CAP TODAY Pathology/Laboratory Medicine/Laboratory Management
Looking at one parameter, number of cultures reviewed per week, revealed a periodicity that Dr. Harrington hadn’t been aware of: “We saw a spike in workflow each week at the first of the month.” Corrected Gram stains were fairly consistent, but culture review showed one week with eight.
Most errors were clerical; some were technical or procedural. Such errors are identified and corrected. One important technical error is “Critical value—stat Gram stain not called.” On average there was fewer than one such error per week, so one week with two errors of this type demanded attention. “Rapid inquiry revealed low staffing levels on evening shift due to illness, with intermittent coverage in micro.” Microbiology and the evening shift supervisory staff resolved the problem quickly.
Occasionally a systemic error cropped up and was analyzed. Two examples: “How do MDRO organisms get reported to infection control? No clear procedure. JCAHO requirement”; “TMP/SMZ is not being reported for Stenotrophomonas maltophilia.” Resolutions were proposed, and the review notes when the resolutions were complete.
In addition to fixing the problem, “This provides us with a nice quality log to show an inspector our review process and that we changed policy,” Dr. Harrington says.
Implementing best practices with regard to repeat testing for C. difficile from stool culture was particularly challenging without the option for system-based control of ordering practices. A simple paper log was devised to prevent tests from being repeated within seven days. “At our specimen processing station a printer spits out two stickers—one is put on the specimen and the other pasted onto the log,” Dr. Harrington explains. “When a specimen comes in for C. difficile culture, the technologist can look back and see if that patient has another sticker on the log within seven days.
“Using a paper-based log, we were able to reduce the number of duplicate test requests by 50 percent.” And there was a drop in the number of patients with multiple duplicate test requests, from 32 percent to seven percent. “All of that happened without any systematic communication to clinicians,” Dr. Harrington says. “We just called them and said we are rejecting this request and told them why. Just this hard stop on ordering with a paper-based log was very effective.
“Creative, small-scale solutions can make an impact,” she says, but acknowledges, “This is not a great solution for high-volume, high-throughput labs.”
Niaz Banaei, MD, assistant professor of pathology and medicine and director of the clinical microbiology laboratory, Stanford University Medical Center, described the use of IT to restrict C. difficile testing. He notes two challenges with C. difficile testing: an inability to distinguish colonization from infection and enforcing a seven-day interval between repeat tests. “The same percentage of hospitalized patients are colonized as are test positive,” Dr. Banaei says. Distinguishing colonization from infection is done by testing only patients who have severe diarrhea, defined as three or more loose stools per day. However, labs rarely have access to clinical criteria. “I asked the audience, and pretty much no one is enforcing this restriction.”
Regarding the second challenge, maintaining a seven-day interval between tests, Dr. Banaei notes that repeat testing was recommended in 2004 when only tests with low sensitivity (less than 70 percent) were available. With the introduction of qPCR for the bacterium’s cytotoxin, which has greater than 90 percent sensitivity, repeat testing is unnecessary. Yet clinicians continue to adhere to the old guideline. Dr. Banaei presented data from his investigation of 406 tests in 293 patients at Stanford Hospitals who had one or more repeat tests after a negative PCR (Luo RF, Banaei N. J Clin Microbiol. 2010;48:3738–3741). “Repeat testing within 7 days provided new information in only 2 (0.8%) out of 266 tests, or two (1.0%) out of 197 patients,” the authors concluded. Other investigators have found a similar outcome (Aichinger E, et al. J Clin Microbiol. 2008;46:3795–3797). Dr. Banaei presented the results of the study to the staff of the gastroenterology division who agreed with the seven-day restriction.
To enforce the seven-day interval, Dr. Banaei set up alerts at the order entry and accessioning steps. “We used the hospital information system to look back for an order in the last seven days,” he says. “If there is an order, we let the clinician know that the test is not indicated.” If the clinician ignores the alert, they get one more warning. They are told the test is highly sensitive, and the data from the Stanford study are displayed. If the doctor persists in the order, an alert tells the doctor he or she is being audited and an e-mail is generated to the laboratory supervisor, who looks at the request more closely.
“We wanted to find out how well this system worked, especially after we switched to a more sensitive assay,” Dr. Banaei says. (In 2012 they adopted the Cepheid Gene Xpert, with 98 percent sensitivity.) During the 20 months after the restrictions were implemented, there was little repeat testing in the seven days after a negative test, with a sharp increase at seven days. Of the repeat tests in the first seven days, 100 percent remained negative.
Dr. Banaei is now analyzing the repeats in the second week. “Are some doctors accepting the negative and moving on,” he wonders, “which would mean we are reducing the absolute number of repeats? Or are we just delaying repeat ordering?” In any event, he concludes that IT tools can be used effectively to implement laboratory criteria for C. difficile testing.
Dr. Banaei showed how one could potentially use the hospital information system to apply clinical criteria. When qPCR for C. difficile toxin is ordered, the information system would search the electronic medical record to see if the patient has loose stool and if he or she has three or more episodes of loose stool per day. Dr. Banaei is working on implementing this program now.
In the preanalytical stage, the metric was requisition verification errors. The goal was 99 percent correct manual orders, which was being met already.
In the analytical phase, the program targeted four metrics (goals in parentheses):
◆ Gram stain correlation with final report (≥95 percent).
◆ AFB contamination rate (less than five percent) and blood culture contamination rate (less than three percent).
◆ Proficiency testing (100 percent correct).
◆ QC remedial actions (100 percent of QC failures documented).
