Analysis of Turnaround Times in Pathology

Evaluation of Turnaround Times of Diagnostic Biopsies: A Metric of Quality in Surgical Pathology

Introduction. Timely and accurate diagnosis of diseases is crucial for effective patient care. Turnaround time (TAT) in surgical pathology, defined as the time between accessioning the sample and reporting results, is a key performance indicator reflecting quality and efficiency. This study explores factors affecting TAT for diagnostic biopsies in a tertiary oncology hospital. Methods. A 1-month pilot study was conducted, focusing on 695 in-house diagnostic biopsies. Biopsies were categorized as routine (requiring only hematoxylin and eosin (H&E) staining) or complex cases (requiring additional tests). TAT was defined as the time between sample accessioning and report availability in the electronic medical record, with delays defined as exceeding 3 days for routine cases and 4 days for complex cases. Survival analysis using Kaplan-Meier plots was utilized to analyze TAT. Results. The overall mean TAT was 3.7 ± 2 days, with routine cases at 3.1 ± 2 days and complex cases at 4.8 ± 2 days (P < 0.001). Survival analysis revealed prolonged TAT for complex cases. Organ-specific analysis highlighted variations in TAT, with brain biopsies presenting the highest complexity and longest TAT. Surprisingly, malignant cases demonstrated slightly shorter TATs compared to benign cases (P = 0.026). Delays were observed in 34% of all cases. Conclusions. Laboratory TAT is crucial and is frequently used as a performance benchmark. We analyzed the various causes of delayed TAT in our hospital's histopathology department, with an emphasis on variables in the analytical phase. The results of this study demonstrate that cases involving ancillary techniques had significantly longer TATs compared to routine H&E cases.

Turnaround Time: An Efficacy Measure for Medical Laboratories

Turnaround time (TAT), which doctors frequently use as the benchmark for laboratory performance, is a typical way to communicate timeliness. It also acts as a quality indicator to evaluate the effectiveness and efficiency of the testing process and the satisfaction of clinicians and patients. TAT is the time from receipt of the sample in the laboratory to final delivery or dispatch of the report of said test. The TAT procedure can be broadly divided into three stages pre-analytical, analytical and post-analytical. There is variability in TAT according to different conditions like the volume of sample size, staff expertise, availability of adequate resources, distances of the hospital from the lab, and various sub-departments. To remove obstacles to optimizing TAT, we must take a practical approach. A workload reduction plan, proper stock management, specialized work assignments, and skilled staff retention are crucial strategies to reduce the setting's delayed TAT.

Validation of the Six Sigma Z-score for the quality assessment of clinical laboratory timeliness

BACKGROUND

The International Federation of Clinical Chemistry and Laboratory Medicine has introduced in recent times the turnaround time (TAT) as mandatory quality indicator for the postanalytical phase. Classic TAT indicators, namely, average, median, 90th percentile and proportion of acceptable test (PAT), are in use since almost 40 years and to date represent the mainstay for gauging the laboratory timeliness. In this study, we investigated the performance of the Six Sigma Z-score, which was previously introduced as a device for the quantitative assessment of timeliness.

METHODS

A numerical simulation was obtained modeling the actual TAT data set using the log-logistic probability density function. Five thousand replicates for each size of the artificial TAT random sample (n=20, 50, 250 and 1000) were generated, and different laboratory conditions were simulated manipulating the PDF in order to generate more or less variable data. The Z-score and the classic TAT indicators were assessed for precision (%CV), robustness toward right-tailing (precision at different sample variability), sensitivity and specificity.

RESULTS

Z-score showed sensitivity and specificity comparable to PAT (≈80% with n≥250), but superior precision that ranged within 20% by moderately small sized samples (n≥50); furthermore, Z-score was less affected by the value of the cutoff used for setting the acceptable TAT, as well as by the sample variability that reflected into the magnitude of right-tailing.

CONCLUSIONS

The Z-score was a valid indicator of laboratory timeliness and a suitable device to improve as well as to maintain the achieved quality level.