Perfect Partners: Healthcare Quality and the Clinical Lab

In a bid to create an efficient, effective, resilient, and reliable healthcare system for all individuals, the Centers for Medicare & Medicaid Services (CMS) launched its National Quality Strategy in 2022. Updated in April 2024, the strategy lays out four priority areas for CMS—outcomes and alignment, equity and engagement, safety and resiliency, and interoperability and scientific advancement.¹ Within each of those areas, the organization has two primary goals and multi-point action plans for achieving them. Although attention has largely been focused on frontline clinical providers, the lab is fundamental to successfully implementing and building on the National Quality Strategy.

Priority area: promote aligned and improved health outcomes

CMS has established a “Universal Foundation” of broadly applicable, high-impact measures for evaluating healthcare quality.² These include preventive interventions such as cancer screening, long-term monitoring of chronic conditions, and follow-up care after a medical event to prevent readmissions or adverse events. The lab’s involvement also extends to specific settings—in hospitals, for example, safety add-on measures include rates of various nosocomial infections. Labs can also support better alignment by participating in the selection and evaluation of new quality measures.

High-priority outcomes are also in the crosshairs, with the Quality Improvement Organization Program and others like it aimed at areas in urgent need of improvement.³ These include chronic disease care, infection control, patient safety, and much more. The clinical lab’s role may seem minimal—but with drug screens, blood glucose monitoring, infectious disease testing, and more among the program’s potential targets, lab testing will be an integral part of tracking and driving gains in patient outcomes.

Priority area: advance equity and engagement for all individuals

One of the National Quality Strategy’s key goals is ensuring all patients have access to the right care at the right time. This includes identifying needs gaps for underserved or otherwise high-risk populations, developing education and resources to support providers in targeting those populations, incentivizing participation, and ensuring that race and ethnicity data are appropriately collected, analyzed, and interpreted. Initiatives to improve care quality might include identifying appropriate reference intervals for tests whose normal ranges vary by ethnicity⁴ (or, conversely, removing race adjustments to improve accuracy and eliminate bias⁵) or spotting patterns of delayed testing so that systemic contributors can be mitigated and barriers to care removed.⁶

Actively involving patients in their own healthcare can improve both individual outcomes and the success of quality initiatives⁷—which is why CMS aims to include patients and communities in every aspect of the process. People are invited to comment on strategy and policy, patient and family experiences are incorporated into quality measures, and quality and safety reports are made public so that patients can make more informed decisions. Patients are also increasingly gaining access to their own health data, including lab results and pathology reports,⁸ which helps them understand and participate in treatment and monitoring decisions. This can be a double-edged sword, but if lab professionals are open to explaining test results or even meeting with patients, the result can drive better health education, access, and equity for everyone.

Priority area: ensure safe and resilient healthcare systems

CMS’ primary safety goal is to eliminate all preventable harm. That means identifying potential sources of error—especially at the system level—and working toward better oversight and prevention. Most laboratory medicine errors arise during the preanalytical phase of testing and range from sample misidentification (such as labeling errors or mismatched paperwork) to specimen mishandling during storage, transport, or preparation. Analytical errors include interference (for instance, from contamination) or analytical bias arising from calibration errors. In the postanalytical phase, labs may struggle with test validation, encounter mistakes or delays in reporting, or even send results to the wrong providers. With so many opportunities for error,⁹ system-wide quality improvement measures are a crucial part of minimizing their incidence and impact.^10,11

Resiliency is a significant concern for laboratories already facing staffing shortages and resource limitations. How can labs guarantee quick turnaround times and eliminate service interruptions when they’re struggling to fill positions and retain stressed-out staff? Through its policies for material and technical assistance, CMS hopes to strengthen struggling systems and enable better care provision. The organization has also considered the implications of a growing population, a changing climate, and the risk of public health emergencies like COVID-19, creating regulations to help labs and healthcare institutions become more future-proof while ensuring that its programs can adapt to changing needs and unexpected events.

Although CMS has emergency preparedness requirements for its providers¹² and the Centers for Disease Control and Prevention offers training and network-building to improve resilience and results in the face of emergencies,¹³ many labs lack comprehensive disaster plans. Creating these plans—or updating and improving existing ones—can mean the difference between uninterrupted healthcare provision in an emergency situation and none at all.

