Context.— Many production systems employ standardized statistical monitors that measure defect rates and cycle times, as indices of performance quality. Clinical laboratory testing, a system that p...

Seven Q-Tracks monitors of laboratory quality drive general performance improvement: experience from the College of American Pathologists Q-Tracks program 1999-2011.

Diagnostic laboratories in Asia Pacific region: Investigation on quality characteristics and time of reporting

This is the result of a Survey of diagnostics laboratories in the Asia Pacific (APAC) region with perspectives on India, investigating the three key aspects that are central to the success of a laboratory: quality, cost and speed. This Survey provides a comparison in selected performance indicators in a large number of diagnostic laboratories in a broad range of countries in the APAC region. The Survey provides data on some key performance characteristics such as quality improvement activities, staff productivity and Turnaround Time (TAT). This Survey also demonstrates in India the common issues facing all the laboratories surveyed but also common solutions using a Quality Systems approach which involves Accreditation, customer responsiveness, greater use of IT, automation and Lean principles. Indian laboratories reported less automation and fewer laboratories have Laboratory Information Systems. The productivity by various measures in Indian laboratories was less than in other APAC laboratories. TAT was more commonly monitored in the Indian specimens though there were fewer laboratories compared with the APAC specimens where there were separate TATs for Short Turnaround Time and Routine specimens.

Diagnostic Laboratories in India: Investigating Quality Characteristics, Productivity and Time of Reporting.

Background: Specimen turnaround time (TAT) is an important metric for laboratory safety and quality. Various methods to improve TAT have seen success using process improvement initiatives. However, there are limited data on barcoding, pneumatic receiving proximity to modular preanalytics, 1 vs 2 measuring cells, and upgrading to Cobas 8000. The example describes the complete execution of a process improvement initiative to improve TAT within these areas over a 20-month period. The study aimed to improve specimen timeliness by decreasing the TAT for preanalytic and analytic specimen processing through a systematic process improvement initiative and to empower staff to “own” their scientific method. Methods: The primary outcome TAT was reported from a prospective quality initiative beginning January 2017 for 2 analytes: troponin and potassium. TATs for albumins from the complete metabolic panels were added to the study design retrospectively during team rounds. Mean TAT was defined as time from arrival to verified times. Process improvement tools within the study design were borrowed from Lean management. Results: After implementation of the process improvement initiative, the number of steps medical laboratory assistants and technologists performed per specimen decreased from 8 to 5. Mean TATs decreased for all analytes. Preimplementation to postimplementation comparisons from 2017 to 2018 decreased for all 3 analytes and within 2017. The number of troponin specimens verified within 60 min improved from 70% in January 2017 to 95% in August 2018, with an improvement from 64% in January 2017 to 87% in August 2018 during peak hours. Conclusions: A systematic process improvement initiative whereby employees “own” the scientific process within specimen preanalytic and analytic testing phases can significantly improve metrics for laboratory quality and safety.

Improving Turnaround Times through a Process Improvement Initiative Involving Barcoding, Floorplans, Dual Measuring Cells, Chemistry Analyzers, and Staff Shifts.

Background Evidence-based evaluation of laboratory performances including pre-analytical, analytical and post-analytical stages of the total testing process (TTP) is crucial to ensure patients receiving safe, efficient and effective care. To conduct risk assessment, quality management tools such as Failure Mode and Effect Analysis (FMEA) and the Failure Reporting and Corrective Action System (FRACAS) were constantly used for proactive or reactive analysis, respectively. However, FMEA and FRACAS faced big challenges in determining the scoring scales and failure prioritization in the assessment of real-world cases. Here, we developed a novel strategy, by incorporating Sigma metrics into risk assessment based on quality indicators (QIs) data, to provide a more objective assessment of risks in TTP. Methods QI data was collected for 1 year and FRACAS was applied to produce the risk rating based on three variables: (1) Sigma metrics for the frequency of defects; (2) possible consequence; (3) detection method. The risk priority number (RPN) of each QI was calculated by a 5-point scale score, where a value of RPN > 50 was rated as high-risk. Results The RPNs of two QIs in post-analytical phase (TAT of Stat biochemistry analyte and Timely critical values notification) were above 50 which required rigorous monitoring and corrective actions to eliminate the high risks. Nine QIs (RPNs between 25 and 50) required further investigation and monitoring. After 3 months of corrective action the two identified high-risk processes were successfully reduced. Conclusions The strategy can be implemented to reduce identified risk and assuring patient safety.

Risk assessment of the total testing process based on quality indicators with the Sigma metrics.

Context.—The Q-Tracks program, created in 1999, is a quality monitoring subscription service offered by the College of American Pathologists. Objective.—To establish benchmarks in quality metrics, ...

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Fifteen years' experience of a College of American Pathologists program for continuous monitoring and improvement.

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Fifteen years' experience of a College of American Pathologists program for continuous monitoring and improvement.