Week 4: Computers in the Workplace and How I Learned My Job Will Be Taken by an AI

    For this week, I'll be describing computers' role in healthcare. I'm currently a Medical Laboratory Technician for the U.S. Army, and we recently transitioned to a new comprehensive medical record system across the entire Department of Defense (DoD) designed by Cerner called MHS Genesis.

    Computers in healthcare have been vital for a long time, as medical records, patient charts, laboratory results, and more are all stored and transferred digitally these days. Prior to this transition, the DoD used several different programs to conduct different aspects of patient care, which had limited or non-existent communication with each other. The records were also stored locally, so to transfer a Service Member's (SM) medical records when they left for a new duty station, the SM had to hand-carry their physical record with them and deliver it to the Medical records department at their new treatment facility.

    The transition to MHS Genesis changed all of that. It was commissioned to be a unified medical records system where a SM's medical record could be accessed from any DoD facility, regardless of service component or type of facility. It uses an app-based design, where there are still different programs for each kind of clinic, but the apps communicate with one another in a unified sandbox so that a laboratory test ordered in Powerchart (the provider's portal and charting program) can be accessed and logged in the P0630 AppBar (a suite of apps related to various aspects of laboratory services, including records management, reporting, blood banking, and sample transfer to other facilities), and the results entered from the laboratory side can readily be accessed in the patient's chart.

    A lab tech needs to be computer-literate in this day and age because all testing is ordered and resulted through computers. All sample transfers are managed through the computer system, all of the analyzers are computerized and interfaced with this system, and more and more maintenance manuals and Standard Operating Procedures (SOPs) are being digitized to cut down on the space needed to store paper records in the lab.

    With more and more processes being automated within the laboratory by computers, I wouldn't be surprised if the next 10 years see the adoption of AI implementation in the laboratory to perform some tests, such as manual differential review or cancer identification. As early as 2013, a program called BakeryScan was originally designed to quickly differentiate between different pastries and sandwiches sold by a Japanese bakery, and by 2017 the technology was adapted into Cyto-Aiscan to be able to tell the subtle morphological differences in cancerous cells (Somers, 2021). I predict we'll begin to see more of that kind of technology being adapted into the processes to conduct testing that used to require a human technician, and to monitor Quality Control data, completely replacing a full-time data analysis position that currently requires an experienced tech possessing a Bachelors degree.

References

Somers, J. (2021, March 18). The Pastry A.I. That learned to Fight Cancer. The New Yorker. https://www.newyorker.com/tech/annals-of-technology/the-pastry-ai-that-learned-to-fight-cancer.