Why POCT?

Point-of-care testing (POCT) is a growing trend. Examples of frequent inpatient POCT measurements include whole blood troponin for assessing myocardial injury, creatinine with estimation of glomerular filtration rate for assessing renal function, prothrombin time (PT) with INR calculation to guide thrombolytic therapy in stroke protocols, and the ubiquitous measuring of whole blood glucose for managing a patient’s glycemic state.

Today, you will see POCT throughout a hospital with handheld devices or small benchtop analyzers in the emergency department, intensive care setting, general medical wards, labor and delivery, and imaging centers. And market analyses seem to reflect this trend of moving testing away from central laboratories and to the patient’s bedside. According to a MarketsandMarkets 2014 report, for example, the global point-of-care diagnostics market is projected to hit US$27.5 billion by 2018 – indicating a clear demand for this type of testing. The market research firm says the growth is due to rising prevalence of chronic and infectious diseases, increasing use of home-based POCT devices, technological advancements, and the decreasing number of technologists in the central laboratory, to name but a few. In my institution, some administrators have also considered POCT as a way to lighten the workload of a resource-strained central laboratory.

This demand is reflected locally with plentiful requests from my clinical medicine colleagues. The ability to perform a rapid biochemical analysis at the bedside, with results sometimes available in seconds rather than hours, is very appealing to the physician. The perceived benefit of POCT is that faster results lead to faster changes in management – meaning that patients will have better outcomes. While logical, there’s no proof yet that this is actually true. It is, however, a testable hypothesis, with well-designed, outcomes-based research studies that evaluate the effectiveness or efficacy of such testing.

However, outcomes research on POCT (or any laboratory tests, for that matter) is difficult because the tests don’t have a direct impact on the patient; instead, they require action by clinicians. I think Petrie Rainey, a professor of laboratory medicine at the University of Washington, USA, summarized this well in his 1998 editorial for Clinical Chemistry (1). He wrote, “…the effect of a test result is always filtered through the change in medical management it engenders.” James Nichols et al., in a 2000 study evaluating patient wait times after POCT tests in an interventional radiology and cardiology setting, very nicely confirmed Rainey’s observation (2). Nichols’ group demonstrated a decrease in wait time only after optimizing workflows around the POCT results. Fast-forward 15 years and this observation still likely explains why so many studies continually fail to show positive outcomes associated with POCT.

A hotbed of POCT outcomes research is the hospital emergency department (ED). Here, POCT has been proposed as the solution to overcrowding (3). The specific aims of POCT in the ED are to increase timely discharge, shorten length of stay, increase patient throughput, and reduce time to treatment. This begs the question – does POCT accomplish the aforementioned aims? Numerous randomized controlled trials have been conducted, for example, comparing POCT with central laboratory measurement of cardiac biomarkers. Roland Bingisser et al. summarized their group’s findings in a 2012 American Journal of Emergency Medicine article (4). Based on my understanding of the article, I think that collectively these randomized controlled trials indicate that point-of-care cardiac biomarker testing has little to no impact on length of stay, which raises questions about the utility of performing POCT when a central laboratory measurement may suffice. It is important to note that managing POCT requires considerable resources and time to ensure quality testing is being performed.

Don’t get me wrong – I do think there can be tremendous benefit to POCT if results are acted upon in a timely manner. The big question is: will we abandon POCT if well-designed studies (incorporating optimized workflows) reproducibly fail to demonstrate a positive effect, or will we continue to perform POC testing under the guise of a perceived benefit? I look forward to seeing the data!