By Amari Henderson, MBA, MLS (ASCP)

Imagine you’re reviewing the morning laboratory results when one patient’s potassium immediately catches your attention. Yesterday, their potassium was 4.1 mmol/L. Today, it’s 7.0 mmol/L. Your first thought probably isn’t to report the result right away. You wonder if the patient suddenly developed severe hyperkalemia overnight. Was the specimen mislabeled? Could the sample be hemolyzed? Was there an issue during collection? Situations like this are exactly why delta checks were created. Before laboratory results are released to healthcare providers, clinical laboratories use verification tools to determine whether an unexpected change deserves a closer look.

A delta check is defined as a post-analytical verification tool used to compare the difference between a patient’s current and previous laboratory results against a predefined limit. This patient-specific quality tool helps identify potential errors at the individual patient level. If the difference exceeds the laboratory’s established threshold, the result is flagged for review before it is reported.

The concept of delta checks was first introduced by Dr. Donald A.B. Lindberg in 1967 as laboratory computer systems and informatics began to evolve. By 1974, delta checks had become an established patient-based quality control tool and have remained an important safeguard for detecting potential errors before results are reported. Today, most laboratory information systems (LIS) and autoverification workflows incorporate delta check rules to automatically identify results that may require additional investigation before they are released.

Not only are delta checks associated with specimen misidentification, they also help identify specimen integrity issues such as intravenous (IV) fluid contamination, incorrect collection tubes, or delayed specimen processing. Selecting effective delta check rules has become more important for maintaining patient safety as well as operational efficiency.

Delta checks are based on the simple fact that most lab values do not change dramatically over a short period of time unless there is a biological or clinical reason. The concept of homeostasis proves that the body strives to maintain a stable internal environment. This is why many analytes remain stable within the same individual from day to day.

One of the main scientific concepts behind delta checks is biological variation. The CLSI EP33 guideline describes biological variation as having two components. Within-subject biological variation (CVI) represents the normal day-to-day fluctuations around an individual’s typical laboratory value. Between-subject biological variation (CVG) refers to the normal differences in laboratory values between different people. This explains why two healthy patients may have different baseline creatinine values while each person’s creatinine remains relatively stable over time.

Analytes with low within-subject biological variation are excellent candidates for delta checks because changes are easier to recognize. According to the CLSI EP33 guideline, the most effective delta check analytes are also ordered frequently. Frequent testing allows for meaningful comparisons between current and previous results. Hemoglobin, hematocrit, sodium, potassium, platelet count, and white blood cell count are all examples of analytes that are perfect for delta checks.

Every laboratory serves a different patient population and uses different instrumentation, workflows, and testing practices. This is why delta check limits should be established using the laboratory’s own patient data whenever possible rather than relying solely on published recommendations. Laboratories are encouraged to periodically review and change their delta check rules to improve error detection while minimizing unnecessary investigations. Thresholds that work well in one hospital could lead to excessive false alerts in another hospital or patient population.

A failed delta check does not automatically mean a laboratory error has occurred. It just means that the result deserves a closer look. Laboratory professionals should review previous patient results, patient history, specimen integrity, collection information, instrument quality controls, and instrument flags. Only after this investigation is complete can the laboratory determine whether the result reflects a true clinical change or whether additional action is necessary.

Delta checks are far more than just a comparison between two results. They combine biological variation, analytical performance, laboratory quality management, and clinical judgment into one patient safety tool. Delta checks provide laboratories with an additional layer of quality assurance before results are reported. More than 50 years later, delta checks remain one of the most effective patient-based quality tools for helping laboratories detect potential errors, improve result accuracy, and protect patients.

Sources

Asirvatham JR, Moses V, Bjornson L. Errors in potassium measurement: a laboratory perspective for the clinician. N Am J Med Sci. 2013 Apr;5(4):255-9. doi: 10.4103/1947-2714.110426. PMID: 23724399; PMCID: PMC3662091.

Clinical and Laboratory Standards Institute (CLSI). Use of Delta Checks in the Medical Laboratory; Approved Guideline, 2nd ed. CLSI document EP33. Wayne: CLSI; 2023.

Markus, C., Tan, R. Z., & Loh, T. P. (2021). Evidence-based approach to setting delta check rules. Critical Reviews in Clinical Laboratory Sciences, 58(1), 49–59. https://doi.org/10.1080/10408363.2020.1800585

Straseski, J. A. (n.d.). The delta check in action: Causes and consequences of discrepant laboratory results. ARUP Laboratories. https://arup.utah.edu/education/deltaChecks.php/

Yenice, S. (2017, October 22). Use of delta checks: A requisite method in quality control [Conference presentation]. Satellite Educational Workshop on Intelligent Clinical Laboratory Management: Impacts on Quality System Improvement, Durban, South Africa. International Federation of Clinical Chemistry and Laboratory Medicine (IFCC)