration in routine clinical workflows. 2–8°C storage of controls reduces the need for frozen storage and transport. Lyophilized controls are widely available and valued for their long shelf life, ready-to-use liquid controls are often favored in routine laboratory workflows because they eliminate reconstitution, reduce preparation errors, and save technician time.

Looking ahead

Recent developments in cardiac troponin testing have led to new opportunities to detect dangerous events earlier than ever, opening the doors for improved patient care and long-term outcomes. But as sensitivity increases, there is more need than ever for reliable controls to ensure that testing workflows are delivering accurate results. With value-assigned native controls from third-party vendors, clinical lab teams can streamline their QC processes across testing platforms from a variety of manufacturers to deliver the most consistent and comparable results for their patients.

Raymond Lu serves as r & d Manager in the diagnostics division at Bio-Techne. He specializes in QC strategy for in vitro diagnostics and has contributed to the development of commercial assays, calibrators, controls, and high-sensitivity cardiac biomarkers.

References are available online at https://mlo-online.com/55352804

The “Goldilocks Approach” to molecular diagnostics stewardship

By Connie Savor, MD, MBA

When it comes to patient care, I think it is fair to say that clinicians, lab professionals — all of us who work in healthcare — want to get it ‘just right’ for every patient, starting at diagnosis.

Correct and timely diagnosis is essential for effective treatments and improving patient outcomes.1 In modern medicine, diagnostic tests figure prominently in clinical decision making surrounding a new diagnosis.

In infectious disease care, we’ve benefited from decades of technological advances designed to get to a diagnosis efficiently and cost effectively. Increasingly, however, advanced technologies introduce a new level of complexity and variety of options that must be managed if we are to get to ‘just right,’ right away.

Navigating the contribution–complexity paradox

For example, nucleic acid amplification-based tests for the diagnosis of infectious diseases, including polymerase chain reaction (PCR) tests, have rapidly expanded over the past two decades. With the increased availability and complexity of these tests, there is also an increased need for collaborative approaches to optimize test use to promote positive impacts on patient care, while mitigating potential negative impact or resource waste.2

Multiplex PCR tests (also known as ‘syndromic panels’) offer a timely example of this contribution-complexity paradox. Syndromic panels combine tests for numerous pathogens and resistance genes into a single test, and have offered a comprehensive approach to diagnosing infections, potentially leading to improved patient care and clinical workflow.3

Over the course of a few years, we’ve seen syndromic panel testing expand to multiple commercial assays for detection of respiratory, blood, gastrointestinal (GI), acute meningitis and encephalitis (ME), and lower respiratory tract infections (LRTIs).4 These panels are now fully integrated into many

clinical laboratories’ standard testing practices, 4 bringing institutions potential benefits such as increasing diagnostic yield and helping clinicians identify co-infections.

Yet, questions persist regarding syndromic panels, notes a 2023 joint society report published in the Journal of Microbiology. 5 While multiplex diagnostic approaches offer clear benefits, the report emphasizes that several critical uncertainties remain. These include determining the optimal breadth of panel targets, evaluating whether broad multitarget panels outperform more selective testing strategies, and assessing whether faster results alone drive improved outcomes — or if a more algorithmic, cost-conscious approach could better serve patients. As clinical evidence continues to evolve, these questions underscore the need for ongoing research and thoughtful implementation.

Antigen testing is another example of a contribution–complexity trade-off. These tests offer rapid results — often within minutes — which can be critical for timely decision-making, especially during outbreaks or in resource-limited settings. However, this speed comes at a cost: antigen tests are generally less sensitive than molecular tests like PCR, meaning they may miss infections, particularly early or late in the course of illness. For example, studies found that antigen test sensitivity ranged from 47% to 64% when compared with PCR.6

This trade-off between speed and accuracy illustrates the complexity of choosing the right diagnostic tool for the right situation. As highlighted in JAMA and Centers for Disease Control and Prevention (CDC) reports,7,8 while antigen tests can help identify infectious individuals quickly, they may not be sufficient for high-risk patients who require more accurate diagnosis for treatment decisions. In addition, the potential for false negative results due to the lower sensitivity of antigen tests may increase the risk for secondary cases and hospital-acquired respiratory infections.9

Principle Key Considerations

Right Patient Patient-Centric Decision-Making

Right Test Tailored & Targeted Testing

Risk Stratification:

Use patient-specific factors (e.g., symptoms, comorbidities, exposure history) to guide testing.

Population Health: tailor testing strategies to reduce transmission and improve public health outcomes.

Test Design: tests should be robustly designed to meet evolving needs, e.g., pathogen evolution, sample type optimized for patient needs and efficiency

Diagnostic Intelligence: Use evidence-based algorithms and decision support tools to guide test selection.

Clinical Relevance: ensure the test has actionable outcomes—i.e., it will influence treatment, prognosis, patient management, or further testing.

Right Time Consider the Setting & the Season

Pretest Probability Awareness: consider disease likelihood / use an algorithm to guide choice.

Seasonality: factor in seasonal trends and prevalence rates.

Turnaround Time Optimization: prioritize fast and decentralized testing to reduce unnecessary or empiric treatments and potentially improve outcomes. adopt in-house testing when possible.

Right Team Laboratorian-Clinician Collaboration

Diagnostic Synergy: combine know-how of laboratory and clinical experts to optimize test choice, ordering, interpretation, workflow integration, and feedback for continuous improvement.

Fortunately, the conversation regarding how, when, and why to deploy different tests dovetails with calls for widespread adoption of diagnostic stewardship, which is the practice of ordering the right tests for the right patient at the right time to inform optimal clinical care.10

Making diagnostic stewardship part of everyday healthcare

Diagnostic stewardship aims to improve the entire diagnostic process — from test ordering to performance to result reporting — by ensuring tests are used appropriately, collected correctly, and understood by both clinicians and patients.11 It has long been a topic of conversation among laboratorians, clinicians, and other healthcare providers who prioritize patient-centered care. Now, however, there is increased attention on the topic and a sense of urgency for providers to codify and adopt diagnostic stewardship programs across the care continuum.

This urgency is in part driven by two landmark reports in 2024 and 2025 from the CDC,1 developed with input from a broad array of stakeholders. Notably, the 2025 report — Core Elements of Hospital Diagnostic Excellence — defines six Core Elements for providers to adopt and adapt to their institutions. ‘Promote diagnostic stewardship is featured in the core element ‘Action,’ and the report includes guidance on operationalizing stewardship practices as part of a hospital-based Diagnostic Excellence program.

I applaud this ground-breaking work, which shies away from any notion that there is a ‘one-size fits all’ stewardship prescription. I wholeheartedly concur that what is called for

Starting Point

Develop consensus-driven diagnostic algorithms based on clinical indications and specimen types.

optimize testing to the environment (inpatient vs. outpatient needs). track test utilization, turnaround times, and downstream clinical actions to evaluate effectiveness.

support cross-functional partnerships, training, and education to facilitate proper test utilization and interpretation related to timing of patient’s presentation. evaluate the frequency of testing and retesting.

Break down traditional departmental silos to ensure clinical and testing perspectives are integrated into the diagnostic process

are ways to help providers find their ‘just right’ program. I propose The Goldilocks Approach offers a way forward.

