The Scarcity of Peer-Reviewed Literature on QI in Laboratory Medicine
Can the Bias Against Publishing be Broken?
By Frederick Strathmann, PhD
As scientists, we have been taught to follow up on new experimental results and hypotheses by performing a thorough search of the published literature. Knowledge of the literature can reduce the repeating of experiments, help hone ideas, and provide a needed perspective on how a new finding fits into a field of study. Unfortunately, laboratorians interested in how to improve quality by reducing specimen loss find that there is not much to read on the subject in the peer-reviewed literature.
To illustrate this point, I conducted a literature search using the term “specimen loss” on Pubmed a common first stop for literature searches. On February 5, 2010, only four articles matched this exact search phrase. One article compared methods of the specimen loss rate during macular hole surgery (1), and two papers reported on the loss of specimens during biopsy procedures (2, 3). The last publication detailed problems with specimen loss in a longitudinal study of beef cattle (4). In contrast to the paucity of literature on specimen loss, 64,383 articles matched the search phrase “method validation”, 31,219 articles matched “cardiac marker”, while 512 articles turned up using “vitamin D mass spectrometry” as the search term. While it is clearly important to validate laboratory methods, investigate cardiac markers, and explore the pros and cons of various methods to measure vitamin D, why are there so few peer-reviewed journal articles on specimen loss?
I believe there are three major reasons why a variety of quality improvement (QI) topics like specimen loss are neglected in the medical literature. First, clinical laboratory directors, both in academic and nonacademic settings, prefer to conduct research on other topics, especially those involving analytic methods or clinical use of tests. Second, risk management officers may block or slow down the publication of the QI data because they fear the institution could suffer a financial loss or damage to its reputation. Finally, laboratory directors themselves may fear revealing QI data due to the prospect of losing their job or damaging their reputation.
The Law of Supply and Demand
It is fair to assume that to some degree the principle of supply and demand is a contributing factor to the limited amount of research on the subject of specimen loss. In this context, demand is determined by comparing the number of laboratorians engaged in QI projects or research versus those working on method development or validation. Supply would refer to the available number of QI projects versus those dealing with method development or validation. In general, on both the supply and demand side, laboratorians favor research on analytic methods and clinical use of tests over QI-related topics. In academic settings, longstanding trends in research funding perpetuate this situation by discouraging academic faculty from investigating how laboratories deliver healthcare.
A common place to lose specimens in the clinical laboratory.
The Other Factor: Fear
Interest, or lack thereof, is not the only reason for the scarcity of published data on specimen loss. Given the current focus on patient safety, it is not surprising that lab directors and their institutions are hesitant to reveal their specimen loss data. Within healthcare organizations, the primary goal of the risk management system is to reduce and control risk associated with the day-to-day activities of the institution. An unfortunate side effect of this goal is the reluctance to publish QI results. Typical risk management questions include: 1) What good can come from publishing how often we lose or destroy specimens? 2) Even if we de-identify our institution, won’t readers be able to determine where the data is coming from based on the authors’ institutional affiliations? 3) Will our competitors use the data to represent us in a negative light? 4) Will patients and their lawyers use the data to sue us? Similar questions haunt individual lab directors as they assess the possible damage to their careers if they publish QI data. The end result is that very little such data are published.
Another important factor concerning publication of specimen loss data is its accuracy. In order to publish such data, the laboratory actually must know its current specimen loss rate and, if such a measure is in place, staff also must be confident about its accuracy. The concept of accuracy can quickly become a gray area because definitions of specimen loss tend to be laboratory specific. Some laboratories narrowly define loss to mean simply the physical loss of a specimen, while others include situations where the lab compromised, and therefore failed to analyze, what was essentially a perfectly good specimen.
With an accepted definition in place, implementing a metric for specimen loss is conceptually quite simple; however, ensuring its accuracy remains a challenge. For example, in most institutions, tracking all the processes involved in the “specimen life cycle”—the point at which the specimen is taken from the patient to final result reporting—is a complex task spread across multiple areas of the organization.
It is unlikely that the topic of specimen loss will ever be as attractive to researchers as developing and validating the next great laboratory test. Nor will this QI subject suddenly result in a comparable number of studies as those on applying the latest technology to a clinical question. After all, a classic method validation project, especially one dealing with an automated laboratory instrument, is typically straightforward and well-suited for a transitory trainee in the lab. In contrast, projects related to specimen loss are often hard to define, difficult to accurately measure, and not easily executed into the time allotted for a typical laboratory research project.
Hopefully, as the application of disciplined problem solving methods like Lean/Six-Sigma spread to all areas of the lab, there will be an expansion of the peer-reviewed, scientific literature on specimen loss and other aspects of QI. Undoubtedly, this expansion will be a helpful resource to laboratory directors whose primary focus is QI and patient safety.
It is true that every sample lost represents a poor outcome for a patient, so Superlative’s lab staff is correct in concluding that there have been more poor patient outcomes over the course of the year. However, if improvement is their goal, using this graph to understand where to start and what to change would merely be tampering because the graph does not give insight into causes.
To determine a baseline before starting the improvement effort, a better choice would be to track the daily lost sample rate (Figure 3). The intent of this analysis is to understand the cause of lost samples. The same data plotted daily as lost samples per test performed shows that performance has in fact been stable and that the peak at day 301 is most likely a “special cause” event.
- Kuo HK et al. Clinicopathological study of the idiopathic macular hole: comparison of epiretinal membrane peeling and internal limiting membrane peeling. Ophthalmologica 2004; 218: 31–5.
- Tsin DA and Colombero LT. Laparoscopic leash: a simple technique to prevent specimen loss during operative laparoscopy. Obstet Gynecol, 1999; 94: 628–9.
- Hookey LC et al. One bite or two? A prospective trial comparing colonoscopy biopsy technique in patients with chronic ulcerative colitis. Can J Gastroenterol, 2007; 21: 164–8.
- Carson C et al. Establishment and maintenance of a longitudinal study of bovine spongiform encephalopathy (the ULiSES scheme). Prev Vet Med 2001; 51: 245–57.
- Monahan T. Surveillance and security: tecnological politics and power in everyday life. Routledge, New York, 2006.
- Young D. Pittsburgh hospital combines RFID, bar codes to improve safety. Am J Health Syst Pharm 2006; 63: 2431, 2435.
- Bacheldor B. At Mayo Clinic, RFID tracks Biopsies. Health Care News January 2007. RFID Journal website. Accessed 19 February 2010.
Frederick Strathmann, PhD, is a senior fellow in the Department of Laboratory Medicine at the University of Washington, Seattle.