Laboratory-related errors: you cannot manage what you don’t measure. You manage what you know and measure

Over the last decades, more and more timely and accurate laboratory test results have been produced leading the clinical laboratory to be recognized as the “nerve centre of diagnostic process” [1]. Every day, clinical laboratories worldwide analyze billions of samples to provide essential information that allows a reliable clinical decision-making (diagnosis, drugs prescriptions, patients admission/discharge from hospital). However, the complex process that finally provide laboratory information is not error-free. Since 1997, with the publication of the landmark paper by Plebani and Carraro [2], a number of papers [3], [4], [5] demonstrated that errors can occur in any step of the process, in the pre-analytical (46–68.2%), analytical (7–13%) and post-analytical phases (18.5–47%) [6]. Although, compared to billions of laboratory results, the absolute percentage of errors could appear very low, on the contrary, it could become relevant when considered in relation to patient outcome. Although Plebani and Carraro [2] demonstrated that 74% of laboratory errors did not affect patients’ outcome, the other 26% translates into a patient care problem, leading at least to further inappropriate investigations, patient discomfort, increased costs (19%) and, even worse, to inappropriate care and/or modification to therapy (6.4%). Undesirable outcomes are generally a result of unrecognized and/or unmanaged risk: any potential error that impacts on a patient must be, therefore, first recognized and detected and subsequently managed.

The knowledge of errors is the key element in the identification and implementation of control measures to prevent failures occurrence and reduce risk, while the recognition and detection of errors are essential to correct failures and intercept them before they reach the patient and cause harm.

In this issue of journal Diagnosis, Ristelli and Noble analyze patient safety events’ data, collected by 75 laboratories using a web-based incident reporting system, thus contributing further essential information on the issue of errors reporting [7]. Although the error rate was consistent with several studies available in the literature [3], [4], the authors highlight a degree of under-reporting in both the intra- and post-analytical phase, not only due to technical problems (lack of access to computers or reporting system that are difficult to use), but also due to human nature (afraid to be blamed as “whistleblowing”, lack of feedback that demoralizes reporters’ efforts). However, the choice of the incident reporting system as an approach for identifying laboratory errors, “forced” health professionals not only to classify the event (as near miss or not), but also to identify the degree of harm to the patient, thus increasing the awareness on patient safety issue.

The majority of reported errors in the study, in fact, concerned patient or sample misidentification [7], one of the nightmares of laboratory staff. This error can originate inside and outside the clinical laboratory, but wherever it originates, it potentially strongly impacts patient safety. It was estimated that in the United States, approximately 25 deaths per year are due to a hemolytic transfusion caused by misidentification errors [8]. In order to highlight this typology of error before the release of results, laboratories have already implemented procedures and systems (e.g. comparison of laboratory results with results obtained on previous samples from the same patient), but the final goal of “zero errors” seems to not be achievable. This depends on the real difficulty to detect this type of error; in fact, the error rates currently reported in the literature represent only the “tip of the iceberg” and the lack of identification and recording of all the errors that occurred does not allow the appropriate analysis of causes and consequently, the implementation of improving actions.

Moreover, when the errors occur outside the laboratory and involve non-laboratory professionals, the management of errors becomes even more complicated and depends on the communication flow between laboratory and non-laboratory staff. However, laboratory professionals play an essential role in improving safety in this crucial step if laboratory testing by implementation of systems is focused on the prevention and catching of errors.

On the basis of an old management adage that perfectly suits the clinical laboratory as well, “You can’t manage what you don’t measure” and “You manage what you know and measure”, laboratory professionals measure errors with different tools [quality indicators (QIs), incident reporting, etc.], that lead to a better understanding and resolution of errors and risk of errors. Numerous efforts have been made in the last decade to study the type and frequency of errors as well as to increase the awareness of laboratory and health care professionals on the importance of a systematic error reporting as an effective way to manage errors. In this context several programs on QIs worldwide have been launched with the aim, not only to collect errors over time, but also to recommend strategies and procedures to improve patient safety [9], [10], [11], [12], [13]. The use of QIs in the clinical laboratories to monitor all critical activities of pre-, intra- and post-analytical phases is also required by the ISO 15189, the International Standard for accreditation of clinical laboratories. In spite of this, a body of evidence demonstrated that a limited number of laboratories collect regular and comprehensive data (especially concerning the extra-analytical phases), generating the so-called “quality indicators paradox” [14]. Among the causes of this paradox, two of them need to be explored further. On the one hand, the lack of computerized system for error recording, useful to guarantee a standardized and complete data collection and to save time and human resources, on the other hand, the missed data analysis and implementation of corrective actions in order to decrease the error rate.

The measuring process is a critical aspect that can affect the correct interpretation of collected data. An important prerequisite, in fact, is that all occurred errors have to be reported in order to evaluate the actual number. In this context, the systematic and automated data collection, if on the one hand, surely facilitates the staff to report errors, on the other hand, it could induce a passive errors reporting if the error is not treated, or when there is no evidence of management to the staff that report errors.

Another difficulty concerns the identification and implementation of corrective actions when the laboratory is not involved. In a published study [15], QIs’ data monitoring over a 3-year time-frame demonstrated that processes under the full control of the clinical laboratory have improved much more than processes requiring the close cooperation between the laboratory and sites where the sample is collected.

In these cases, a top-down approach is usually used, according to which the host organization within which the laboratory works, takes charge of the errors management (e.g. formalization of operating procedures and its dissemination to clinical wards, training courses, re-engineering of processes). However, the error management cannot stop at high host organization levels, but the actions taken should be divulged and shared with the staff involved. In many cases, in fact, data analysis and preventive/corrective actions implementation are performed by the high organization (managers) and not by error reporters (nurses and physicians in clinical wards), thus leading to a lack of feedback to the reporters, resulting in the following passive data reporting, known to be not equivalent to error reduction.

Anyway, in the field of health care errors, and more so in general laboratory errors, the detection and management, should be based on a “systems approach” according to which the errors arise due to system design failures instead of human failure (careless or inattentive staff).

The reactive approach, basically based on error reporting and monitoring over time, allows identifying not only the source of errors but also the most critical processes. These latter, once identified, could be proactively studied, in order to improve them and to ensure that clinicians provide the effective care they intend to provide.

In conclusion, the items to point out are:

• the reporting system, regardless of typology of events involved (adverse events, near miss events or sentinel events, etc.), represent a key tool in the management of errors. It allows knowing the critical activities and providing the possibility to resolve the problems and improve the performance. Ultimately, it improves patient safety by adopting the strategies ‘‘learn from incidents’’ and ‘‘reduce error impact’’;

• the use of consensually harmonized QIs, as an integrated part of the quality improvement system, guarantees a standardized and continuous data collection and the possibility of benchmarking;

• the use of a systems approach is useful to de-emphasize personal culpability, so that latent conditions that cause errors are recognized as system failures amenable to analysis and correction;

• although the “zero-defect” should be the goal to be achieved, the available data have shown that it remains a very ambitious goal;

• the awareness of all health care professionals about the importance of reporting and management of occurred undesirable events is the driving force of the entire system.