The Goldilocks Approach to molecular diagnostics stewardship

The Goldilocks Approach is a patient-centered, evidencebased set of principles and practices intended to help providers realize diagnostic stewardship across the care continuum and for all health conditions. Rooted in four principles: Right Patient, Right Test, Right Time, and Right Team (See Figure 1), the Goldilocks Approach works synergistically with the CDC recommendations with prompts to help providers formulate and activate a stewardship program that aligns to their resources and resolve.

Further, the Goldilocks Approach was developed with real-world contribution–complexities top of mind. For example, returning to the molecular diagnostics examples cited earlier, introduction of a Goldilocks Approach will prompt thoughtful dialogue regarding stewardship of syndromic panels (is more always better?) and antigen testing (what are our acceptable speed/accuracy trade-offs per patient cohort?), among other topics.

Crossing the chasm together

We’re at an exciting time in the evolution of molecular diagnostics, propelled forward by technological advances that offer proven benefits and introduce complexity in clinical decision-making. A scientific paper from Zanella et al. frames the challenge clearly: “Clinicians are facing a choice:

Figure 1. Molecular testing and the Goldilocks Approach to diagnostic stewardship

INFECTION DIAGNOSTICS

should testing drive clinical management or should medical needs stay in the driver seat, with decisions to test and treat target(s) remaining secondary to a stepwise clinical strategy that includes consideration of epidemiological factors.”12 This tension reflects a broader shift in healthcare — one that calls for diagnostic stewardship, where testing supports, rather than dictates, clinical decision-making. The goal is not just more testing, but smarter testing, aligned with patient needs and public health priorities.

I anticipate ample and robust discussion of diagnostic stewardship will continue. It is my intent, and my hope, that the Goldilocks Approach contributes to that dialogue and catalyzes widespread adoption of common sense practices that help providers get care ‘just right’ for every patient.

REFERENCES

1. Core elements of hospital diagnostic excellence (DxEx). Centers for Disease Control and Prevention. Published February 11, 2025. Accessed January 29, 2026. https:// www.cdc.gov/patient-safety/hcp/hospital-dxexcellence/index.html.

2. Valencia-Shelton F, Anderson N, Palavecino EL, et al. Approaches to developing and implementing a molecular diagnostics

CLINICAL ISSUES

continued from page 14

weeks. A concordance rate of at least 95% is expected.

Equally important is ensuring that validation covers the full spectrum of cases the laboratory anticipates encountering. For a GI-focused practice, this meant carefully selecting representative biopsies and diagnostic scenarios to ensure digital interpretations were fully commensurate with glass slide review.

Redesigning the workflow

Adopting digital pathology is not simply a technology upgrade, it is a workflow transformation. Our objective was to ensure that all cases could be accessioned, processed, stained, scanned, and ready for digital review by the following morning.

Rather than imposing a top-down solution, we empowered our laboratory team to redesign the workflow from the ground up. They were encouraged to think creatively, without preconceived constraints around shifts, staffing patterns, or traditional processes.

The result was an impressively streamlined workflow that improved efficiency, enhanced scalability, and positioned the lab to absorb future

stewardship program for infectious diseases: an ASM Laboratory Practices Subcommittee report. J Clin Microbiol. 2024;62:e00941-24. doi:10.1128/jcm.00941-24.

3. Dumkow LE, Worden LJ, Rao SN. Syndromic diagnostic testing: a new way to approach patient care in the treatment of infectious diseases. J Antimicrob Chemother 2021;76(Suppl 3):iii4-iii11. doi:10.1093/jac/ dkab245.

4. Dien Bard J, McElvania E. Panels and syndromic testing in clinical microbiology. Clin Lab Med. 2020;40(4):393-420. doi:10.1016/j. cll.2020.08.001.

5. Lewinski MA, Alby K, Babady NE, et al. Exploring the utility of multiplex infectious disease panel testing for diagnosis of infection in different body sites: A joint report of the Association for Molecular Pathology, American Society for Microbiology, Infectious Diseases Society of America, and Pan American Society for Clinical Virology. J Mol Diagn. 2023;25(12):857-875. doi:10.1016/j.jmoldx.2023.08.005. Erratum in: J Mol Diagn. 2025;27(3):232. doi:10.1016/j. jmoldx.2024.12.004.

6. Smith-Jeffcoat SE, Mellis AM, Grijalva CG, et al. SARS-CoV-2 viral shedding and rapid antigen test performance - Respiratory Virus Transmission Network, November 2022-May 2023. MMWR Morb Mortal Wkly Rep. 2024;73:365-371. doi:10.15585/mmwr. mm7316a2.

7. Chu VT, Schwartz NG, Donnelly MAP, et al. Comparison of home antigen testing with RT-PCR and viral culture during the course of SARS-CoV-2 infection. JAMA Intern Med. 2022;182(7):701-709. doi:10.1001/

growth and new service lines with minimal friction.

Training and change management

Training is essential to success. While many pathologists adapt quickly to digital review, confidence builds over time. Comprehensive training for histology staff, IT personnel, and pathologists ensured that everyone understood not only how to use the system, but how to troubleshoot and support one another.

We designated several in-house experts to serve as first-line support for the pathology team. This internal safety net made a significant difference, reducing anxiety and accelerating adoption.

Looking ahead

Evaluating and implementing a digital pathology system is a substantial undertaking, particularly for an independent laboratory with established workflows. For OmniPathology, the process proved to be an opportunity to reassess our priorities, modernize our operations, and position ourselves for sustainable growth.

Digital pathology has given us a more efficient, scalable, and forward-looking

jamainternmed.2022.1827.

8. Kennedy AG. Evaluating the effectiveness of diagnostic tests. JAMA. 2022;327(14):1335-1336. doi:10.1001/ jama.2022.4463.

9. Ghazi L, Simonov M, Mansour SG, et al. Predicting patients with false negative SARS-CoV-2 testing at hospital admission: A retrospective multi-center study. PLoS One 2021;16(5):e0251376. doi:10.1371/journal. pone.0251376.

10. Fabre V, Davis A, Diekema DJ, et al. Principles of diagnostic stewardship: A practical guide from the Society for Healthcare Epidemiology of America Diagnostic Stewardship Task Force. Infect Control Hosp Epidemiol 2023;44(2):178-185. doi:10.1017/ice.2023.5.

11. Singh HK, Claeys KC, Advani SD, et al. Diagnostic stewardship to improve patient outcomes and healthcare-associated infection (HAI) metrics. Infect Control Hosp Epidemiol. 2024;45(4):405-411. doi:10.1017/ ice.2023.284.

12. Zanella MC, Meylan P, Kaiser L. Syndromic panels or “panel syndrome”? A perspective through the lens of respiratory tract infections. Clin Microbiol Infect. 2020;26(6):665-668. doi:10.1016/j. cmi.2019.12.018.

Connie Savor, MD, MBA serves as Chief Medical Officer for Cepheid , a molecular diagnostics company that makes the GeneXpert systems and Xpert tests.

platform, one that enhances diagnostic quality today while opening the door to AI-driven innovation tomorrow. Access to experienced mentors and resources from organizations such as the College of American Pathologists and the Digital Pathology Association was instrumental in our success.

For laboratories considering the leap into digital pathology, the journey is challenging, but the destination is well worth the effort.

