Pre-analytical issues are the top source of lab errors, resulting in up to 70% of diagnostic errors.1
This is especially true for coagulation testing, where pre-analytical variables can create significant differences in values. If a laboratory does not address these variables, it can lead to misdiagnosis, improper dosing or incorrect treatments.
To avoid these consequences, laboratories must follow guidelines and best practices to optimize coagulation testing, including those from reagent and instrument manufacturers.2 Three strategies that labs can use to improve coagulation testing include:
- Prevention of pre-analytical errors
- Quality control activities
- Clinical decision support.
Pre-analytical considerations
For pre-analytical testing, labs should standardize procedures for five stages: patient variables, sample collection, sample transport, sample processing and storage, and sample testing.
They should assess patient variables that can affect coagulation testing, as well as disease states associated with coagulopathy and any health issues that can affect hemostasis testing outcomes.
They must establish testing standards, particularly for test timing. Organizational standards are needed for sample collection variables, including needle size, sample mixing procedures and preferred anticoagulant. Additionally, double identifiers for patients and standards for printing tube labels can help avoid errors in sample and patient identification.
To ensure the integrity of samples during transport, labs should set standards for timing, temperature and vibration management, as well as guidelines for sample storage, refrigeration, thawing, addressing handling errors, validation protocols and any exceptions to the most frequently used standards.
Finally, they should establish criteria for sample acceptance, which can be done manually or with newer automated coagulation analyzers for a standardized process.
Quality control
Quality control activities that promote standardization of analytical techniques, reagents and instrumentation are helping improve lab outcomes. These activities should include internal quality control and external quality assurance.
Internal quality control will ensure assay performance meets specifications and results are reliable and accurate. If results are outside of an accepted range, labs can use standard rules, such as the Westgard Rules, to determine whether instrument or assay troubleshooting is needed. Labs should also monitor variations between reagent lots, as they can indicate the need for assay recalibration.
External quality assurance allows labs to compare their performance with other labs using the same or different reagents and instruments. After an assessment, they must investigate, address and document any analytes outside of defined allowable limits.
Clinical decision support
The third strategy, clinical decision support, uses digitized data from EHRs and other sources, along with clinical guidelines, to make laboratory workflows more efficient, reduce unnecessary testing, optimize staffing and lower costs. For coagulation testing, three key CDS interventions relate to ordering, education and diagnostics.
CDS technology uses order search menus, templates and instructions, order sets, order reflexes and cascades, and alerts to promote appropriate ordering. Predictive analytics help guide clinicians to evidence-based test orders, with 98% of providers reporting the interpretations as “useful or informative.”3
Education can also guide clinician ordering behaviors and provide them with information about what their peers are doing. CDS-based education can include infobuttons that display clinical guidelines and test information at the point of care, reducing errors on coagulation testing orders.4
Meanwhile, new diagnostic capabilities that include decision algorithms and artificial intelligence can support advance order logic and predictive analytics.
High demand for coagulation testing has underscored the need for CDS to help clinicians improve ordering and prevent errors through alerts and educational support, and for modern coagulation analyzers to help laboratories automate and standardize the specimen review to flag unsatisfactory pre-analytical conditions.
By applying these strategies to improve coagulation testing, lab managers can increase accuracy, speed and quality while streamlining operations and lowering costs. Those that embrace these strategies can see quantifiable improvements in coagulation testing while also improving provider and patient satisfaction.
References
- Lippi G., Blanckaert N., Bonini P., Green S., Kitchen S., Palicka V., et. al. Haemolysis: An Overview of the Leading Cause of Unsuitable Specimens in Clinical Laboratories. Clin Chem Lab Med. 2008;46:764-72. https://doi.org/10.1515/CCLM.2008.170.
- Gosselin, R., Marlar, R. Pre-analytical Variables In Routine Coagulation Testing: Setting the Stage for Accurate Results. Seminars in Thrombosis and Hemostasis. July 10, 2019. https://pubmed.ncbi.nlm.nih.gov/31291676/
- Three strategies to improve your coagulation testing. Siemens Healthineers. September 2023. https://www.siemens-healthineers.com/en-us/hemostasis/coagulation-testing
- Jackups, R. Jr., Szymanski, J.J., Persaud, S.P. Clinical Decision Support for Hematology Laboratory Test Utilization. Int J Lab Hem. 2017:39 (Suppl.1): 128-135. https://pubmed.ncbi.nlm.nih.gov/28447421/