Differential application of rate and delta check on selected clinical chemistry tests

Delta checks

Delta check is an electronic error detection tool. It compares the difference in sequential results within a patient against a predefined limit, and when exceeded, the delta check rule is considered triggered. The patient results should be withheld for review and troubleshooting before releasing to the clinical team for patient management. Delta check was initially developed as a tool to detect wrong-blood-in-tube (sample misidentification) errors. It is now applied to detect errors more broadly within the total testing process. Recent advancements in the theoretical understanding of delta check has allowed for more precise application of this tool to achieve the desired clinical performance and operational set up. In this Chapter, we review the different pre-implementation considerations, the foundation concepts of delta check, the process of setting up key delta check parameters, performance verification and troubleshooting of a delta check flag.

Application and optimization of reference change values for Delta Checks in clinical laboratory

BACKGROUND

Delta check is a patient-based QC tool for detecting errors by comparing current and previous test results of patient. Reference change value (RCV) is adopted in guidelines as method for delta check, but the performance is not verified. We applied RCV-based delta check method to patients' data and modified for application.

MATERIALS AND METHODS

Reference change value were calculated using results of internal QC materials and biological variation data. Test results of 17 analytes in inpatients, outpatients, and health examination recipients were collected. The detection rates of currently used delta check method and those of RCV-based method were compared, and the methods were modified.

RESULTS

Reference change value-based method had higher detection rates compared to conventional method. Applied modifications reduced detection rates. Removing the pairs of results within reference interval reduced detection rates (0.42% ~ 10.92%). When RCV was divided by time interval, the detection rates were similar to prior rates in outpatients (0.19% ~ 1.34%). Using RCV multiplied by twice the upper limit of reference value as cutoff reduced the detection rate (0.07% ~ 1.58%).

CONCLUSIONS

Reference change value is a robust criterion for delta check and included in clinical laboratory practice guideline. However, RCV-based method generates high detection rates which increase workload. It needs modification for use in clinical laboratories.

National survey on delta checks in clinical laboratories in China

Background

This study aimed to understand the status quo of delta checks in Chinese clinical laboratories through a nationwide online survey.

Methods

The survey was divided into two parts. The first part was a general situation survey in which clinical laboratories had to provide information about the laboratories, including delta checks used. In the second part, clinical laboratories were asked to record the delta check alerts generated in their laboratories from June 1st, 2019 to June 30th, 2019.

Results

The most frequently used analytes in delta checks were potassium (K), glucose (Glu), creatinine (Cre) for clinical chemistry and hemoglobin (Hgb), platelet (PLT) count and white blood cell (WBC) count for clinical hematology. The median maximum time interval between specimens for all analytes was 5 days. The most commonly used delta check calculation modes in Chinese clinical laboratories were percentage change and absolute change. K and Hgb were the analytes most involved in clinical chemistry and clinical hematology delta check alerts. The most common causes of delta check alerts were that the patients had received treatment, which was followed by the change in the patient’s physiological state and interference from hemolysis, lipemia and icterus. The two most common outcomes of delta check alerts were ‘no problems found, standard report issued’ and ‘no problems found, report issued with comment’.

Conclusions

This study was the first nationwide survey of delta checks in China, the results of which help us to understand the current situation of delta checks in Chinese clinical laboratories.

Post-analytical laboratory work: national recommendations from the Working Group for Post-analytics on behalf of the Croatian Society of Medical Biochemistry and Laboratory Medicine

The post-analytical phase is the final phase of the total testing process and involves evaluation of laboratory test results; release of test results in a timely manner to appropriate individuals, particularly critical results; and modification, annotation or revocation of results as necessary to support clinical decision-making. Here we present a series of recommendations for post-analytical best practices, tailored to medical biochemistry laboratories in Croatia, which are intended to ensure alignment with national and international norms and guidelines. Implementation of the national recommendations is illustrated through several examples.

