title: The automated clinical microbiology laboratory: fact or fantasy?
abstract: Automated chemistry laboratories dependent on robotic processes are the standard in both academic and large community hospital settings. Diagnostic microbiology manufacturers are betting that robotics will be used for specimen processing, plate reading, and organism identification in the near future. These systems are highly complex and have large footprints and hefty price tags. However, they are touted as being more efficient, rapid, and accurate than standard processes. Certain features, such as image collection, are highly innovative. Hospital administrators may be swayed to institute these new systems because of the promise of the need for fewer skilled workers, higher throughput, and greater efficiency. They also may be swayed by the fact that workers with the requisite clinical microbiology skills are becoming more difficult to find, and this technology should allow fewer skilled workers to handle larger numbers of cultures. In this Point-Counterpoint, Nate Ledeboer, Medical Director, Clinical Microbiology and Molecular Diagnostics, Dynacare Laboratories, and Froedtert Hospital, Milwaukee, WI, will explain why he believes that this approach will become widespread, while Steve Dallas of the University of Texas Health Science Center San Antonio explains why he thinks that this automation may not become widely used.
authors.affiliation: Department of Pathology, Medical College of Wisconsin, and Dynacare Laboratories, Milwaukee, Wisconsin, USA nledeboe@mcw.edu dallass@uthscsa.edu.
authors.forename: Nathan A
authors.initials: NA
authors.lastname: Ledeboer
authors.affiliation: Department of Clinical Laboratory Sciences, UT Health Science Center San Antonio, and Microbiology Laboratory, University Hospital, San Antonio, Texas, USA nledeboe@mcw.edu dallass@uthscsa.edu.
authors.forename: Steven D
authors.initials: SD
authors.lastname: Dallas
mesh_terms: D057205:Automation, Laboratory / Q000379:methods*; D006801:Humans; D008828:Microbiological Techniques / Q000379:methods* / Q000639:trends*; D013781:Texas