Ronald A. Blum, PhD With over 25 years’ experience in clinical laboratories, diagnostics and clinical trials, Dr. Blum has helped companies drive growth, expand into new markets, and increase profitability and valuation. He has been instrumental in bringing to market hundreds of new and enhanced assays and has served in senior leadership roles at major clinical laboratories and diagnostic companies. Dr. Blum has lectured internationally on the latest developments in precision medicine, technology, and laboratory science, and has published extensively. He is Vice President of Science & Technology at OmniPathology and Chief Executive Officer for Blum & Associates Consulting, LLC

The cardiometabolic care gap laboratories can help identify earlier

By Justin Jones, PhD

Data generated within the clinical laboratory stands to reshape longterm patient care strategies. One opportunity is identifying heart failure risk in patients with diabetes.

Heart failure and diabetes mellitus are among the most prevalent and interconnected chronic conditions worldwide. As cardiometabolic disease is increasingly recognized as a multi-organ continuum, it has become clear that glycemic control alone does not fully capture cardiovascular risk in patients with diabetes. Individuals with diabetes face a substantially increased risk of developing heart failure, often years before symptoms emerge and frequently in the absence of overt coronary artery disease.1,2

Increasing evidence shows that cardiometabolic disease is not a series of siloed conditions, but rather an interconnected spectrum. Insulin resistance and obesity serve as root contributors, triggering cascades affecting the heart, kidney, liver, and vascular system. These

interconnected pathways make individuals with diabetes far more susceptible to early cardiac stress and eventual heart failure, even before symptoms arise.

Cardiac biomarkers, including N-terminal pro-B-type natriuretic peptide (NT-proBNP) and high-sensiti vity cardiac troponin (hs-cTn), offer laboratorians objective tools to support earlier detection of myocardial stress and injury, improve risk stratification, and facilitate more proactive cardiometabolic care.1-3

The expanding and earlier burden of heart failure

Heart failure remains a major public health challenge, affecting more than 64 million people globally and accounting for substantial morbidity, mortality, and healthcare utilization.4 Contemporary definitions of heart failure have evolved to reflect earlier disease recognition. In addition to symptoms and structural or functional cardiac abnormalities, abnormal cardiac biomarkers are

now recognized as integral components of heart failure diagnosis and classification.1,5

This shift acknowledges that myocardial stress and injury often precede overt clinical manifestations. For patients with diabetes who may develop cardiac dysfunction through metabolic and microvascular mechanisms, biomarker-based assessment offers a means to identify risk earlier in the disease course.2

Diabetes and the cardiometabolic continuum

Diabetes confers a two- to five-fold increased risk of heart failure.2 This elevated risk is driven not only by traditional cardiovascular pathways, but also by insulin resistance, chronic inflammation, endothelial dysfunction, and altered myocardial metabolism.3,6 Diabetes frequently coexists with obesity and chronic kidney disease, conditions that further amplify cardiac stress and accelerate progression toward heart failure. Poorly controlled blood glucose accelerates

vascular damage, which contributes to complications such as atherosclerosis, heart failure, and kidney disease. Hemoglobin A1c (A1C), a key biomarker that reflects average blood glucose over approximately three months, is essential in the cardiometabolic continuum as even modest elevations are associated with increased cardiovascular risk. Maintaining A1C within target ranges helps slow disease progression, reduce complications, and improve long-term cardiometabolic outcomes.

These overlapping mechanisms underscore the importance of moving beyond glucose-centric assessment toward integrated cardiometabolic risk evaluation.

Heart failure risk in patients with diabetes extends beyond glycemic control and reflects a complex cardiometabolic continuum.

Natriuretic peptides: Biology that informs interpretation

Natriuretic peptides, including BNP and NT-proBNP, are synthesized and released by cardiomyocytes in response to increased myocardial wall stress . 7 Acting as counter-regulatory hormones, they promote vasodilation, natriuresis, and attenuation of maladaptive cardiac remodeling through cyclic GMP-mediated pathways.

NT-proBNP is released in equimolar amounts with BNP but has a longer circulating half-life due to differences in clearance mechanisms. Understanding this biology, along with the presence of multiple circulating peptide fragments detected by clinical assays, supports appropriate interpretation across acute and chronic care settings.7,8

Importantly, natriuretic peptides are intended to support, not replace, clinical judgment. Appropriate use requires understanding of peptide biology, differential diagnosis, and clinical context.8,9

Diagnosis and exclusion of heart failure

Natriuretic peptides are embedded in international heart failure guidelines as diagnostic aids.1,5 Low concentrations provide a strong negative predictive value, effectively excluding heart failure in patients presenting with dyspnea or nonspecific symptoms, while elevated values support further cardiovascular evaluation.5

Risk stratification and prognosis

Beyond diagnosis, NT-proBNP and BNP provide independent prognostic

information. Elevated concentrations are associated with increased risk of heart failure hospitalization and cardiovascular mortality, even in patients without previously diagnosed heart failure.1,10 Serial measurements further enhance prognostic value by identifying patients whose risk trajectory is worsening over time.10

Interpreting biomarkers in diabetes and comorbid conditions

Interpretation of natriuretic peptides requires careful attention to comorbidities common in diabetes. Elevated values may reflect myocardial stress related to atrial fibrillation, pulmonary hypertension, renal dysfunction, or systemic illness, and should not be interpreted in isolation.7,8

Conversely, obesity is associated with lower circulating natriuretic peptide concentrations due to suppressed peptide production and altered hemodynamics.11 In this context, values that appear modest may still represent abnormal cardiac stress, highlighting the importance of laboratorian–clinician collaboration.

High-sensitivity troponin and subclinical myocardial injury

High-sensitivity cardiac troponin assays detect low-grade myocardial injury below thresholds for acute coronary syndromes. In patients with diabetes, such subclinical injury is common and reflects microvascular disease and metabolic stress.3 Elevated hs-cTn concentrations, even within the reference range, are independently associated with incident heart failure and adverse cardiovascular outcomes.10

When interpreted alongside natriuretic peptides, hs-cTn provides complementary insight into myocardial injury and hemodynamic stress, enabling a more comprehensive assessment of cardiometabolic risk.3,10

Toward prevention: Identifying stage B heart failure

An emerging application of cardiac biomarkers is the identification of stage B heart failure, defined by structural heart disease or abnormal cardiac biomarkers in the absence of clinical symptoms.1,5 Asymptomatic individuals with elevated NT-proBNP face a significantly higher risk of progressing to overt heart failure.10

Consensus guidelines increasingly support biomarker testing in high-risk

populations, including patients with diabetes, to identify early heart falure risk and prompt timely clinical evaluation.1,2 This biomarker-guided approach aligns with contemporary strategies aimed at shifting heart failure care from reactive diagnosis to proactive prevention.

The end game: Using lab data to affect change

Labs offer objective biomarker insights to detect signs of cardiometabolic risk earlier. Taking it one step further, asserting data-driven insights can shape longer-term care strategies in partnership with clinicians to ensure

Beyond

diagnosis, NTproBNP and BNP provide independent prognostic information.

clinical data is fully understood and applied. 12 Rather than operating in isolation, laboratory teams are called to embrace close collaboration with clinicians, contribute to education and training, and continually deepen their understanding of clinical needs so that diagnostic testing can more effectively support patient care.