Establishing and Evaluating Autoverification Rules with Intelligent Guidelines for Arterial Blood Gas Analysis in a Clinical Laboratory

Arterial blood gas (ABG) analysis is important for acutely ill patients and should be performed by qualified laboratorians. The existing manual verifications are tedious, time-consuming, and prone to send wrong reports. Autoverification uses computer-based rules to verify clinical laboratory test results without manual review. To date, no data are available on the use of autoverification for ABG analysis. All autoverification rules were established according to AUTO10-A. Additionally, the rules were established using retrospective patient data, and then validated by actual clinical samples in a "live" environment before go-live. The average autoverification passing rate was 75.5%. The turnaround time (TAT) was reduced by 33.3% (27 min vs 18 min). Moreover, the error rate fell to 0.05% after implementation. Statistical analysis resulted in a kappa statistic of 0.92 ( p < 0.01), indicating close agreement between autoverification and senior technician verification, and the chi-square value was 22.4 ( p < 0.01), indicating that the autoverification error rate was lower than the manual verification error rate. Results showed that implementing autoverification rules with intelligent guidelines for ABG analysis of patients with critical illnesses could decrease the number of samples requiring manual verification, reduce TAT, and eliminate errors, allowing laboratorians to concentrate more time on abnormal samples, patient care, and collaboration with physicians.

Delta Check Practices and Outcomes: A Q-Probes Study Involving 49 Health Care Facilities and 6541 Delta Check Alerts

Context.—

Delta checks serve as a patient-based quality control tool to detect testing problems.

Objective.—

To evaluate delta check practices and outcomes.

Design.—

Q-Probes participants provided information about delta check policies and procedures. Information about investigations, problems, and corrective actions was prospectively collected for up to 100 testing episodes involving delta check alerts.

Results.—

Among 4505 testing episodes involving 6541 delta check alerts, the median frequencies of actions taken among 49 laboratories were clinical review, 38.0%; retest, 25.0%, or recheck, 20.2%; current specimen, nothing, 15.4%; analytical check, 5.0%; other; 2%; and retest or check previous specimen, 0%. Rates of any action taken by analyte ranged from 84 of 179 (46.9%) for glucose to 748 of 868 (86.2%) for hemoglobin and potassium. Among 4505 testing episodes, nontesting problems included physiologic causes (1472; 32.7%); treatment causes (1318; 19.2%); and transfusion causes (846; 9.9%). Testing problems included 77 interference (1.7%), 62 contamination (1.4%), 51 clotting (1.1%), 27 other (0.6%), 12 mislabeling (0.3%), and 5 analytical (0.1%). Testing problems by analyte ranged from 13 of 457 (2.8%) for blood urea nitrogen to 12 of 46 (26.1%) for mean corpuscular hemoglobin concentration. Using more delta check analytes was associated with detecting more testing problems (P = .04). More delta check alerts per testing episode resulted in more actions taken (P = .001) and more problems identified (P &lt; .001). The most common outcome among 4500 testing episodes was reporting results without modifications or comments in 2512 (55.8%); results were not reported in 136 (3.0%).

Conclusions.—

Actions taken in response to delta check alerts varied widely, and most testing problems detected were preanalytical. Using a higher number of different analytes and evaluating previous specimens may improve delta check practices.

Development and Implementation of Autoverification Rules for ELISA Results of HBV Serological Markers

Autoverification is a process of using computer-based rules to verify clinical laboratory test results without manual review. But to date, there are few published articles on the use of autoverification over the course of years in a clinical laboratory. In our study, we firstly described the development and implementation of autoverification rules for enzyme-linked immunosorbent assay (ELISA) results of hepatitis B virus (HBV) serological markers in a clinical immunology laboratory. We designed the autoverification rules for HBV by using Boolean logic on five clinically used serological markers in accordance with the framework of AUTO-10A, issued by the American Clinical Laboratory Standards Institute in 2006. The rules were written into the laboratory information system (LIS) and installed in the computer, so we could use the LIS to screen the test results. If the results passed the autoverification rules, they could be sent to doctors immediately. To evaluate the autoverification rules, we applied the real-time data of 11,585 patients with the autoverification rules. The autoverification rate of the five HBV serological markers was 79.5%. Furthermore, the turnaround time (TAT) was reduced by 38% (78 minutes vs. 126 minutes). The error rate was nearly eliminated. These results show that using LIS with autoverification rules can shorten TAT, enhance efficiency, and reduce manual review errors.

