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A case study of the laboratory: the most important department in the hospital?

Kenneth E Blick
1 January, 2008  

Kenneth E Blick
PhD
Professor
Director of ­Chemistry and Lab Automation
Department of Pathology
University of Oklahoma Health Sciences Center
Oklahoma City
USA

Since 70–80% of the objective data in the patient’s chart is laboratory data and, at least in the USA, the practice of medicine is clearly moving to a more evidence-based approach, perhaps we should study the role of laboratory services and its direct impact on patient care more closely. In a 12-hospital study involving hospitals in Texas and Oklahoma, we have shown that in fact the laboratory has a direct impact on the flow of patients through the accident and emergency ­department (A&E).(1,2)

These two studies have shown that poorly run laboratories offering an “unpredictable service” can be rate-determining in patients’ A&E length-of-stay (LOS) and, accordingly, may delay clinical, lifesaving medical decisions in the A&E and other critical care areas of the hospital.

For example, in our OU Medical Center (OUMC) in 2003, we monitored our potassium turnaround time (TAT) on A&E patients and measured the percentage of times we failed to hit our promised potassium TAT of 40 minutes. Indeed, we missed the promised 40-minute TAT target 18% of the time. On the other hand, our “routine” potassium tests were taking 40–150 minutes. Physicians and nurses throughout our three teaching hospitals responded to this unpredictable service by:

  • Frequently calling the laboratory asking for verbal reports.
  • Ordering tests as Stat requests.
  • Providing a general lack of support of the laboratory service. Indeed, Stat orders raised to nearly 53% at the OUMC, and frequent telephone calls required nearly 1.5 full-time equivalents (FTEs) just to answer the telephone calls.

In 2003, the laboratory at OUMC launched a project to correct the problems described above by embracing newer computer systems and robotic technology, which would presumably eliminate the need for Stat testing altogether. Automation of the entire testing process was required, which includes the test order, specimen collection instruction/barcode label, transport to the laboratory, specimen receipt and process, test analysis, quality control and verification, electronic release of laboratory results and electronic real-time reporting to the electronic medical record. Two laboratory testing approaches were simultaneous embraced:

  • Total automation of a central core laboratory using a commercial total laboratory automation (TLA) system.
  • Total automation of point-of-care (POC) testing when testing in the automated core ­laboratory was not sufficient to meet critical patient care needs. 

What were the results of these efforts?
In just nine months, we reduced our TAT outlier percent on potassium (and other chemistry testing) from 18% to less than 3%. We eliminated Stat testing altogether by simply testing all specimens in real time on a first-in, first-out basis. After 1.5 years, our physician requests for Stat testing dropped from nearly 53% to less than 4%, with the latter probably reflecting true emergent clinical events. Clearly, this ­difference between the 54% and 4% Stat orders reflected an elimination of the frustration physicians were experiencing with our old, nonautomated, batch-testing approach to laboratory medicine. ­Moreover, calls to the laboratory by physicians and nurses were essentially eliminated, leaving the laboratory staff more productive time to focus on problem specimens and other quality improvement projects. 

And what about eliminating the laboratory as a factor in A&E LOS? Indeed, prior to automation, the A&E LOS for non-admitted A&E patients correlated with our potassium outlier percentage (TAT OP), which started at the very high level of 18% (r2 = 0.95). However, after we improved the service by eliminating TAT outliers, the correlation between TAT OP for potassium and A&E patient LOS dropped to a statistically insignificant r2 = 0.54. This observation strongly suggested that we had eliminated the laboratory as a factor in A&E LOS. 

Based on the foregoing, the indications are pretty clear. For those hospitals that want patients to flow through the hospital on a “real-time” basis, they had better focus on eliminating those racks of ­specimens awaiting processing and testing in the laboratory. Surely, a rack of specimens awaiting analysis in the lab equates to a rack (or queue) of patients in the A&E and other areas of the hospital. The solution for the laboratory is pretty clear as well. TLA with robotics, expert decision-making computer systems, biosensors, immunosensors and automated walk-away analysers are the tools that allow laboratories to achieve real-time testing.

References

  1. Holland LL, Smith LL, Blick KE: Reducing laboratory turnaround time outliers can reduce emergency ­department patient length of stay. Am J Clin Pathol 2005;124(5);672-4.
  2. Holland LL, Smith LL, Blick KE. Total ­laboratory automation can eliminate the laboratory as a factor in emergency department length-of-stay. Am J Clin Pathol 2006;125:765-70.