If there’s one silver lining to intensifying pressure to achieve better patient outcomes, it is that physicians now widely welcome this type of collaboration.13 By advancing earlier detection and supporting coordinated, patient-centered care, these biomarkers highlight how laboratory medicine can help drive meaningful progress against the leading cause of death in the United States.

Justin Jones, PhD has more than a decade of experience in diagnostics and translational science, including leading assay development projects at Siemens Healthineers. in his current position as a Field Medical Partner, he specializes in cardiac biomarkers and clinical education. Justin holds a PhD in biochemistry and is dedicated to connecting laboratory insights with patient care.

References are available online at https://mlo-online.com/55355144

STATE OF THE INDUSTRY LAB DATA ANALYTICS

Data analytics in the medical laboratory: Progress, gaps, and persistent barriers

Results from the 2026 MLO State of the Industry Survey reveal steady digital expansion, ongoing interoperability challenges, and cautious movement toward AI adoption

By Kara Nadeau

This year’s MLO State of the Industry (SOI) Survey Article on Data

Analytics explored how medical laboratories are navigating digital transformation amid mounting operational, financial, and workforce pressures.

A total of 127 medical laboratory professionals participated in the survey, with most working in hospital labs (62%) and holding lab manager, administrator, supervisor, or director roles (48%).

Respondents represented a broad range of lab sizes, from small independent labs to large, multi-site organizations.

Alongside the subjective survey data, MLO presents expert insights from laboratory professionals and vendors in this space.

Five top survey findings:

• Reported LIS infrastructure shifts away from on-prem, with use of inhouse lab information system (LIS)

software/servers dropping to 25% in 2026, down from 52% in 2025, and 70% in 2024. Cloud-based LIS adoption increased modestly to 24%.

• D igital enablement is expanding beyond orders/results, with increased adoption of electronic QA/QC, scheduling, and inventory management functions.

• L IS/EHR interoperability and data integration remain persistent bar-

riers, reported by more than half of respondents.

• Data quality and security challenges stem equally from system fragmentation and workforce readiness , including staff training and literacy gaps.

• I nterest in AI is growing, but adoption remains limited , with only 7% reporting production use and most labs prioritizing foundational analytics investments.

Lab technology system infrastructure trends

Survey results point to incremental LIS infrastructure change rather than broad transformation. Most laboratories continue to rely on enterprise-wide electronic health record (EHR) embedded (53%) or stand-alone LIS platforms (32%), while use of on-premise servers continue to decline (25%, down from 52% in 2025, 70% in 2024). Cloud LIS adoption remains limited (24%), constrained by organizational policy, even as electronic workflows expand.

One medical lab professional commented that their lab had integrated with its hospital information system (HIS), software server systems, and

cloud-based systems, noting how “no solution can seem to meet all our needs.”

More than three-quarters of respondents (76%) reported that cloud SaaS laboratory solutions are not currently permitted within their organizations, underscoring ongoing governance and security concerns.

Ed Price, director of Information Systems, Computer Service & Support, shared his thoughts on how vendor-lab partnerships are evolving around data governance, cloud adoption, and compliance: “Partnerships are getting more formal with shared responsibility models, standardized security attestations, tighter vendor due diligence, and clearer policies for access, retention, and auditability rather than informal handshake deals.

hamper automation, innovation, and operational efficiency. Migrating to interoperable APIs like Epic is costly and labor-intensive.

“At the same time, legacy, vendor-specific systems and fragmented interfaces force staff to manually reconcile duplicate orders and rely on custom SQL and Excel workarounds to produce analytics. Limited functionality and outdated infrastructure further constrain what labs can afford and implement, ultimately slowing clinicians and lab staff and hindering process improvements.”

“Cloud adoption is moving forward with stronger controls like segmentation, least privilege access, comprehensive logging, and compliance alignment. The goal is for governance to be designed in from the start, not added later.”

Electronic workflows and integration

Electronic orders and results remain the most mature digital functions (89%), followed by analyzer integration (73%). Year-over-year growth was reported in electronic scheduling (39%, up from 25%), QA/QC (65%, up from 54%), and inventory management/ supply chain management (31%, up from 23%), signaling broader operational digitization. However, there was a reported decline in adoption of point of care testing (POCT) management (37%, down from 41%) and customer service tools (17%, down from 20%).

Interoperability

Cyndee Jones, MSHCA, CLS, senior director, Laboratory Services, Valley Health Laboratory Administration, Winchester, Va., spoke to interoperability constraints and its impact on data sharing between systems: “The technology/testing does not have an automated way of getting into the patient record. This can be from a lack of interface or driver for automated analyzers, a lack of mechanism to scan in test kit information, and poor structure/ functionality within the EHR for resulting tests outside of traditional laboratory information systems (e.g., POCT, physician office labs).

“Often, without automated processes testing is documented on paper and scanned into the chart. This process makes results hard to find and unable to be integrated in the same way as discrete data points.”

Interoperability challenges continue to limit the impact of electronic workflows. More than half of respondents (54%) cited LIS and EHR integration as stumbling blocks to automation and analytics adoption.

Amanda J. Lewis MLS(ASCP) cm , quality assurance supervisor, Abilene Market Laboratories, Abilene, Texas, commented on how these issues impact her lab’s operations: “Interoperability gaps between the LIS, instruments, and EHR create daily challenges that

Marci Dop, VP Enterprise Lab Operations, ELLKAY, offered a vendor’s perspective on system connectivity and data management: “Interoperability is still a challenge because many labs still use connections that simply move data from one system to another. Real progress depends on reliable patient identification across systems, standardized orders and results, and data that is consistent, trusted, and usable for reporting and clinical decisions.”

Lisa-Jean Clifford, President at Gestalt Diagnostics added, “One of the biggest issues is the transparency and terminology being used by various vendors and solution providers when using the word interoperability. There are varying degrees of integration, which of course carry varying degrees of value to the laboratory and workflows. A vendor who is using the word interoperable as

amanda Lewis ed Price

interchangeable with interfacing is not doing a full, real-time, bi-directional data exchange of all discreet data. Interoperability means open architecture, flexible workflow support and real-time data exchange between multiple differing applications and data sets.”

She continued, “Another issue is that some vendors are not willing to openly exchange this data even if they are able to. There is a bit of a turf war when a vendor wants to maintain complete control over the customer vs. providing a fully functioning solution that is best for the customer or end user.”

Data quality and security trends

Figure 1: Where would AI be most bene cial in your lab?

Billing

Staf ng

Results review/ diagnostic alerts

Operational and productivity enhancements

Other

When asked to report on the primary challenges faced when managing laboratory data quality, integration across multiple systems (50%) and staff training and data literacy (50%) were ranked highest, followed by data accuracy/validation (45%) and data standardization (39%).

Vy Nguyen, informatics marketing manager, Clinical Diagnostics Group, Bio-Rad, commented on how vendors can help with their customers’ data challenges: “Vendors are helping labs improve trust in their data by building solutions that prioritize seamless integration with existing systems and embed validation checks at the point of entry, reducing manual rework.

“They’re also investing in intuitive user experiences and contextual guidance, so that staff at all levels—not just data specialists—can understand, interpret, and act on data confidently without added complexity.”

