Timeliness “at a glance”: assessing the turnaround time through the six sigma metrics

Evaluation of Laboratory Performance, Associated Factors and Staff Awareness Towards Achieving Turnaround Time in Tertiary Hospitals, Ethiopia

Background

WHO recommends that each laboratory should establish turnaround time (TAT) to monitor and evaluate performance throughout processes. The status of established TAT was not yet assessed in Ethiopian Armed Force Comprehensive Specialized Hospital. The aim of this study was to evaluate the laboratory performance and associated factors towards achieving TAT in clinical chemistry and hematology tests at Armed Force Comprehensive Specialized Hospital, Addis Ababa, Ethiopia.

Methods

Hospital-based cross-sectional study was conducted from April 2019 to June 2019. Standardized questionnaire was designed to collected data on awareness of laboratory staffs about TAT. The data was entered, cleaned and analyzed using SPSS version 24.0 Software. Logistic regression analysis was done to find out statistically significant association and strength of association between dependent and independent variables at pvalue <0.05.

Result

A total of 422 test results were systematically selected with 100% response rates. Of these, 253(59.9%) were chemistry tests. From the expected < 90min TAT clinical chemistry tests, only 41(16.2%) and from < 60min TAT time for hematology tests, 37(21.9%) met the target. The laboratory TAT was affected by factors including high work load, laboratory information system problem, power interruption and sample collection time. Moreover, the level of knowledge, attitude and practices of laboratory staffs towards laboratory TAT were 60%, 85.7% and 62.9% respectively.

Conclusion

Overall achievement of clinical Chemistry and hematology tests TAT was poor. The finding might reflect other public hospital situation in Addis Ababa. Thus, additional large scale studies need to conduct.

Confidence interval of percentiles in skewed distribution: The importance of the actual coverage probability in practical quality applications for laboratory medicine

Introduction

Quality indicators (QI) based on percentiles are widely used for managing quality in laboratory medicine nowadays. Due to their statistical nature, their estimation is affected by sampling so they should be always presented together with the confidence interval (CI). Since no methodological recommendation has been issued to date, our aim was investigating the suitability of the parametric method (LP-CI), the non-parametric binomial (NP-CI) and bootstrap (BCa-CI) procedures for the CI estimation of 2.5^th, 25^th, 50^th, 75^th and 97.5^th percentile in skewed sets of data.

Materials and methods

Skewness was reproduced by numeric simulation of a lognormal distribution in order to have samples with different right-tailing (moderate, heavy and very heavy) and size (20, 60 and 120). Performance was assessed with respect to the actual coverage probability (ACP, accuracy) against the confidence level of 1-α with α = 0.5, and the median interval length (MIL, precision).

Results

The parametric method was accurate for sample size N ≥ 20 whereas both NP-CI and BCa-CI required N ≥ 60. However, for extreme percentiles of heavily right-tailed data, the required sample size increased to 60 and 120 units respectively. A case study also demonstrated the possibility to estimate the ACP from a single sample of real-life laboratory data.

Conclusions

No method should be applied blindly to the estimation of CI, especially in small-sized and skewed samples. To this end, the accuracy of the method should be investigated through a numeric simulation that reproduces the same conditions of the real-life sample.

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.