Post-analytical Processes Research Articles

Reduction of multi-dimensional laboratory data to a two-dimensional plot: a novel technique for the identification of laboratory error

The clinical laboratory generates large amounts of patient-specific data. Detection of errors that arise during pre-analytical, analytical, and post-analytical processes is difficult. We performed a pilot study, utilizing a multidimensional data reduction technique, to assess the utility of this method for identifying errors in laboratory data. We evaluated 13,670 individual patient records collected over a 2-month period from hospital inpatients and outpatients. We utilized those patient records that contained a complete set of 14 different biochemical analytes. We used two-dimensional generative topographic mapping to project the 14-dimensional record to a two-dimensional space. The use of a two-dimensional generative topographic mapping technique to plot multi-analyte patient data as a two-dimensional graph allows for the rapid identification of potentially anomalous data. Although we performed a retrospective analysis, this technique has the benefit of being able to assess laboratory-generated data in real time, allowing for the rapid identification and correction of anomalous data before they are released to the physician. In addition, serial laboratory multi-analyte data for an individual patient can also be plotted as a two-dimensional plot. This tool might also be useful for assessing patient wellbeing and prognosis.

Quality in point-of-care testing: taking POC to the next level

Point-of-care testing (POCT) is a complex system with many opportunities for error. Delivering quality POCT requires multidisciplinary coordination and an understanding of the preanalytic, analytic, and postanalytic processes that are necessary to deliver a test result and take clinical action. Most errors in laboratory testing occur in the pre and postanalytical phases and many mistakes that are referred to as lab error are actually due to poor communication, actions by others involved in the testing process, or poorly designed processes outside the laboratory's control. POCT requires significant operator interaction with analysis and documentation of calibration and quality control, unlike other medical devices. Clinicians often interpret POCT as equivalent to core laboratory testing, only faster, and mistakenly utilize the results interchangeably despite the differences in test methodologies. Taking quality of POCT to the next level involves looking beyond the analytical phase and integration of POCT into the entire pathway of patient care to understand how POCT relates to medical decision-making at specific points during the patient's care. A systematic review of the literature by the National Academy of Clinical Biochemistry is currently being conducted to draft guidelines for best practice that link the use of POCT to improved patient outcomes.

Improving Preanalytic Processes Using the Principles of Lean Production (Toyota Production System)

The basic technologies used in preanalytic processes for chemistry tests have been mature for a long time, and improvements in preanalytic processes have lagged behind improvements in analytic and postanalytic processes. We describe our successful efforts to improve chemistry test turnaround time from a central laboratory by improving preanalytic processes, using existing resources and the principles of lean production. Our goal is to report 80% of chemistry tests in less than 1 hour and to no longer recognize a distinction between expedited and routine testing. We used principles of lean production (the Toyota Production System) to redesign preanalytic processes. The redesigned preanalytic process has fewer steps and uses 1-piece flow to move blood samples through the accessioning, centrifugation, and aliquoting processes. Median preanalytic processing time was reduced from 29 to 19 minutes, and the laboratory met the goal of reporting 80% of chemistry results in less than 1 hour for 11 consecutive months.

Executing Successful Performance Appraisals and Competency Assessments

A performance appraisal is a planned, motivational management tool used to evaluate an employee’s on-the-job behavior and to determine compensation, training needs, and career decisions. The appraisal should include clearly defined expectations, a valid and fair performance assessment, and documentation and follow-up of a plan for improvement. Formal appraisals should be performed by trained individuals to ensure that evaluations are non-discriminatory and confidential since they are discoverable in a court of law. Appraisals are generally position-specific and competency-based, using a rating system to measure the employee’s performance. Certified laboratories must according to CLIA ’88, show documented evidence of performance appraisals and semi-annual competency assessment of pre-analytical, analytical, and post-analytical processes as well as following implementation of any new method or instrument.

Quality indicators and specifications for the extra-analytical phases in clinical laboratory management.

Quality management systems should cover all the steps involved in the overall testing and non-testing processes. To identify quality indicators for extra-analytical processes in the clinical laboratory and to specify acceptability limits, in order to provide a useful tool for continuous improvement of laboratory service. A literature review by Medline search was performed using the keywords: Q-Tracks and Q-probes alone, and management, error, mistake, and indicator crossed with quality, laboratory and medicine. The indicators retrieved were organized according to the various laboratory processes. Their expression was standardized in relation to the total activity of each process reported in each paper reviewed. The magnitude of the errors reported was considered to be the current state of the art for the extra-analytical step and was proposed as the quality specification. Examples of indicators and specifications for the pre-analytical process: Analytical request: Error in patient identification (0.08%), request unintelligible (0.1%). Requested but not collected (7%), redraws (2%). Transport and reception of samples: Inadequate transportation conditions (0.005%), hemolyzed sample (0.2%). Examples of indicators and specifications for the post-analytical process: Report validation: Test not performed (1.4%), test performed but not requested (1.1%). Intra-laboratory reports: Laboratory reporting errors (0.05%), delivery outside specified time (11%). Consulting service: average time to communicate critical values for inpatients (6 min). These extra-analytical indicators and their specifications, expressed in a standardized manner, constitute a preliminary basis for comparison of individual laboratory performance with the purpose of improving laboratory quality.

Outcomes in transfusion.

Outcomes data in medicine can be limited by subjective methodologic issues such as poor selection of end points and use of nonvalidated systems for quality adjustment. Blood transfusion analyses are further complicated by the fact that transfusion seldom is primary therapy but is usually supportive or adjunctive. Thus, much of the outcome data in transfusion medicine are either unavailable or in one of two areas. The first area is prevention of bad sequelae of various cytopenias or factor deficiencies. The second is decreasing adverse effects of transfusion itself. A different useful area for outcome and root cause approaches in individual institutions is examining preanalytical and postanalytical processes of their own. Examples are sample labeling accuracy, quality and timeliness of blood suppliers, internal delivery processes and times, and product wastage. Use review can be changed to real time from retrospective time. By reducing complaints about service to objective data, realistic change can be made in internal and external processes.