Lewis offered her thoughts on the challenges of staff education and training in this area: “Significant skill gaps persist due to minimal efforts to upskill workers. Manual data entry errors and limited data literacy undermine analytics and clinical outcomes. Consistent data practices, governance, automated validation, and targeted training are needed, yet investment and incentives remain scarce.”

Turning to challenges with data security, cybersecurity/ access control topped the list (53%), followed by staff training/ data literacy (48%). Most laboratory professionals reported that their organizations have dedicated cybersecurity resources (65%) and vendor risk assessment requirements (72%).

Performance KPIs, analytics, and forecasting trends

Key performance indicators Laboratories continue to prioritize operational key performance indicators (KPI), including turnaround time (87%), quality improvement initiatives (80%), cost per test (57%), and staff productivity goals (48%). Benchmarking practices vary widely, with roughly one-third (35%) comparing performance externally, a little over one quarter (27%) benchmarking internally across sites/departments, and the remainder not benchmarking at all.

Lee B. Springer, Ph.D., senior VP of Operations & Strategic Development LabSavvy, contrasted operational versus tactical

analytics: “Operational analytics get you the ‘what’ and ‘why’ to ensure smooth operations but not the tactical ‘how’ which is more directly linked to your strategic analytics or the direction “where” the business is heading. Operational analytics will get you a TAT percentage, where tactical analytics will get you a TAT to ER admit ratio or TAT/ productivity value.”

Regarding productivity, Jones commented on the criticality of this metric and the challenges of measuring it: “Staffing productivity is the performance indicator that is the most critical for us right now. The target is established by evaluating all similar sized laboratories and how many employees are used (e.g., # of employees per # of billable tests) then establishing what is considered the most ‘efficient’ for that compare group.

“This metric is apart from anything associated with quality, reliability, complexity of testing, or amount of test systems or methods used. The challenge is that the more understaffed all laboratories become, the more ‘efficient’ they appear on paper. This ends up moving the bar for all laboratories to a point that may impact employee satisfaction, retention, and quality of service.”

Turning to KPIs that help lab leaders understand their bottom line, Stephanie Denham, XiFin VP, RCM Systems and Analytics, commented: “Accurate cost-per-test tracking, paired with test level profitability analysis, enables labs to understand the true economics of their business. Labs need visibility across the entire lifecycle of an order - from order capture, through testing, to billing and reimbursement - to identify where costs are occurring, where inefficiencies exist, or where revenue is leaking.

“Ultimately, the labs that achieve stronger financial visibility are those that align data with process. When you can clearly see how costs map to every step of the revenue cycle, you can prioritize the right areas for optimization and automation. This ensures that efforts to reduce cost-to-collect deliver the highest possible return—without disrupting clinical operations.”

Vy nguyen

Stephanie denham

cyndee Jones, MShca, cLS

Figure 2: Have you begun implementing (or actively considering implementing) AI or machine learning tools in your laboratory operations or data analytics?

Yes, implemented in production

Yes, pilot or evaluation phase

Not yet, but planned within 2 years

No plans currently

Analytics

Analytics adoption increased modestly compared with last year, with more labs using data analytics across all aspects of lab management (20%, up from 12%). However, analytics tool maturity remains uneven, with many organizations relying on tools integrated with their LIS (36%). Fewer respondents reported using tools that are part of their LIS (27%, down from 32%), or a separate tools for data analytics (17%, down from 27%).

When asked about data visualization or dashboard tools used for reporting and decision-making, just over half of lab professionals (51%) reported using built-in LIS dashboards, followed by instrument-provided analytics (33%), custom-built internal dashboards (28%), and third-party business intelligence (BI) platforms (20%). Additionally, 19% reported no current use of data analytics tools.

Springer offered his interpretation of the trend toward LIS-native dashboards or instrument analytics over third-party BI adoption: “It signals that the laboratory is still looked at as an ancillary department vs. a business service line. Labs need to see themselves and push to be seen as a business service line that warrants systems with robust predictive analytics to help create business intelligence models that drive success. Looking outside of the lab industry for analytics solutions is also key to creating models that are adaptable to lab type, market and clients served.”

Price spoke to why labs tend to rely on built-in analytics tools, noting how AI can serve as a bridge to broader analytics capabilities: “Labs lean on LIS-native and instrument analytics because they’re turnkey, familiar, and often sufficient for day-to-day operational decisions without the added cost and complexity of a separate analytics platform. It signals many labs are still building readiness - standardizing definitions, improving data quality, and tightening

governance — before expanding into broader, enterprise-wide analytics.

“AI can also help bridge the gap by surfacing insights and answering common questions directly from existing data while that foundation is being built.”

Looking at the data that feeds their lab analytics, more than one-third (33%) reported regularly integrating internal analytics with external data sources, while (39%) report no integration.

Nearly one-quarter (24%) reported their data source(s) is refreshed in real-time and the same percentage (24%) reported daily data refreshment.

Forecasting

Use of electronic management forecasting declined year-over-year across test utilization (48%, down from 68%), staffing levels (44%, down from 55%), and workloads (49%, down from 55%). More than three-quarters of lab professionals (76%) reported no electronic forecasting tools, indicating continued reliance on manual methods.

Test tracking trends

Reported tracking of infectious disease test volumes declined across multiple categories compared with last year, including influenza (50%, down from 67%), COVID-19 (57%, down from 73%), STI/HIV (30%, down from 45%), and strep (32%, down from 45%). New tracking categories introduced this yearHbA1c and Troponin – were reported by roughly one-third of respondents, suggesting evolving priorities tied to chronic disease management and cardiac care.

Jones spoke to how staffing shortages impact labs’ abilities to provide broad testing portfolios: “There are not enough people going into the laboratory career fields. There is also

Figure 3: What are your primary challenges in managing laboratory data quality?

an extreme lack of college programs available to meet the industry needs, which further impacts the availability of people coming into this career field. [Because of this], many laboratories have sent out testing and operate with a limited test menu.

“This common business practice has decreased the number of students who can meet the full gambit of clinical training to qualify for their degree. This means a college cannot graduate enough students to make the program financially successful from their perspective. The resulting program closures further compound the workforce availability problem.”

When asked how better integration between diagnostic platforms and analytics help labs maintain visibility without increasing manual effort, George Wierschem, MBA, MT(ASCP), senior global product manager, Informatics, QuidelOrtho, answered: “When diagnostic platforms are fully integrated with centralized analytics tools, labs may gain real-time visibility into testing activity across supported instruments and sites without relying on manual effort.

“Automated dashboards and analytics can help consolidate results from multiple sources, enabling lab professionals to monitor operational trends, performance indicators and workflow changes, and drive meaningful patient care decisions, especially as operational complexity increases.”

Denham commented on the financial value of lab/provider data integration: “Labs need the ability to drill down to the ordering physician level. Understanding a provider’s test mix and payor mix is vital, especially when certain clients may predominantly send Medicaid or uninsured patients, negatively affecting profitability. These insights help labs segment their client base, refine service strategies, and make informed decisions about resource allocation.”

AI interest and usage trends

Interest in AI continues to grow, but adoption remains limited and uneven. Only a small percentage of laboratory professionals report active use of AI (7%) or AI pilot implementations (11%), while most (61%) have no near-term plans.