Priority area: accelerate interoperability and scientific innovation

When patients move or change healthcare providers, their records often fail to follow them—which can create problems when establishing a patient’s history, obtaining previous baseline test results, or monitoring a chronic condition over the long term. Interoperability can help by ensuring that data gathered in one location can be stored and used in any other or even automatically forwarded to the new location. Quality measurement is also becoming increasingly digitized in hopes of simplifying data collection, reporting, and aggregation to spot patterns and potential problems.¹⁴ To support this move, CMS and its partners are developing standards for data architecture, language, format, and secure exchange of quality measures and other health information.¹⁵

Within the heavily regulated world of healthcare quality, though, it’s vital to leave space for growth. The final goal of the National Quality Strategy is to further scientific advancement by improving the data available to researchers and the public, increasing the transparency and efficiency of the coverage review process for new medical technologies, and actively engaging with advanced computing tools like artificial intelligence (AI). This is one area in which labs frequently lead the way¹⁶—and CMS encourages innovation that leverages AI to improve quality.¹⁷

Will the strategy have the desired effect on health outcomes? That remains to be seen—but establishing key measures, standards, and areas for improvement can only benefit the providers and patients affected by healthcare quality every day.

References:

1. Centers for Medicare & Medicaid Services. CMS National Quality Strategy. CMS.gov. April 5, 2024. https://www.cms.gov/medicare/quality/meaningful-measures-initiative/cms-quality-strategy.
2. Jacobs DB et al. Aligning quality measures across CMS – the Universal Foundation. N Engl J Med. 2023;388(9):776–779. doi:10.1056/NEJMp2215539.
3. Centers for Medicare & Medicaid Services. Quality Improvement Organizations. CMS.gov. May 30, 2024. https://www.cms.gov/medicare/quality/meaningful-measures-initiative/cms-quality-strategy.
4. Rappoport N et al. Comparing ethnicity-specific reference intervals for clinical laboratory tests from EHR data. J Appl Lab Med. 2018;3(3):366–377. doi:10.1373/jalm.2018.026492.
5. Umeukeje EM et al. Systematic review of international studies evaluating MDRD and CKD-EPI estimated glomerular filtration rate (eGFR) equations in Black adults. PLoS One. 2022;17(10):e0276252. doi:10.1371/journal.pone.0276252.
6. Baymon DE et al. Race, ethnicity, and delayed time to COVID-19 testing among US health care workers. JAMA Netw Open. 2024;7(4):e245697. doi:10.1001/jamanetworkopen.2024.5697.
7. Marzban S et al. Impact of patient engagement on healthcare quality: a scoping review. J Patient Exp. 2022;9:23743735221125439. doi:10.1177/23743735221125439.
8. Steitz BD et al. Perspectives of patients about immediate access to test results through an online patient portal. JAMA Netw Open. 2023;6(3):e233572. doi:10.1001/jamanetworkopen.2023.3572.
9. Plebani M. Errors in clinical laboratories or errors in laboratory medicine?. Clin Chem Lab Med. 2006;44(6):750–759. doi:10.1515/CCLM.2006.123.
10. Plebani M. The detection and prevention of errors in laboratory medicine. Ann Clin Biochem. 2010;47(Pt 2):101–110. doi:10.1258/acb.2009.009222.
11. Agarwal R. Quality-Improvement Measures as Effective Ways of Preventing Laboratory Errors. Lab Med. 2014;45(2):e80–e88. doi:10.1309/LMD0YIFPTOWZONAD.
12. Medicare and Medicaid Programs; Emergency Preparedness Requirements for Medicare and Medicaid Participating Providers and Suppliers. Federal Register. September 16, 2016. https://www.federalregister.gov/documents/2016/09/16/2016-21404/medicare-and-medicaid-programs-emergency-preparedness-requirements-for-medicare-and-medicaid.
13. Centers for Disease Control and Prevention. About CDC OneLab™. https://www.cdc.gov/labtraining/about-onelab.html.
14. eCQI Resource Center. Electronic Clinical Quality Improvement (eCQI) Resource Center. https://ecqi.healthit.gov.
15. eCQI Resource Center. Standards Summary. https://ecqi.healthit.gov/standards-summary?qt-standards=about.
16. Hou H et al. Artificial intelligence in the clinical laboratory. Clin Chim Acta. 2024;559:119724. doi:10.1016/j.cca.2024.119724.
17. Centers for Medicare & Medicaid Services. Artificial Intelligence (AI) in Quality Management. March 19, 2024. https://www.youtube.com/watch?v=oc966JKB-Gw.