Funded by the CDC, the program hopes to alleviate personnel shortages in Baltimore area clinical labs while also producing a knowledge base for lab managers nationwide
Clinical laboratory managers struggling to fill vacant phlebotomy and accessioning positions will be interested to learn about a pilot program being conducted by the City of Baltimore and the University of Maryland School of Medicine to train people “for employment in hospital laboratories, phlebotomy draw sites, and reference laboratory processing centers,” according to The Elm, a publication of the University of Maryland, Baltimore.
The 14-week “Mayor’s Workforce Development Program” began on April 19 and will continue through the end of July. Participants meet twice a week for lectures and experience working with specimens in actual medical laboratories or in a “hybrid learning environment,” The Elm reported.
“I came up with the idea of doing cross-training for laboratory people and public health people in case there is another pandemic,” explained Lorraine Doucette in an exclusive interview with Dark Daily. Doucette, who is managing the pilot program, is an Assistant Professor and Medical Laboratory Science Program Director, Department of Medical and Research Technology, University of Maryland School of Medicine.
“There is already a huge shortage of laboratory people, but an enormous amount left in droves during the pandemic because they got physically burned out. Some just could not do the work anymore because of things like carpal tunnel syndrome and repetitive stress injuries,” she added.
“I’m confident that all 15 or 16 students who complete this workforce program will be employed within weeks of finishing as accessioners,” said Lorraine Doucette (above), Assistant Professor and Medical Laboratory Science Program Director, Department of Medical and Research Technology, University of Maryland School of Medicine, in an exclusive interview with Dark Daily. “This has been so successful. This is making a difference in people’s lives. This is changing them from being unemployed to actually having a career in a clinical laboratory. They love it. They are so proud of themselves.” (Photo copyright: LinkedIn.)
CDC Funding Part of National Program to ‘Enhance’ Clinical Lab Workforce
The collaboration is part of a CDC project titled, “Enhancing US Clinical Workforce Capacity.’ Doucette will receive a total of one million dollars over the course of three years to facilitate the program in stages.
“It is not necessarily an old-fashioned grant where they just gave me a pile of money,” Doucette told Dark Daily. “The CDC works with me constantly via reports and Zoom meetings.”
This CDC project is designed to both cross train clinical laboratory professionals in public health, clinical chemistry, microbiology, and hematology, as well as to train individuals in the workforce development program to become laboratory accessioners.
“They are going to be qualified to work as an accessioner in any local hospital,” Doucette noted. “The people who pick up the lab samples out of the tube system are the accessioners and there is a huge shortage of them also. We’re teaching them the basics so the more advanced lab personnel can perform the higher-level work.”
Students in the program learn all about lab safety and the proper handling of lab samples as well as proper data entry, professionalism, and how to communicate with medical and laboratory personnel. They work with urine and blood samples and fabricated spinal fluid samples.
“They are taught about the different tubes, what the anticoagulants are, what makes each tube unique, why you can’t mix samples, balancing a centrifuge, and how to properly put on and remove safety gear like lab coats, gloves, and goggles,” Doucette explained.
The Mayor’s Workforce Development Program is free for Baltimore residents looking for employment via the workforce office. The only requirements for enrolling are having a high school education and being fully vaccinated.
Phlebotomy and Additional Cross-training to Be Added
Doucette would eventually like to add a phlebotomy segment to future training sessions. “We would like to develop an additional partnership with BCCC (Baltimore City Community College) for the phlebotomy piece. That would definitely increase the people and the program’s marketability,” she said. “They could not only draw the blood, but they could also process the sample.”
After assessing the success of the current program and determining what did and did not work, there will be an additional training session held in the fall. Next year, there will be more sessions held for individuals in the workforce program and cross-training classes for current clinical laboratory professionals.
The strategy for the third year of the grant includes sharing the specifics of the program with medical laboratory professionals via the CDC’s free OneLab REACH platform. This portion includes the online delivery of documentation such as training sheets, lab exercises, Microsoft PowerPoint presentations, and videos used in both the accessioning and cross-training coursework.
