Diagnostics


That would be enough of an issue if microbiology labs were fully staffed. They’re not. The growing difficulty laboratory medicine faces in recruiting and retaining specialist staff suggests Lenk is not the only one having issues with the nature of the work. Between 2016 and 2018, according to the Journal of Clinical Microbiology, clinical laboratories in the US were hamstrung by a technician vacancy rate of over 7%, as several thousand staff left the profession and the number of new positions grew at double the rate of other occupations. Covid-19 hasn’t made things any easier.


“Automation has a quality component to it and, quite bluntly, it has a practical component – especially in the US and Canada, where we’re seeing massive shortages of trained medical technologists who work in laboratories,” says Nate Ledeboer, medical director for clinical microbiology and molecular diagnostics at the Medical College of Wisconsin. In 2014, Ledeboer’s lab became one of the first microbiology labs in the US to fully automate its front-end processing (medium selection, medium inoculation, plate streaking and the application of patient information and barcodes for tracking), incubation and plate imaging with the Copan WASPLab platform. Since then, it’s cut a day from clinical workflows, and learned how to field calls from physicians adamant that, as Ledeboer recalls, “You must have screwed up my patient’s results; there’s no possible way you could have got them back so fast.” To borrow the terms Lenk uses to define the ‘smart’ lab of the future, what Ledeboer had actually done is begin to “bridge the gap between biology and technology”. In the clinical labs of Lenk’s unoptimised nightmares, that chasm is papered over by the wrist- straining bustle and busywork of overstretched technologists, and quality suffers as a result. A recent study – also in the Journal of Clinical Microbiology – of the economic impacts of implementing total lab automation (TLA) platforms (either the Copan WASPLab or the BD Kiestra) in four US microbiology labs found productivity increases ranging from 18–93%, and cost-per-specimen reductions of 15–47%, resulting in approximate annual labour savings of between $268,000 and $1.2m. Across laboratory medicine, these systems are making the connections necessary for greater use of AI and machine learning in diagnostics, as well as enabling the integration of multiple specialities into a single hub. But the requirements for implementing TLA are just as profound as its potential impacts.


Embrace automation


“If you look at clinical laboratories, what they have is very sophisticated devices for each specific target, because there are good sales for smaller companies that have specific solutions for specific problems,”


Practical Patient Care / www.practical-patient-care.com


explains Lenk, “but these device solutions are not normally integrated into the infrastructure. They create a text file with the result, or they have a display saying: ‘Okay, you are ill.’ Now, the existing gap calls for a solution to link all these systems, to organise the workflow with less staff – perhaps even making it 24 hours – and to connect all these island solutions to form the big picture.” Particularly in larger urban hospitals and more standardised disciplines, we can already begin to sketch that image. Microbiology, for all the difficulties it presents, is beginning to catch up with chemistry, where almost all samples are automatically verified in the laboratory information system without technologist involvement. Lenk also notes that blood tests and cultures have been highly automated for many years. That doesn’t mean lab staff, or even device manufacturers, are prepared for the changes that come with embracing automation and digitisation. As Ledeboer explains, the hardware “nuts and bolts” of automation only become useful when labs redesign their processes to make use of them. He doesn’t downplay what that entails. “If you want your automation project to succeed, you can’t try to fit automation into your current workflow,” he says. “You really have to look at your workflows and blow them up, if you will, to make them much more suitable and much more compatible for an automated laboratory.” To start, that actually means leaving the lab. Prospective automaters need to follow their specimens back to the source to adapt and standardise the way they are collected across the hospital or health system – swapping traditional cotton swabs for flocked swabs that are better able to release material into a liquid state, for instance. So begins a delicate journey of self- discovery. Doctors and nurses are likely to have a few questions about these new commandments, while a number of a clinical laboratory’s SOPs and best practices might have as much to do with the quirks and preferences of the people that have worked there as the quality of its outputs. “We had a lot of resistance because every tech has a slight variation in how they manage their bench or how they pull their plates, and we can’t have that anymore when it comes to automation,” says Ledeboer, his words taking on an increasingly insistent rhythm. “Everybody has to do the same thing. You can’t build your automation to have a unique process for tech one, and a unique process for tech two.”


Benefits of an automated future Since Ledeboer’s lab began its transformation before there was much data about the positive impact of automation on microbiology, he was forced to take a step-by-step approach. This involved starting with the most standardisable cultures (urine and surveillance swabs), and parlaying success in those areas into approval for the more difficult aspects of


32%


Proportion of time technicians in clinical microbiology labs spend on manual tasks.


Clinics in Laboratory Medicine


7%


Proportion of unfilled lab technician roles in the US between 2016 and 2018.


$1.2m


Upper limit of labour savings that implementation of TLA platforms could bring to US microbiology labs.


Journal of Clinical Microbiology 31


Page 1  |  Page 2  |  Page 3  |  Page 4  |  Page 5  |  Page 6  |  Page 7  |  Page 8  |  Page 9  |  Page 10  |  Page 11  |  Page 12  |  Page 13  |  Page 14  |  Page 15  |  Page 16  |  Page 17  |  Page 18  |  Page 19  |  Page 20  |  Page 21  |  Page 22  |  Page 23  |  Page 24  |  Page 25  |  Page 26  |  Page 27  |  Page 28  |  Page 29  |  Page 30  |  Page 31  |  Page 32  |  Page 33  |  Page 34  |  Page 35  |  Page 36  |  Page 37  |  Page 38  |  Page 39  |  Page 40  |  Page 41  |  Page 42  |  Page 43  |  Page 44  |  Page 45  |  Page 46  |  Page 47  |  Page 48  |  Page 49  |  Page 50  |  Page 51  |  Page 52  |  Page 53  |  Page 54  |  Page 55  |  Page 56  |  Page 57  |  Page 58  |  Page 59