Perceived value of AI in laboratory operations centered on operational and productivity enhancements (37%), reviewing results/diagnostic alerts (28%), and billing-related use cases (20%).

AI governance approached vary, with respondents describing system-led, lab-led, and collaborative models, as well as uncertainty regarding future ownership and oversight.

“AI in healthcare is still developing… outdated systems and fragmented data, make centralized, validated databases essential to its effectiveness,” said Lewis.” Starting with small-scale pilots, such as anomaly detection or maintenance

prediction, may help build trust before expanding to critical clinical workflows.”

“The number one thing that must happen for increased adoption and use of AI in the clinical laboratory space is approval from the FDA,” said Jones. “Without their approval, the CLIA complexity increases and the task to maintain regulatory compliance and accreditation standards becomes a daunting task. Many laboratories do not have resources to support that.”

Nguyen pointed out how labs must prioritize foundational data and governance when considering AI tools: “Labs often overestimate AI’s readiness for fully autonomous interpretation or decision-making, not recognizing that these tools still require well-curated data and expert oversight to be both reliable and actionable.”

She offered up the following AI use cases where labs can find tangible value today: “Targeted applications like predictive maintenance for instruments, automated result flagging to support technologists, and workflow optimization that reduces turnaround times.”

According to Mike Hampton, chief commercial officer (COO), Sapio Sciences, “The labs making progress are embedding AI tools into workflows and applying platform-level intelligence, so context, governance, and decision-making remain connected. Disconnected tools can drive shadow AI and fragment workflows.”

He has seen AI deliver value to labs through use cases such as “Automating result interpretation and providing real-time assistance during routine lab processes.” He explained how “These gains are typically localized and task-specific, which is where many labs begin to overestimate readiness.”

Clifford reported observing several Gestalt customers utilize AI for primary diagnosis and teaching purposes. She continued, “However, I have heard lower than realized numbers in discussions with other vendors, including AI

Data standardization

Integration across multiplesystems

Regulatory compliance (e.g., HIPAA, CLIA)

Data accuracy and validation

Cybersecurity and access control

Staff training and data literacy

Figure 4: What are your primary challenges in managing laboratory data security? Percentage

Lee b. Springer, Ph.d

Marci dop

George Wierschem, Mba, Mt(aScP)

partners of ours. The benefits we hear from several of our customers align with patient safety, accuracy, support of the pathologist in workflow enhancement and confidence in reinforcing their diagnosis. The main purpose for adoption we have heard is: 1. Providing the best possible patient care; and 2. An aide for the pathologist.”

Looking ahead

Topping the list of current and short-term (next 2 years) challenges faced by lab professionals, are staffing (#1), followed by funding at (#2), and technology (#3). Strategic IT priorities are focused on LIS replacement (20%) and infrastructure and platform development (18%), followed by revenue cycle management optimization (13%) and data analytics optimization to support lab management (13%).

Advanced initiatives such as digital pathology implementation (6%), interconnectivity with reference and public health labs (4%), and adopting AI/ML tools (4%) ranked lower, suggesting that laboratories are focused on stabilizing core operations.

When asked what will distinguish labs that successfully mature their analytics capabilities over the next three years, Wierschem stated: “Based on my observation, labs that successfully advance their analytics capabilities tend to look

beyond static reports toward cloud-based platforms that securely manage big data integrated from multiple sources and embed analytics directly into daily lab workflows, where permitted.

“Over time, these analytics capabilities may enable long-term data analysis to potentially detect and alert labs to shifts or trends, helping them to proactively address areas that could affect patient outcomes or their laboratory business.”

Moving forward, Hampton predicts labs that “treat analytics and AI as part of a unified, configurable lab platform rather than standalone reporting tools” will pull ahead of the curve. He added, “The differentiator will be applying AI across workflows with human oversight, surfacing trends and system-level issues early enough to change outcomes while maintaining governance and control.”

Dop believes labs that embed analytics directly into lab workflows, rather than producing more dashboards, will be best positioned to move insights into action. She noted how they will have the ability to use data “to proactively manage turnaround time, capacity, quality issues, and outreach performance.” She added,“They will also be better positioned to adopt predictive and AI-driven use cases because their data is trusted, timely, and usable.”

Kara Nadeau has 20+ years of experience as a healthcare/medical/technology writer, having served medical device and pharmaceutical manufacturers, healthcare facilities, software and service providers, non-profit organizations and industry associations.

Mike hampton

Lisa-Jean clifford

Are you doing diagnostics — or logistics?

What can you do in just three seconds ?

By Thomas Coulson

Is it possible to make truly significant decisions in a short amount of time? Because essential tasks in the high-stakes field of healthcare diagnostics typically require time and deliberate intervention. Manual procedures, subjective visual inspections, and valuable resource time are frequently involved in characterizing a patient sample — confirming its identity, assessing its quality, and guaranteeing its suitability for testing. This extended, hands-on involvement affects turnaround time and, most importantly, leaves room for human error. This is where automation goes beyond speed, especially with Advantaged Workflows. Automation involves enabling the lab to complete thorough sample characterisation in just three seconds with advanced intelligence that automatically reacts to challenges, supports quality, and

enhances the consistency and clarity of diagnostic results throughout the process.

The hidden cost of errors: When diagnostic integrity falters early

Every step of the testing process is under tremendous pressure in the fast-paced setting of a diagnostic laboratory due to the sheer volume of samples, growing test complexity, and growing resource limitations. The journey to an accurate diagnosis frequently falters long before the sample ever reaches an analyzer, even though the analytical phase frequently receives the most attention due to its sophisticated methodologies and precision instruments. In actuality, the pre-analytical phase — that is, everything that takes place from the time a sample is collected until it starts analysis — is where a startling majority of laboratory errors occur — estimates suggest up to 70%.1 Mislabelling, inadequate sample volume, improper tube types, and samples with an unidentified or inappropriate spin status are examples of these silent saboteurs.

In addition to re-draws and lost time, each error carries a hidden cost. A series of unfavorable outcomes could result from each inappropriate sample that passes through:

• Delayed results: Inadequate volume requires a re-draw, a mislabelled tube needs to be correctly identified, and improper tube prioritization can cause important results to be delayed. The timeline for diagnosis and treatment is postponed with each interruption.

• I naccurate results: Clinicians may be misled in their diagnosis by an unflagged compromised sample, such

as one with an incorrect additive ratio because of low volume or an inappropriate spin status.

• I ncreased workload and cost: Labs must spend more time finding mistakes, interacting with wards, and conducting re-collections and retesting, which require more labor and reagents.

• Patient dissatisfaction and anxiety: Repeated venipunctures can cause discomfort and anxiety and erode patient trust in the healthcare system. 2

How can automation address these challenges? Automation is about doing things better, more consistently, and with a direct, positive impact on patient outcomes, especially by addressing the pervasive pre-analytical issues.

