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| [[File:IBM 1130 (16758008839).jpg|right|thumb|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<ref name="KriegClinical74">{{cite book |chapter=Chapter 30: Clinical Laboratory Computerization |title=Clinical Diagnosis by Laboratory Methods |author=Krieg, A.F. |editor=Davidsohn, I.; Henry, J.B. |publisher=W.B. Saunders Company |pages=1340–58 |year=1974 |isbn=0721629229}}</ref><ref name="FlynnComputer65">{{cite book |chapter=Computer-assisted processing of bio-chemical test data |title=Progress in Medical Computing |author=Flynn, F.V. |editor=Atkins, H.J.B. |publisher=Blackwell Science Ltd |page=46 |year=1965 |isbn=0632001801}}</ref><ref name="WilliamsTheUse64">{{cite journal |title=The Use of Data Processing and Automation in Clinical Pathology |journal=Military Medicine |author=Williams, G.Z. |volume=129 |issue=6 |pages=502–9 |year=1964 |doi=10.1093/milmed/129.6.502}}</ref><ref name="HicksRoutine66">{{cite journal |title=Routine Use of a Small Digital Computer in the Clinical Laboratory |journal=JAMA |author=Hicks, G.P.; Gieschen, M.M.; Slack, W.V. et al. |volume=196 |issue=11 |pages=973–78 |year=1966 |doi=10.1001/jama.1966.03100240107021}}</ref><ref name="StraumfjordElectronic67">{{cite journal |title=Electronic Data Processing System for Clinical Laboratories: A System Used for All Laboratory Sections |journal=American Journal of Clinical Pathology |author=Straumfjord, J.V.; Spraberry, M.N.; Biggs, H.G.; Noto, T.A. |volume=47 |issue=5_ts |pages=661–76 |year=1967 |doi=10.1093/ajcp/47.5_ts.661}}</ref>, though that enthusiasm was often based on the potential of the computers themselves rather than their actual capabilities.<ref name="KriegClinical74" /> 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.<ref name="KriegClinical74" /> | | What exactly is a [[laboratory information system]] (LIS) or [[laboratory information management system]] (LIMS) anyway? Do I need one? What options are available and how do I compare them? What about a request for information (RFI), request for proposal (RFP), or request for quotation (RFQ)? These are questions [[laboratory]] professionals typically ponder upon finding themselves charged with the mission of finding software for their lab. For many the task can be a daunting proposition. |
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| 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<ref name="BallASurvey70">{{cite journal |title=A Survey of Field Experience in Clinical Laboratory Computerization |journal=Laboratory Medicine |author=Ball, M.J. |volume=1 |issue=11 |pages=25–27, 49–51 |year=1970 |doi=10.1093/labmed/1.11.25}}</ref>:
| | You may know the workflow-related needs of your laboratory, but perhaps you don't know much about [[Information management|data management]] solutions like LIS and LIMS, leaving you intimidated by all the options. You'll first need to gauge your lab's informatics needs in order to determine which products are worth investigating further. Of course your lab's analysis requirements, reporting and data sharing constraints, instrument interfacing needs, [[Barcode|barcoding]] and tracking requirements, quality assurance processes, etc. are very important factors. But these systems vary in numerous ways, and other important factors exist. Price should certainly be considered, although value is ultimately more important than a low price. Other important questions that get asked include: |
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| <blockquote>''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</blockquote>
| | *Should we purchase software licenses or "rent" the software via a subscription-based model? |
| | *Does the software need to be on-site, or is a [[Software as a service|SaaS]] hosted option more practical? |
| | *Is a modular or complete system better for us? |
| | *What is the best licensing/rental scheme for us? Should we consider site, named user, concurrent user, or workstation licenses? |
| | *Is the company qualified and trustworthy? |
| | *What functionality is available to help our lab not only accomplish workflow tasks but also remain regulatory compliant? |
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| <blockquote>''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</blockquote>
| | These and other questions are addressed in this chapter. |
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| <blockquote>''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</blockquote>
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| 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.<ref name="JonesInformatics14">{{cite journal |title=Informatics and the Clinical Laboratory |journal=The Clinical Biochemist Reviews |author=Jones, R.G.; Johnson, O.A.; Batstone, G. |volume=35 |issue=3 |pages=177–92 |year=2014 |pmid=25336763 |pmc=PMC4204239}}</ref> And those systems continue to advance, with [[machine learning]] now finding its way into a few laboratory data management and [[Data analysis|analysis]] workflows.<ref name="BurtonNHS18">{{cite web |url=https://towardsdatascience.com/nhs-laboratories-need-data-science-c93f7983302c |title=NHS Laboratories Need Data Science |author=Burton, R. |work=Towards Data Science |date=19 July 2018 |accessdate=18 November 2021}}</ref><ref name="CuffAugment18">{{cite web |url=https://www.nextplatform.com/2018/06/19/augmenting-pathology-labs-with-big-data-and-machine-learning/ |title=Augmenting Pathology Labs with Big Data and Machine Learning |author=Cuff, J. |work=The Next Platform |date=18 June 2018 |accessdate=18 November 2021}}</ref>
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| 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.
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| ==References== | | ==References== |
| {{Reflist|colwidth=30em}} | | {{Reflist|colwidth=30em}} |
What exactly is a laboratory information system (LIS) or laboratory information management system (LIMS) anyway? Do I need one? What options are available and how do I compare them? What about a request for information (RFI), request for proposal (RFP), or request for quotation (RFQ)? These are questions laboratory professionals typically ponder upon finding themselves charged with the mission of finding software for their lab. For many the task can be a daunting proposition.
You may know the workflow-related needs of your laboratory, but perhaps you don't know much about data management solutions like LIS and LIMS, leaving you intimidated by all the options. You'll first need to gauge your lab's informatics needs in order to determine which products are worth investigating further. Of course your lab's analysis requirements, reporting and data sharing constraints, instrument interfacing needs, barcoding and tracking requirements, quality assurance processes, etc. are very important factors. But these systems vary in numerous ways, and other important factors exist. Price should certainly be considered, although value is ultimately more important than a low price. Other important questions that get asked include:
- Should we purchase software licenses or "rent" the software via a subscription-based model?
- Does the software need to be on-site, or is a SaaS hosted option more practical?
- Is a modular or complete system better for us?
- What is the best licensing/rental scheme for us? Should we consider site, named user, concurrent user, or workstation licenses?
- Is the company qualified and trustworthy?
- What functionality is available to help our lab not only accomplish workflow tasks but also remain regulatory compliant?
These and other questions are addressed in this chapter.
References
