Pre-analytical steps, the major source of mistakes in laboratory diagnostics, arise during patient preparation as well as sample collection, transportation, preparation, and storage. However, while it has been reported that the pre-analytical phase is error-prone, only recently it has been demonstrated that most errors occur in the ‘pre-Pre-analytical phase’.
The latter comprises the initial procedures of the testing process performed by healthcare personnel outside the laboratory walls and outside the direct control of the clinical laboratory. Let us look at the state-of-the-art of pre- Pre-Analytic Automation in the laboratory.
Quality in laboratory medicine should be defined as the guarantee that each and every step in the Total Testing Process (TTP) is correctly performed. Thus, assuring valuable medical decision-making and effective patient care. Indeed, consequent changes made to the medical landscape have greatly impacted the quality and delivery of laboratory services.
In the past decades, a ten-fold reduction in the analytical error rate has been achieved thanks to improvements in the reliability and standardisation of analytic techniques, reagents and instrumentation, and advances in information technology, quality control, and quality assurance methods.
However, recent evidence suggests that 70 per cent of errors in the loop fall actually outside the analytical phase. It is also worth mentioning that the pre- and post-analytical steps have been found to be more vulnerable to the risk of error. The current lack of attention and monitoring to extra laboratory factors is in stark contrast with the body of evidence pointing to the multitude of errors that continue to occur in the pre-analytical phase.
Moreover, the ISO 15189 standard for laboratory accreditation defines the pre-analytical phase as ‘steps starting in chronological order — from the clinician’s request and including the examination requisition, preparation of the patient, collection of the primary sample, and transportation to and within the laboratory, and ending when the analytical examination procedure begins’.
This clearly recognises the need to evaluate, monitor and improve all the procedures and processes in the initial phase of the brain-to-brain concept introduced by Lundberg.
Pre-analytic automation
Pre-Analytic steps including test ordering, sample collection, patient identification, and correct sample tubes can be brought in an intelligent test tube collection management system, which can be integrated with the LIS/HIS system.
This intelligent system selects and recognises the correct tubes as per the ordered tests. This automation in pre- Pre-Analytic phase is very helpful as these initial procedures are usually performed neither in the clinical laboratory nor undertaken at least in part under the control of laboratory personnel.
Once the sample is collected it should be transported immediately through an approved transportation system. The automatic transporting system can be connected with all the collection units to a single sample receiving station in the laboratory. The system is dedicated to one-touch handling and lightning-fast transport of all clinical samples. It supports lean thinking through new working routines. It even reduces the need for potential POCT equipment. More importantly, the transportation system has a sample tracking system with software that allows consistent data collection.
Thus, automation is an objective measure that potentially evaluates all critical care domains such as patient safety, effectiveness, equity, patient-centredness, timeliness and efficiency based on evidence associated with those domains. It can also be implemented in a consistent and comparable manner across settings and over time.
Conclusion
The implementation of Pre-Analytic automation in the laboratory is a fundamental step in providing sound evidence of quality. Automation also plays a key role in ensuring that the targeted continuous improvement activities aiming to reduce the risk of errors in clinical practice are undertaken. Consistent data collection through an automation system and the software automatically results in effective quality improvement.
References available on request.
Dr. Sumi Koshy is the Quality Manager at AgileLab.
This article appears in the latest issue of Omnia Health Magazine. Read the full issue online today.