Protecting diagnostic quality from the start

To effectively address these complex and compounding challenges, a new approach is required — one that combines flexible instrumentation, scalable automation, and integrated, intuitive informatics solutions — all meticulously designed for laboratories to handle the nuanced demands of modern patient care. This powerful combination is essential for achieving what can be referred to as Advantaged Workflows. How do Advantaged Workflows transform the laboratory’s ability to actively combat pre-analytical errors? It begins with empowering automation with intelligent pre-analytical sample checks — a cornerstone capability applied right at the earliest possible stage. The seamless integration of scalable automation (for efficient sample handling) with sophisticated clinical informatics (for embedded intelligence) means that systems can proactively inspect a sample’s integrity (details below), assess its suitability, and manage its journey. This intelligence

precisely enables the prevention and mitigation of critical pre-analytical mistakes like mislabelling, insufficient volume, mis-prioritization, incorrect tube types, or inappropriate spin status, ensuring diagnostic quality from the outset.

Precision in seconds: Automation’s vigilance

Imagine a sophisticated automation system that actively and precisely inspects tubes in addition to transporting them. What might occur in a system like this in three seconds? In this moment, a top automation platform can complete a thorough, nine-parameter specimen check. Importantly, this comprehensive characterization takes place in a single multipurpose module before the sample is ever loaded onto the main automation transport line. This is very different from systems that might perform pre-analytical checks directly on the main transport line or spread them across several modules, which can result in needless traffic and bottlenecks. With the use of advanced optical sensors, integrated software, and camera technology, an automation platform can do the following:

• Verify identity and context: Rapidly read the barcode identification (ID) and retrieve critical patient, test, and priority information from the clinical informatics system(s). This immediately flags mislabelled or missing orders and establishes priority.

• A ssess tube integrity and type: Detect the tube type (size, cap color, presence/type of gel separator) and intelligently cross-reference it with the ordered tests to identify incorrect tube types before analysis, preventing potentially invalid results due to improper additives.

• C heck sample volume: Accurately stratify fluid levels within the tube (clot, gel, serum, air) to ensure sufficient volume for all requested tests, even detecting levels through multiple layers of paper labels. This immediately identifies low volume samples, saving valuable analyzer time.

• Determine spin status: Identify whether a sample has been pre-centrifuged or requires spinning, ensuring the correct spin status for sample processing. An unspun sample can be routed to an integrated centrifuge, eliminating manual handling and ensuring proper processing.

• C ross-reference data with algorithms: Algorithmically compare expected parameters (e.g., tube color versus ordered tests, volume versus required tests) to immediately flag any other non-conformities. Real-time, comprehensive error detection — done before samples even hit the track, all in one place — changes the game for labs. Automation is not just moving tubes around anymore; it is actively protecting diagnostic quality. It spots and deals with unsuitable samples before they clog up the system, waste analyzer time, or skew results. As Worcestershire Acute Hospitals NHS Trust observed after implementing Beckman Coulter’s DxA 5000 system, errors are shown upfront by the system, reducing the clinical risk of producing erroneous results for the patient, while improving the efficiency of quality control.3

Elevating the lab’s role: The lab as diagnostic gatekeeper

This kind of track-independent, pre-analytical approach lets labs reinvent themselves. They are not just processing samples — they are standing guard over diagnostic quality

and taking on a bigger, more strategic role in healthcare. Instead of scrambling to fix errors after the fact, labs stop problems before they start. That shift frees up lab staff to focus on the work that really matters: complex analysis, critical decisions, and continuous improvement. It builds a culture centered on excellence and patient safety. And the ripple effects go way beyond catching a few mistakes:

• Patient safety, front and center: When labs cut down on bad results and speed up alerts for redraws, they slash the risk of misdiagnosis and delays. Patients get answers faster, with less anxiety and fewer repeat visits.4

• O perations that just work: By trimming manual steps, redraws, and troubleshooting, labs save serious time and money. One facility cut manual work and delays by 70%, saving over 250 minutes per batch of routine samples. They could put staff on higher-value work, too. 5 Another site dropped non-essential manual steps by 43%. 6

• Turnaround times you can trust: By preventing errors that would otherwise slow things down, and smart routing that prioritizes urgent samples, labs deliver results quickly and reliably. Take a UK hospital that saw a 91% drop in the variation of urgent sample turnaround times — clinicians could finally count on consistent, predictable results. 3

• Smarter, data-driven improvements: Every tube gets a full, traceable history thanks to intelligent middleware. These data help labs find the real causes of pre-analytical issues and tighten up their processes, making the whole operation safer and more effective.4

No compromises: The future’s already here

With advanced automation and integrated informatics, Advantaged Workflows are rewriting the rulebook for diagnostic labs. This isn’t just about faster logistics — it is about building intelligence and vigilance into every step, especially the tricky pre-analytical phase. By checking each

sample thoroughly before it even joins the main transport line, these systems cut out workflow bottlenecks and make sure only the right samples move forward, keeping everything running efficiently and reliably.

Labs that stay ahead of errors, deliver trustworthy results fast, and put patient safety first cement their place as essential partners in modern healthcare. That is what “care without compromise” looks like, and it is what I’m committed to delivering — helping power the moments that matter most for patients.

REFERENCES

1. Plebani M, Sciacovelli L, Aita A, Pelloso M, Chiozza ML. Performance criteria and quality indicators for the pre-analytical phase. Clin Chem Lab Med. 2015;53(6):943-8. doi:10.1515/cclm-2014-1124.

2. Bodley T, Chan M, Clarfield L, et al. Patient harm from repetitive blood draws and blood waste in the ICU: A retrospective cohort study. Blood 2019;134(Supplement_1):57-57. doi:10.1182/blood-2019-127394.

3. Beckman Coulter, Inc. Advancing Patient Healthcare in Worcestershire: One-Year Impact of DxA 5000 Track Installation. 2025. Available upon request.

4. Lippi G, Chance JJ, Church S, et al. Preanalytical quality improvement: From dream to reality. Clin Chem Lab Med. 2011;49(7):1113-26. doi:10.1515/CCLM.2011.600.

5. Beckman Coulter, Inc. Case Study: En Chu Kong Hospital, Taiwan. Maximizing Return on Investment With Future-Proof Laboratory Automation Solutions. 2025. Available upon request.

6. Beckman Coulter, Inc. Case Study at Bethesda North Hospital. Breaking Status Quo: Continuing Success With Advanced Laboratory Automation. 2022. Available upon request.

Thomas Coulson a Senior Global Product marketing manager at Beckman Coulter, specializes in Workflow and it Solutions (W i t S) within diagnostics. Leveraging his extensive experience in product marketing and strategic planning and drawing on his background as a Biomedical Scientist, he is passionate about developing and delivering innovative solutions that enhance laboratory efficiency and ultimately improve patient care. He always aims to make a real difference for both laboratories and patients.

CDC certified with defined pediatric expected values

t he Vitamin d to tal a s say from s iemens Healthineers is the only cdc certified method with defined pediatric expected values. With defined pediatric reference ranges for the a t ellica im and ad V i a c entaur Vitamin d to tal assays, ranges can be easily adopted with a simple in-lab validation*.

* re fer to c L s i EP28- a 3 c for recommendations on establishing and verifying referenceranges

Siemens Healthineers

Comprehensive QC for vitamin D testing

t he acusera immunoassay Premium Plus control provides third - party assessment for 54 analytes. including 1-25 - (oH) 2 Vitamin d and 25 - oH Vitamin d, alongside routinely run tumor markers, hormones, and more in a lyophilized, human serum matrix.