Blindsided by the Monospot test

A 20-year-old man developed bilateral forearm paresthesias after propping his elbows on the desk studying. He was diagnosed with ulnar neuropraxia and instructed to follow up with a neurologist. The symptoms continued and the patient was admitted for a formal workup of his neuritis. A Monospot test was positive. The patient was discharged with a diagnosis of infectious mononucleosis. A comment on his complete blood count, showing absolute lymphocytosis with atypical lymphocytes and rare blasts with flow cytometry recommended, was missed, possibly due to the fact that it was not highlighted red on the electronic medical record indicating an abnormal result. A month later, an outpatient diagnosis of B-lymphoblastic leukemia/lymphoma was made on flow cytometry. This case highlights cognitive errors in diagnosis, including premature closure and failing to ‘see’ key data, as well as vulnerabilities created by data display limitations of the electronic medical record.

Autoverification in a core clinical chemistry laboratory at an academic medical center

Background:

Autoverification is a process of using computer-based rules to verify clinical laboratory test results without manual intervention. To date, there is little published data on the use of autoverification over the course of years in a clinical laboratory. We describe the evolution and application of autoverification in an academic medical center clinical chemistry core laboratory.

Subjects and Methods:

At the institution of the study, autoverification developed from rudimentary rules in the laboratory information system (LIS) to extensive and sophisticated rules mostly in middleware software. Rules incorporated decisions based on instrument error flags, interference indices, analytical measurement ranges (AMRs), delta checks, dilution protocols, results suggestive of compromised or contaminated specimens, and ‘absurd’ (physiologically improbable) values.

Results:

The autoverification rate for tests performed in the core clinical chemistry laboratory has increased over the course of 13 years from 40% to the current overall rate of 99.5%. A high percentage of critical values now autoverify. The highest rates of autoverification occurred with the most frequently ordered tests such as the basic metabolic panel (sodium, potassium, chloride, carbon dioxide, creatinine, blood urea nitrogen, calcium, glucose; 99.6%), albumin (99.8%), and alanine aminotransferase (99.7%). The lowest rates of autoverification occurred with some therapeutic drug levels (gentamicin, lithium, and methotrexate) and with serum free light chains (kappa/lambda), mostly due to need for offline dilution and manual filing of results. Rules also caught very rare occurrences such as plasma albumin exceeding total protein (usually indicative of an error such as short sample or bubble that evaded detection) and marked discrepancy between total bilirubin and the spectrophotometric icteric index (usually due to interference of the bilirubin assay by immunoglobulin (Ig) M monoclonal gammopathy).

Conclusions:

Our results suggest that a high rate of autoverification is possible with modern clinical chemistry analyzers. The ability to autoverify a high percentage of results increases productivity and allows clinical laboratory staff to focus attention on the small number of specimens and results that require manual review and investigation.

Patient data algorithms

As the clinical laboratory attempts to manage and mitigate risk, individual patient results can be a useful complement to routine quality-control materials. Patient results can be used to detect error or identify potential testing complications at all phases of the total testing process. Patient-specific data algorithms include delta checks, tests to verify specimen or tube type, absurdity checks, and result-based reporting. Delta checks are highlighted because they can uniquely point to issues all along the testing cycle, from preanalytical to postanalytical concerns. When used properly, patient results can work to minimize risk and increase the quality of individual patient results.

New decision criteria for selecting delta check methods based on the ratio of the delta difference to the width of the reference range can be generally applicable for each clinical chemistry test item

BACKGROUND

Many laboratories use 4 delta check methods: delta difference, delta percent change, rate difference, and rate percent change. However, guidelines regarding decision criteria for selecting delta check methods have not yet been provided. We present new decision criteria for selecting delta check methods for each clinical chemistry test item.

METHODS

We collected 811,920 and 669,750 paired (present and previous) test results for 27 clinical chemistry test items from inpatients and outpatients, respectively. We devised new decision criteria for the selection of delta check methods based on the ratio of the delta difference to the width of the reference range (DD/RR). Delta check methods based on these criteria were compared with those based on the CV% of the absolute delta difference (ADD) as well as those reported in 2 previous studies.

RESULTS

The delta check methods suggested by new decision criteria based on the DD/RR ratio corresponded well with those based on the CV% of the ADD except for only 2 items each in inpatients and outpatients. Delta check methods based on the DD/RR ratio also corresponded with those suggested in the 2 previous studies, except for 1 and 7 items in inpatients and outpatients, respectively.

CONCLUSIONS

The DD/RR method appears to yield more feasible and intuitive selection criteria and can easily explain changes in the results by reflecting both the biological variation of the test item and the clinical characteristics of patients in each laboratory. We suggest this as a measure to determine delta check methods.