“We’re going to do the OneLab REACH,” Doucette said. “I’m going to be putting it all online and marketing it all around the country in stages and increments. I will be going to a lot of professional society meetings and talking to lab managers to help them understand the concept of how this all benefits them.”
This unique collaboration between the City of Baltimore and University of Maryland School of Medicine, funded by the CDC, should help alleviate some of the clinical laboratory worker shortages that exist in the Baltimore area. Hopefully, the effort will result in additional knowledge, resources, and tools to assist medical lab managers across the country to recruit and retain talented, highly-skilled workers.
An assay using mass spectrometry could go to clinical trial within two years
Dark Daily has regularly observed that humans generate a variety of volatile substances—particularly in breath—which can be used for diagnostic purposes. But what if people, like certain trained animals, could smell the presence of disease before the onset of symptoms? What types of clinical laboratory testing biomarkers could be developed based on human-generated volatile organic compounds?
Researchers at the University of Manchester (UM) in the United Kingdom (UK) say their “breakthrough” test to diagnose Parkinson’s disease “can diagnose disease from skin swabs in three minutes,” according to a university press release.
Perdita Barran, PhD (right), head of the University of Manchester research team that developed the mass spectrometry Parkinson’s test, is shown above with Joy Milne (left), the retired nurse from Scotland who inspired Barran’s team to develop a new Parkinson’s biomarker and method for identifying it. “We are tremendously excited by these results which take us closer to making a diagnostic test for Parkinson’s Disease that could be used in clinic,” she said in a press release. A viable clinical laboratory test for Parkinson’s disease is greatly needed, as more than 10 million people worldwide currently live with the neurodegenerative disorder. (Photo copyright: University of Manchester.)
Using Mass Spectrometry to Analyze Sebum
The UM scientists hypothesized that the smell could be due to sebum, a light oily substance on skin that was going through a chemical change due to the Parkinson’s disease, Hull Daily Mail explained.
Increased sebum, which is produced by the sebaceous glands, is a hallmark of Parkinson’s, the researchers noted.
Their new method involves analysis of sebum using mass spectrometry, according to the JACS AU paper. The method, the researchers claim, makes it possible to diagnose Parkinson’s disease from skin swabs in three minutes.
“There are no cures for Parkinson’s, but a confirmatory diagnosis would allow [Parkinson’s patients] to get the right treatment and get the drugs that will help to alleviate their symptoms,” Perdita Barran, PhD, told the Hull Daily Mail. Barran is Chair of Mass Spectrometry in the Department of Chemistry and Director of the Michael Barber Centre for Collaborative Mass Spectrometry at UM’s Manchester Institute of Biotechnology. “What we are now doing is seeing if (hospital laboratories) can do what we’ve done in a research lab in a hospital lab,” she added.
Sebum Analyzed with Mass Spectrometry
Parkinson’s disease—the world’s fastest growing neurodegenerative disorder—needs “robust biomarkers” that could advance detection and head off onset of motor symptoms such as tremor, rigidity, and postural instability, the researchers note in their paper.
Their recent study builds on earlier 2019 findings they published in ACS Central Science about volatile compounds in sebum possibly being used as Parkinson’s biomarkers.
“Sebum is an underexplored biofluid, which is readily obtained from non-invasive skin swabs, which primarily consists of a mixture of triglycerides, cholesterol, free fatty acids, waxy esters, and squalene,” the researchers explained in their JACS AU paper.
The scientists sought, “to develop a method to analyze sebum in its native state to facilitate rapid assessment of the Parkinson’s disease status. Paper spray ionization mass spectrometry, which allows the direct analysis of compounds from paper, has previously been demonstrated to detect small molecules from unprocessed biofluids, such as blood and urine, but not to date with sebum,” they wrote.
The UM researchers used mass spectrometry to analyze sebum collected on cotton swabs from the backs of 79 people with Parkinson’s and 71 healthy individuals, BBC Scotland News reported.
