Difference between revisions of "User:Shawndouglas/sandbox/sublevel12"

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*'''Support for notations on primary and derivative assets, as well as other entities''': Given the above about primary specimens and the culturing of derivatives, it's vital that careful note-taking is performed at the various stages of analysis and interpretation by microbiologists. This electronic note-taking—in the past performed on physical note cards<ref name="RhoadsClin14" />—in turn can improve quality and patient outcomes. As such, many informatics systems will provide note-taking functions at granular levels for a variety of entities in the system.<ref name="RhoadsClin14" />
*'''Support for notations on primary and derivative assets, as well as other entities''': Given the above about primary specimens and the culturing of derivatives, it's vital that careful note-taking is performed at the various stages of analysis and interpretation by microbiologists. This electronic note-taking—in the past performed on physical note cards<ref name="RhoadsClin14" />—in turn can improve quality and patient outcomes. As such, many informatics systems will provide note-taking functions at granular levels for a variety of entities in the system.<ref name="RhoadsClin14" />
*'''More robust, standardized, optimized, and automated result reporting''': Microbiology labs in particular have multiple requirements and methods for reporting analytical and interpretive results, compared to other clinical laboratory disciplines, which usually report in a largely quantitative way. The microbiology lab will need report and interpret complex qualitative, semi-quantitative, and quantitative data and information, using long and repetitive text strings (e.g., ''Staphylococcus epidermidis'') in both preliminary and final results. Ensuring ease-of-use with keyboard shortcuts for long, repetitive text strings, while also ensuring succinct, standardized terminology and clear and accurate test results or interpretations is imperative. A LIMS can apply a more "synoptic" approach to reporting typically found with surgical pathology, supporting highly configurable layouts, the enforcement of standardized nomenclature, and appropriate result highlighting mechanisms to ensure more confident report interpretation by both microbiologists and treating physicians.<ref name="RhoadsClin14" />
*'''More robust, standardized, optimized, and automated result reporting''': Microbiology labs in particular have multiple requirements and methods for reporting analytical and interpretive results, compared to other clinical laboratory disciplines, which usually report in a largely quantitative way. The microbiology lab will need report and interpret complex qualitative, semi-quantitative, and quantitative data and information, using long and repetitive text strings (e.g., ''Staphylococcus epidermidis'') in both preliminary and final results. Ensuring ease-of-use with keyboard shortcuts for long, repetitive text strings, while also ensuring succinct, standardized terminology and clear and accurate test results or interpretations is imperative. A LIMS can apply a more "synoptic" approach to reporting typically found with surgical pathology, supporting highly configurable layouts, the enforcement of standardized nomenclature, and appropriate result highlighting mechanisms to ensure more confident report interpretation by both microbiologists and treating physicians.<ref name="RhoadsClin14" />
*'''Robust support for interfacing with an immense variety of systems and instruments''': While system and instrument interfacing is largely ''de facto'' required out of most any LIMS, this interfacing is essential to a majority of medical microbiology labs. Communication between it and any [[hospital information system]] (HIS), for example, must be unhindered and clear such that analytical and interpretive orders placed in the HIS make their way to the LIMS, and results from the lab are readily transferred back to the HIS in a standardized and readable format. This interfacing must be verified periodically to ensure high levels of quality and patient outcomes. As such, the microbiology LIMS must have robust interfacing support using standardized protocols that ensure clear and rapid bidirectional communication between other informatics systems and laboratory instruments.<ref name="RhoadsClin14" /> This includes total laboratory automation (TLA) instruments and systems, which have gradually become more viable for the microbiology lab.<ref name="RhoadsClin14" /><ref name="FutrellAddress23" /><ref>{{Cite journal |last=Antonios |first=Kritikos |last2=Croxatto |first2=Antony |last3=Culbreath |first3=Karissa |date=2021-12-30 |title=Current State of Laboratory Automation in Clinical Microbiology Laboratory |url=https://academic.oup.com/clinchem/article/68/1/99/6490228 |journal=Clinical Chemistry |language=en |volume=68 |issue=1 |pages=99–114 |doi=10.1093/clinchem/hvab242 |issn=0009-9147}}</ref> Additionally, as the early promise of automated microbiology image analysis<ref name="RhoadsClin14" /> has progressed to full-fledged systems with [[artificial intelligence]] (AI) components<ref name="SandleEnhanc21">{{cite web |url=https://www.europeanpharmaceuticalreview.com/article/166302/enhancing-rapid-microbiology-methods-how-ai-is-shaping-microbiology/ |title=Enhancing rapid microbiology methods: how AI is shaping microbiology |author=Sandle, T. |work=European Pharmaceutical Review |date=22 December 2021 |accessdate=17 April 2024}}</ref><ref name="GilesSciBiomicv3_24">{{cite web |url=https://www.biomic.com/biomic-v3.html |title=BIOMIC V3 |publisher=Giles Scientific, Inc |date=2024 |accessdate=17 April 2024}}</ref>, the modern microbiology LIMS need to effectively interface with these systems too.
