User:Shawndouglas/sandbox/sublevel1

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IBM 1130 desk-sized computer from the mid-1960s and '70s

Computers in the laboratory are not a recent phenomenon. The mid-1960s saw clinical laboratory computerization become increasingly popular[1][2][3][4][5], though that enthusiasm was often based on the potential of the computers themselves rather than their actual capabilities.[1] Researchers imagined potentials such as automatic specimen label generation, daily log and report management, instrument interfacing and data processing, results comparisons, and time management tools. It would take time for some of those potentials to be realized.[1]

In 1970, Temple University Medical School's Marion Ball, M.A., an assistant professor in the Department of Medical Physics, conducted a survey of pathology directors in clinical laboratories that were using computers. Asking their opinions about the advantages and disadvantages of computerized systems in the lab, she received responses from directors in 15 U.S. states, as well as from three other countries. Responses included[6]:

The ability to rapidly prepare cumulative records and then to inspect them for possible errors through analysis trends has been proven to be of tremendous advantage in a number of laboratories. We can prevent errors in our analytical systems, but we are not prepared to prevent errors in the collecting of the sample, the mislabeling of the sample, or the accidental use of an incorrect sample. Thus, the ability to inspect data trends presents the only real tool that we currently have to pick out these kinds of errors. - Max E. Chilcote, Ph.D, Meyer Memorial Hospital Division

There is little argument about whether an operating computer system can be an advantage in a laboratory, but the most critical time is the installation and transition from a "manual" to a "computer" oriented laboratory. - Robert L. Habig, Duke University Medical Center

The most pressing future need for computerization of the laboratory lies in the area of medical diagnosis and guidance of the therapeutic management. This is where the physician's role for the future in the laboratory lies ... We will be gathering vast amounts of information on the health status of many individuals. We can then take advantage of large data processing computers to analyze this information and come up with patterns of disease states. - Leonard Jarett, M.D., Barnes Hospital

Reading about these potentials and opinions today, some 50 years later, we see both clear similarities and definite advances. For example, Habig's statement about transitioning from manual to more automated processes still rings true today: it can be nerve wracking and critical to get the transition right. Conversely, while the systems of decades past weren't able to "prevent errors in the collecting of the sample, the mislabeling of the sample, or the accidental use of an incorrect sample," modern laboratory informatics systems provide many assurances to sample management in the lab. In many cases, activities such as label generation, reporting, results analysis, workflow control, test ordering, and broad interoperability are commonplace in modern systems.[7] And those systems continue to advance, with machine learning now finding its way into a few laboratory data management and analysis workflows.[8][9]

We've come a long way since the 1960s, to a point where the question is no longer "can a computerized system help my lab?" but rather "how do I choose and implement an informatics system to help my lab?" What follows is information to help you with that question, while considering the technology, features, security, cost, implementation, and vendor guarantees that come with such a system.

References

  1. 1.0 1.1 1.2 Krieg, A.F. (1974). "Chapter 30: Clinical Laboratory Computerization". In Davidsohn, I.; Henry, J.B.. Clinical Diagnosis by Laboratory Methods. W.B. Saunders Company. pp. 1340–58. ISBN 0721629229. 
  2. Flynn, F.V. (1965). "Computer-assisted processing of bio-chemical test data". In Atkins, H.J.B.. Progress in Medical Computing. Blackwell Science Ltd. p. 46. ISBN 0632001801. 
  3. Williams, G.Z. (1964). "The Use of Data Processing and Automation in Clinical Pathology". Military Medicine 129 (6): 502–9. doi:10.1093/milmed/129.6.502. 
  4. Hicks, G.P.; Gieschen, M.M.; Slack, W.V. et al. (1966). "Routine Use of a Small Digital Computer in the Clinical Laboratory". JAMA 196 (11): 973–78. doi:10.1001/jama.1966.03100240107021. 
  5. Straumfjord, J.V.; Spraberry, M.N.; Biggs, H.G.; Noto, T.A. (1967). "Electronic Data Processing System for Clinical Laboratories: A System Used for All Laboratory Sections". American Journal of Clinical Pathology 47 (5_ts): 661–76. doi:10.1093/ajcp/47.5_ts.661. 
  6. Ball, M.J. (1970). "A Survey of Field Experience in Clinical Laboratory Computerization". Laboratory Medicine 1 (11): 25–27, 49–51. doi:10.1093/labmed/1.11.25. 
  7. Jones, R.G.; Johnson, O.A.; Batstone, G. (2014). "Informatics and the Clinical Laboratory". The Clinical Biochemist Reviews 35 (3): 177–92. PMC PMC4204239. PMID 25336763. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4204239. 
  8. Burton, R. (19 July 2018). "NHS Laboratories Need Data Science". Towards Data Science. https://towardsdatascience.com/nhs-laboratories-need-data-science-c93f7983302c. Retrieved 18 November 2021. 
  9. Cuff, J. (18 June 2018). "Augmenting Pathology Labs with Big Data and Machine Learning". The Next Platform. https://www.nextplatform.com/2018/06/19/augmenting-pathology-labs-with-big-data-and-machine-learning/. Retrieved 18 November 2021.