For the month of April 2013, actual figures for these four metrics were as follows: 100 percent, 1.2 percent and 1.9 percent, 100 percent, and 100 percent, respectively. In that month, there were five QC failures, all documented. “We go over QC failures and double check what action was taken,” Dr. Balada-Llasat says. Three failures involved low control failures for molecular testing. “QC has to be signed by the lead technologist and by the director,” he says. “We cannot report any result if QC is out of range, and no result is reported until the problem is fixed.”
Postanalytical metrics are turnaround time for molecular viral testing and M. tuberculosis tests and corrected reports. Goals for TAT are more than 95 percent within four days for viruses and more than 95 percent in two days for M. tuberculosis. Achieved values for April 2013 were 100 percent for both metrics. For corrected reports, the target is fewer than two affecting patient care, fewer than four not affecting patient care, and fewer than six total. For April the numbers were one, four, and five, respectively. Educational talks or retraining is the corrective action for corrected reports.
One type of report error is the clerical type, such as using the code FUSP, which denotes Fusobacterium sp., instead of FUSPE, which indicates Fusarium sp. A processing error would be only plating a routine throat culture on BAP. “In this case, the technologist forgot to plate a chocolate plate, so there was no coverage for Haemophilus influenza,” Dr. Balada-Llasat says.
He cites an example of a microscopic error involving a direct smear of cerebrospinal fluid, where the technologist reported no organisms seen, while Gram-negative bacillus was found on review. “When a physician orders Gram stain on CSF,” Dr. Balada-Llasat explains, “the sample may also be sent to anatomic pathology. They are looking for cells and sometimes use different stains. In this case the pathologist contacted me about cells in the CSF. That was a red flag.” Seeing neutrophils in the CSF is an alert that the patient might have an infection. “I reviewed the slide and agreed with the pathologist. It was an opportunity to make some changes.” Now, if neutrophils are seen but no organism is reported, a second technologist must confirm there are no Gram-negative or -positive organisms in the slide.
One of the more common corrected reports has been yeast preliminarily identified as Staphylococcus sp. based on morphology. “When you are dealing with immature colonies, yeast can be misidentified as staph,” Dr. Balada-Llasat says. “Our final identification is now based on mass spec and the preliminary morphology is called ‘yeast-like.’ Since we started doing Gram stain on a wet mount, that mistake has decreased.”
A Gram stain from a positive blood culture is verified in Dr. Balada-Llasat’s laboratory on the Verigene instrument, which identifies organisms by DNA hybridization and provides results in two hours. “We call the physician right away and don’t wait for confirmation by our other methods, which give results the next day.” The other methods are MALDI-TOF mass spectrometry and MicroScan. “In 99.9 percent of cases all methods match,” he says. “It is rare to have a discrepancy.” However, if the other test results don’t match those of Verigene, a corrected report is issued.
Dr. Balada-Llasat showed one case in which a positive blood culture stained as Gram-positive coccus and was identified as E. faecalis by Verigene. However, MicroScan identified the isolate as E. avium, confirmed by MS. “This revealed a weakness of the Verigene—cross-reactivity of E. avium with E. faecalis, which we have now noted,” Dr. Balada-Llasat says. In this situation there was no adverse patient effect.
Dr. Balada-Llasat started validating mass spectrometry two years ago and introduced it into the clinical laboratory more than a year ago. “It has been great for us. It’s quite impressive how sensitive it is. It has expedited identification. For bacteria, mycobacteria, yeast, and dimorphic fungi, you can use MALDI.” Right now they are only doing it on colonies from solid media and mycobacteria from liquid media and consider it their primary method for identifying organisms. However, it gives only the main organism in mixed infections. Also, clinicians and pharmacy want to know about Van A and B and Mec A genes for resistance. “MALDI can’t do that,” Dr. Balada-Llasat says. “Verigene gives us that in a couple of hours.”
Putting MALDI-TOF MS into clinical practice will introduce new QA challenges. “Mass spectrometry is increasingly being used in micro labs for routine identification,” says Dr. Butler-Wu of the University of Washington. Cumitech document 31A, “Verification and Validation of Procedures in the Clinical Microbiology Laboratory,” governs how a laboratory qualifies an instrument like MS for clinical application. A minimum of 200 isolates is required. The document says, “Whenever possible, these isolates should include all species identifiable by the new or revised test.”“Those criteria might work for Vitek or Phoenix,” Dr. Butler-Wu says, “but it becomes impossible for something like MALDI,” for which “everyone is sort of reinventing the wheel.” Laboratories are validating independently and using identification score thresholds. “There are no best practices out there. I was just trying to start a dialogue about this,” she says of her remarks about mass spec in the symposium.
Mass spec is used primarily now in large medical centers. But two instruments—Bruker Biotyper and Vitek MS—are before the FDA. There will be FDA-approved databases, she says. For example, more than 3,000 organisms are in the Bruker Biotyper database, though it is predicted that IVD databases will be more limited.
In her own laboratory Dr. Butler-Wu has taken what she calls a “very conservative” approach, doing species-level identification of organisms they see in clinical practice. She has looked at 2,000 organisms. “That list is now becoming bigger and bigger,” she says. “In time it will become unmanageable.”
While Dr. Butler-Wu confidently concludes that integrating “trust lists” into the routine workflow of the clinical microbiology laboratory has the potential to reduce the number of organisms that require identification by sequencing, when it comes to mass spec, laboratories are back to square one. She says, “There is no consensus on the ideal way to validate MALDI-TOF MS for identification of routine isolates.”
William Check is a writer in Ft. Lauderdale, Fla.