*'''Robust support for interfacing with a vast variety of systems and instruments''': While system and instrument interfacing is largely ''de facto'' required out of most any LIMS, this interfacing is essential to and more complex for a majority of medical microbiology labs. Communication between the LIMS and any [[hospital information system]] (HIS), for example, must be unhindered and clear such that analytical and interpretive orders placed in the HIS make their way to the LIMS, and results from the lab are readily transferred back to the HIS in a standardized and readable format. This interfacing must be verified periodically to ensure high levels of quality and patient outcomes. As such, the microbiology LIMS must have robust interfacing support using standardized protocols that ensure clear and rapid bidirectional communication between other informatics systems and laboratory instruments.<ref name="RhoadsClin14" /> This includes total laboratory automation (TLA) instruments and systems, which have gradually become more viable for the microbiology lab.<ref name="RhoadsClin14" /><ref name="FutrellAddress23" /><ref>{{Cite journal |last=Antonios |first=Kritikos |last2=Croxatto |first2=Antony |last3=Culbreath |first3=Karissa |date=2021-12-30 |title=Current State of Laboratory Automation in Clinical Microbiology Laboratory |url=https://academic.oup.com/clinchem/article/68/1/99/6490228 |journal=Clinical Chemistry |language=en |volume=68 |issue=1 |pages=99–114 |doi=10.1093/clinchem/hvab242 |issn=0009-9147}}</ref> Additionally, as the early promise of automated microbiology image analysis<ref name="RhoadsClin14" /> has progressed to full-fledged systems with [[artificial intelligence]] (AI) components<ref name="SandleEnhanc21">{{cite web |url=https://www.europeanpharmaceuticalreview.com/article/166302/enhancing-rapid-microbiology-methods-how-ai-is-shaping-microbiology/ |title=Enhancing rapid microbiology methods: how AI is shaping microbiology |author=Sandle, T. |work=European Pharmaceutical Review |date=22 December 2021 |accessdate=17 April 2024}}</ref><ref name="GilesSciBiomicv3_24">{{cite web |url=https://www.biomic.com/biomic-v3.html |title=BIOMIC V3 |publisher=Giles Scientific, Inc |date=2024 |accessdate=17 April 2024}}</ref>, the modern microbiology LIMS need to effectively interface with these systems too. Finally, connections to a wide variety of third-party [[database]]s, used for identification of microorganisms, are important and must be addressed by any microbiology LIMS.
*'''Analytical and reporting support for susceptibility testing and antibiograms''': An antibiogram is a cumulative summary or "overall profile of [''in vitro''] susceptibility testing results for a specific microorganism to an array of antimicrobial drugs," often given in a tabular form.<ref name="UnivMNHowTo20">{{cite web |url=https://arsi.umn.edu/sites/arsi.umn.edu/files/2020-02/How_to_Use_a_Clinical_Antibiogram_26Feb2020_Final.pdf |format=PDF |title=How to Use a Clinical Antibiogram |author=Antimicrobial Resistance and Stewardship Initiative, University of Minnesota |date=February 2020 |accessdate=17 April 2024}}</ref> There are multiple approaches to antibiograms for a wide variety of susceptibility testing, common to microbiology labs.<ref>{{Cite journal |last=Gajic |first=Ina |last2=Kabic |first2=Jovana |last3=Kekic |first3=Dusan |last4=Jovicevic |first4=Milos |last5=Milenkovic |first5=Marina |last6=Mitic Culafic |first6=Dragana |last7=Trudic |first7=Anika |last8=Ranin |first8=Lazar |last9=Opavski |first9=Natasa |date=2022-03-23 |title=Antimicrobial Susceptibility Testing: A Comprehensive Review of Currently Used Methods |url=https://www.mdpi.com/2079-6382/11/4/427 |journal=Antibiotics |language=en |volume=11 |issue=4 |pages=427 |doi=10.3390/antibiotics11040427 |issn=2079-6382 |pmc=PMC9024665 |pmid=35453179}}</ref> While it's not common for a LIMS or LIS to have extensive data analysis capabilities, some may support the sometimes complex work of generating antibiograms.<ref name="RhoadsClin14" /><ref name="SlclabVideos23" /><ref name="BGASoftMolec23" /> At a minimum, the LIMS should have robust reporting capabilities able to handle the nuances of susceptibility testing and antibiograms, particularly to the standard CLSI M39 ''Analysis and Presentation of Cumulative Antimicrobial Susceptibility Test Data''.<ref name="RhoadsClin14" /><ref>{{Cite journal |last=Simner |first=Patricia J. |last2=Hindler |first2=Janet A. |last3=Bhowmick |first3=Tanaya |last4=Das |first4=Sanchita |last5=Johnson |first5=J. Kristie |last6=Lubers |first6=Brian V. |last7=Redell |first7=Mark A. |last8=Stelling |first8=John |last9=Erdman |first9=Sharon M. |date=2022-10-19 |editor-last=Humphries |editor-first=Romney M. |title=What’s New in Antibiograms? Updating CLSI M39 Guidance with Current Trends |url=https://journals.asm.org/doi/10.1128/jcm.02210-21 |journal=Journal of Clinical Microbiology |language=en |volume=60 |issue=10 |pages=e02210–21 |doi=10.1128/jcm.02210-21 |issn=0095-1137 |pmc=PMC9580356 |pmid=35916520}}</ref> Ideally, the LIMS can even run the analyses themselves, pulling data from the LIMS and HIS, but again this may not be common.