Randox

Phosphorus-SL for vitamin D monitoring

s E K isui ’s Phosphorus assay is intended for the in vitro quantitative measurement of inorganic phosphorus in serum. increased phosphorus concentrations (hyperphosphatemia) are usually the result of Vitamin d overdose, hypoparathyroidism, or renal failure. decreased serum concentrations (hypophosphatemia) usually result from rickets, hyperparathyroidism, or Fanconi s y ndrome.

SEKISUI Diagnostics

Proficiency testing program for vitamin D

c linical laboratories can ensure testing accuracy with W s L H P t ’ s Vitamin d proficiency testing program. t his program is included in the immunoassay c hemistry B panel, provided in staggered shipments of lyophilized serum samples. For more details, refer to P t 0 1712 on page 17 of the 2026 c linical P t c a talog: wslhpt.org.

WSLH Proficiency Testing

Vitamin D assay quality control

Automated and comprehensive 25 VitDs measurement

t he ids 25 Vit ds assay (is -2500 n) quantitively measures total 25-hydroxyvitamin d [25(oH) d] in human serum and plasma on the ids s y stem, with co-specificity for 25(oH) d 3 and 25(oH) d 2 i t is standardized to the id - L c ms / m s re ference Procedure. s t able, readyto-use human serum calibrators (is -2520 n) and controls (is -2530 n) are also available.

Euroimmun (part of Revvity)

c omplete d 25- oH V itamin d c ontrol is a liquid, ready-to-use quality control material for monitoring clinical assays measuring total 25-hydroxyvitamin d Prepared in a human serum matrix with 25- oH v itamin d 2 and d 3 , it represents clinically relevant concentrations and is suitable for daily quality control and comparison between test systems. Quantimetrix

LABORATORY INNOVATOR

Brittany Teeter, MS, CLS, MLS(ASCP)CM is an Assistant Professor of Medical Laboratory Sciences at The University of Texas Health Science Center at San Antonio and an experienced clinical laboratory professional with a career spanning bench practice, laboratory management, quality and compliance, and academic instruction. Her professional background includes leadership roles in hospital and health system laboratories, where she supported regulatory compliance, quality management programs, operational oversight, and workforce development.

She currently serves in multiple national leadership roles within the American Society for Clinical Pathology (ASCP), including President-Elect of the Texas Riverwalk Chapter, Chair of the ASCP Board of Certification Committee, and Chair of the Clinical Laboratory Management and Administration (CLMA), along with additional committee and advisory appointments. Through these roles, she contributes to professional standards, certification processes, and leadership initiatives that support laboratory operations and patient safety.

Brittany’s teaching, scholarship, and service interests center on laboratory quality systems, leadership skill development, compliance education, workforce engagement, and innovative instructional strategies. She is particularly interested in applied learning, gamification, and tools that enhance team performance and professional identity formation. Brittany is currently a PhD candidate in Health Sciences and is recognized for her contributions to leadership education and quality-focused practice in the clinical laboratory profession.

Leadership is a skillset: Brittany Teeter’s vision

By Christina Wichmann

Please describe your path from a laboratory professional to professor. How have your leadership experiences influenced your perspective on the role of emerging leaders in lab medicine?

My path from the bench to the classroom was driven by a strong interest in mentorship, quality improvement, and workforce development. Early in my clinical career, I was frequently asked to take on informal leadership roles—training new staff, supporting competency assessments, and contributing to quality and compliance initiatives. Those experiences made it clear that leadership in laboratory medicine does not begin with a title, but with accountability, communication, and advocacy for best practice. As a professor, I now see emerging leaders as individuals who must be developed intentionally and early, with exposure to decision-making, systems thinking, and professional identity formation alongside technical expertise.

You’ve taken on leadership roles relatively early in your career. What mindset or skill set do you believe is most essential for laboratory professionals who want to lead in their organizations?

The most essential mindset is viewing leadership as service rather than authority. Strong laboratory leaders are adaptable, data-driven, and willing to step into uncertainty while maintaining patient-centered priorities. Equally important are communication skills—being able to translate technical information to diverse stakeholders, manage conflict, and build trust across teams. Early career professionals who invest in self-awareness, continuous learning, and systems-level thinking are often best positioned to lead effectively, regardless of formal title.

You were part of a team that created the board game, “Escape the Lab.” Please tell us about it! Escape the Lab was developed as a gamified tool based on an ASCP job aid tool

(https://www.supportcdconelab.org/ aligning-lab-team-resources/) created to help laboratory professionals identify where they best fit within the lab based on individual traits such as being introverted, extroverted, analytical, or detail-oriented. The game focuses on aligning strengths with roles, allowing teams to see how different personalities contribute to laboratory operations, problem-solving, and quality outcomes. Through interactive challenges, participants engage in strengths-based collaboration while navigating realistic lab scenarios. The instruction guide outlines gameplay, lab roles, and how teams “match the strengths and solve the crisis” in order to Escape the Lab.

What trends in laboratory training do you believe will be most critical over the next 5–10 years?

Over the next decade, laboratory training must place greater emphasis on leadership development, informatics, and adaptability. While technical competence remains essential, laboratories increasingly need professionals who understand quality systems, data analytics, regulatory environments, and interdisciplinary collaboration. Experiential learning, simulation, and case-based instruction will continue to grow in importance, as will training that prepares professionals to navigate workforce shortages, automation, and evolving scopes of practice. Intentional succession planning and leadership pipelines will be critical for sustainability.

What advice do you give to early career laboratory professionals?

My advice is to be proactive in shaping your career. Seek mentors and find opportunities that suit the developmental stage you are at now. Build a strong foundation in quality, communication, and professionalism early on. Most importantly, remember that laboratory medicine is a people-centered p rofession—technical skill matters, but your ability to collaborate, teach, and advocate will define your longterm impact.

Alinity i TBI

ENHANCE HEAD TRAUMA CARE IN EMERGENCY DEPARTMENTS WITH A SIMPLE LAB TEST.

DID YOU KNOW...

•Most traumatic brain injuries (TBIs) that occur each year are mild TBIs (also called concussions).1

•Overuse of CT imaging increases costs, length of stay (LOS), and ED crowding.2

•Abbott’s TBI blood-based biomarker test (serum and plasma) aids in evaluating suspected mild traumatic brain injury in people 18 and older within 12 hours of injury and can help rule out the need for a CT scan.3

ALINITY i TBI TEST PATHWAY

Patient presents to the ED with suspected mTBI

Blood sample collected within 12 hours of injury

Serum or plasma sample prepared, test run

Biomarker level read out within 18 minutes

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For In Vitro Diagnostic Use

1 Centers for Disease Control and Prevention. About traumatic brain injury. https://www.cdc.gov/traumatic-brain-injury/about/index.html. Accessed Sept. 12, 2025.

2 Mills CM, Roberts N, Fritsche K, Merideth D, Babic N. Clinical evaluation of the TBI assay in a representative emergency department cohort. J Appl Lab Med. Published online October 22, 2025. doi:10.1093/jalm/jfaf159

3 Alinity i TBI IFU 802673R01. Abbott Diagnostics. May 2023.

©2026 Abbott. All rights reserved. All trademarks referenced are trademarks of either the Abbott group of companies or their respective owners.

Test result delivered to physician for further evaluation