Depanjan Sarkar, PhD, Research Associate, University of Manchester, further explained the technique in the UM news release:
Sebum is taken from the swab to filter paper cut in a triangle.
Using a solvent and voltage, sebum compounds transfer into the mass spectrometer.
“When we did this, we found more than 4,000 unique compounds of which 500 are different between people with Parkinson’s compared to the control participants,” Sarkar said.
Fatty Acids Make Assay Possible
Could fatty acids pave the way to an assay? The UM researchers believe so.
“We have identified two classes of lipids, namely [triglycerides] and diglycerides, as components of human sebum that are significantly differentially expressed in PD,” the researchers wrote in JACS AU. “Non-invasive sampling followed by PS-IM-MS [paper spray-ion mobility–mass spectrometry] analysis targeting these compounds could provide an inexpensive assay to support clinical phenotyping for the confirmatory diagnosis of Parkinson’s disease.”
A clinical trial for their test, which costs about $20, may be done within two years in Manchester area, the Daily Mail reported.
When Dark Daily reported in 2020 on Joy Milne’s unique ability to smell her husband’s Parkinson’s disease before it was formally diagnosed, we predicted a diagnostic test for Parkinson’s may be years away. And here it is, albeit with regulatory clearance needed following clinical trials.
It may in fact be possible to leverage sebum analysis to detect other diseases, the UM researchers noted.
For diagnostics developers, this story of Joy Milne and her husband Les Milne is a useful example of how, in tracking the life of a specific patient with a specific disease and close family members, researchers were able to identify a new class of biomarkers that could be used in a diagnostic assay.
It will be interesting to follow the University of Manchester researchers in their quest for a diagnostic mass spectrometry clinical laboratory test for Parkinson’s disease. According to Parkinson’s Foundation statistics, about 10 million people worldwide live with the neurodegenerative disorder. Such a new diagnostic test could be vitally important to medical laboratory care, and to patients and their families.
At hospitals where results of molecular COVID-19 testing can take up to several days to return, this new method for identifying potentially infected patients could improve triage
Frustrated by shortages of essential COVID-19 tests and supplies—as well by lengthy coronavirus test turn-around times—researchers at Weill Cornell Medicine have created an Artificial Intelligence (AI) algorithm that can use routine clinical laboratory test data to determine if a patient is infected with SARS-CoV-2, the coronavirus that causes the COVID-19 disease.
This is an important development because the turn-around-time (TAT) for common lab tests is generally much shorter than COVID-19 molecular diagnostics—such as real-time reverse transcription polymerase chain reaction (RT-PCR), currently the most popular coronavirus test—and certainly serological (antibody) diagnostics, which require an infection incubation time of as much as 10-14 days before testing.
Some RT-PCR diagnostic tests for COVID-19, which detect viral RNA on nasopharyngeal swab specimens, can take up to several days to return depending on the test and on the lab’s location. But routine medical laboratory tests generally return much sooner, often within minutes or hours, making this a potential game-changer for triaging infected patients.
Machine Learning Brings AI to COVID-19 Diagnostics
Advances in the use of AI in healthcare have led to the development of machine-learning algorithms that are being utilized as diagnostic tools for anatomic pathology, radiology, and for specific complex diseases, such as cancer. The Weill Cornell scientists wanted to see if alternative lab test results could be used by an algorithmic model to identify people infected with the SARS-CoV-2 coronavirus.
“When patients come to the [emergency department] and the doctor orders several panels of routine lab [tests] and also the [SARS-CoV-2] RT-PCR test, generally the routine test results come back in a couple of hours,” Sarina Yang, MD, PhD (above), one of the authors of the study, told Modern Healthcare. “So, we thought it could be useful to use the routine labs to predict whether the RT-PCR results would be positive or negative to improve the triage process.” Yang is an assistant professor in the Department of Pathology and Laboratory Medicine, and Assistant Director of the central laboratory and Director of the toxicology laboratory at Weill Cornell Medicine. (Photo copyright: Weill Cornell Medicine.)
To perform the research, the team incorporated patients’ age, sex, and race, into a machine learning model that was based on results from 27 routine lab tests chosen from a total of 685 different tests ordered for the patients. The study included 3,356 patients who were tested for SARS-CoV-2 at New York-Presbyterian Hospital/Weill Cornell Medical Center between March 11 and April 29 of this year. The patients ranged in ages from 18 to 101 with the mean age being 56.4 years. Of those patients, 1,402 were RT-PCR positive and the remaining 1,954 were RT-PCR negative.
Using a machine-learning technique known as a gradient-boosting decision tree, the algorithm identified SARS-CoV-2 infections with 76% sensitivity and 81% specificity. When looking at only emergency department (ED) patients, the model performed even better with 80% sensitivity and 83% specificity. ED patients comprised just over half (54%) of the patients used for the study.
Weill Cornell Medicine Algorithm Could Lower False Negative Test Results
The algorithm also correctly identified patients who originally tested negative for COVID-19, but who tested positive for the coronavirus upon retesting within two days. According to the researchers, these results indicated their model could potentially decrease the amount of incorrect test results.
“We are thinking that those potentially false negative patients may demonstrate a different routine lab test profile that might be more similar to those that test positive,” Fei Wang, PhD, Assistant Professor of Healthcare Policy and Research at Weill Cornell Medicine and the study’s senior author, told Modern Healthcare. “So, it offers us a chance to capture those patients who are false negatives.”
The researchers validated their model by comparing the results with patients seen at New York Presbyterian Hospital/Lower Manhattan Hospital during the same time period. Among those patients, 496 were RT-PCR positive and 968 were negative and the algorithmic model performed with 74% specificity and 76% sensitivity.
preliminarily identify high-risk SARS-CoV-2 infected patients before RT-PCR results are available,
risk stratify patients in the ED,
select patients who need relatively urgent retesting if initial RT-PCR results are negative,
help isolate infected patients earlier, and
assist in the identification of SARS-CoV-2 infected patients in areas where RT-PCR testing is unavailable due to financial or supply constraints.
Early Results of Study Promising, But More Research is Needed
Wang noted that more research is needed on the algorithm and that he and his colleagues are currently working on ways to improve the model. They are hoping to test it with different conditions and geographies.
“Our model in the paper was built on data from when New York was at its COVID peak,” he told Modern Healthcare. “At that time, we were not doing wide PCR testing, and the patients who were getting tested were pretty sick.”
At the time of the study, the positivity rate for COVID-19 at New York-Presbyterian Hospital was in the 40% to 50% range. That was substantially higher than the current positivity rate, which is in the 2% to 3% range, Modern Healthcare reported.
“This model we built in a population in New York in a certain time period, so we can’t guarantee that it will work well universally,” Wang told Modern Healthcare.
It’s exciting to think that advances in software algorithms may one day make it possible to combine routine clinical laboratory testing and create diagnostics that identify diseases in ways the individual tests were not originally designed to do.
This study is an example that researchers in AI and informatics are working to bring new tools and diagnostic capabilities to clinical laboratories. Also, this is a demonstration of how a patient’s results from multiple other types of lab tests can by analyzed using AI and similar analytical algorithms to diagnose a health condition unrelated to the original reasons for performing those tests.
If this can be demonstrated with other diseases and health conditions, it would open up one more way that pathologists and clinical laboratory scientists can contribute to more accurate diagnoses and improved selection of the most appropriate therapies for individual patients.
Many IVD vendors are cautiously optimistic about the “state of the medical lab industry,” but recognize that declining reimbursement for lab tests is now harming many lab organizations
Complying with this standard will help reduce errors by improving specimen handling and tracking, and also reduce lab costs by boosting accuracy and quality.
Clinical laboratories have about nine months to comply with a new standard for bar code labels. The deadline for compliance to AUTO12-A, Specimen Labels: Content and Location, Fonts, and Label Orientation, is April 29, 2014.