*'''Analytical and reporting support for susceptibility testing and antibiograms''': An antibiogram is a cumulative summary or "overall profile of [''in vitro''] susceptibility testing results for a specific microorganism to an array of antimicrobial drugs," often given in a tabular form.<ref name="UnivMNHowTo20">{{cite web |url=https://arsi.umn.edu/sites/arsi.umn.edu/files/2020-02/How_to_Use_a_Clinical_Antibiogram_26Feb2020_Final.pdf |format=PDF |title=How to Use a Clinical Antibiogram |author=Antimicrobial Resistance and Stewardship Initiative, University of Minnesota |date=February 2020 |accessdate=17 April 2024}}</ref> There are multiple approaches to antibiograms for a wide variety of susceptibility testing, common to microbiology labs.<ref>{{Cite journal |last=Gajic |first=Ina |last2=Kabic |first2=Jovana |last3=Kekic |first3=Dusan |last4=Jovicevic |first4=Milos |last5=Milenkovic |first5=Marina |last6=Mitic Culafic |first6=Dragana |last7=Trudic |first7=Anika |last8=Ranin |first8=Lazar |last9=Opavski |first9=Natasa |date=2022-03-23 |title=Antimicrobial Susceptibility Testing: A Comprehensive Review of Currently Used Methods |url=https://www.mdpi.com/2079-6382/11/4/427 |journal=Antibiotics |language=en |volume=11 |issue=4 |pages=427 |doi=10.3390/antibiotics11040427 |issn=2079-6382 |pmc=PMC9024665 |pmid=35453179}}</ref> While it's not common for a LIMS or LIS to have extensive data analysis capabilities, some may support the sometimes complex work of generating antibiograms.<ref name="RhoadsClin14" /><ref name="SlclabVideos23" /><ref name="BGASoftMolec23" /> At a minimum, the LIMS should have robust reporting capabilities able to handle the nuances of susceptibility testing and antibiograms, particularly to the standard CLSI M39 ''Analysis and Presentation of Cumulative Antimicrobial Susceptibility Test Data''.<ref name="RhoadsClin14" /><ref>{{Cite journal |last=Simner |first=Patricia J. |last2=Hindler |first2=Janet A. |last3=Bhowmick |first3=Tanaya |last4=Das |first4=Sanchita |last5=Johnson |first5=J. Kristie |last6=Lubers |first6=Brian V. |last7=Redell |first7=Mark A. |last8=Stelling |first8=John |last9=Erdman |first9=Sharon M. |date=2022-10-19 |editor-last=Humphries |editor-first=Romney M. |title=What’s New in Antibiograms? Updating CLSI M39 Guidance with Current Trends |url=https://journals.asm.org/doi/10.1128/jcm.02210-21 |journal=Journal of Clinical Microbiology |language=en |volume=60 |issue=10 |pages=e02210–21 |doi=10.1128/jcm.02210-21 |issn=0095-1137 |pmc=PMC9580356 |pmid=35916520}}</ref> Ideally, the LIMS can even run the analyses themselves, pulling data from the LIMS and HIS, but again this may not be common.
*'''Decision support systems for medical microbiology''': Just as there are [[decision support system]]s (DSS) built into some LIMS that can guide pharmacogenomics (PGx) decisions made with the aid of [[molecular diagnostics]] testing<ref name="EmgenexLIS24">{{cite web |url=https://www.emgenex.com/lis |title=Redefining LIS |publisher=Emgenex, Inc |date=2024 |accessdate=17 April 2024}}</ref>, a handful of LIMS or HIS options may incorporate DSS to better guide microbiology-based decisions on antibiotic prescription.<ref name="RhoadsClin14" /><ref name="EgliDigital20">{{Cite journal |last=Egli |first=A. |last2=Schrenzel |first2=J. |last3=Greub |first3=G. |date=2020-10 |title=Digital microbiology |url=https://linkinghub.elsevier.com/retrieve/pii/S1198743X20303670 |journal=Clinical Microbiology and Infection |language=en |volume=26 |issue=10 |pages=1324–1331 |doi=10.1016/j.cmi.2020.06.023 |pmc=PMC7320868 |pmid=32603804}}</ref> (DSS has already been used for other purposes in LIMS.<ref>{{Cite journal |last=Díaz-Gimenez |first=Macarena |last2=Carratala Calvo |first2=Arturo |last3=Vinyals-Bellido |first3=Inmaculada |last4=Corchon-Peyrallo |first4=Africa |last5=Hervas-Romero |first5=Ausias |last6=Pozo-Giraldez |first6=Adela |last7=Rodriguez-Borja |first7=Enrique |date=2021-06-15 |title=Decision support system through automatic algorithms and electronic request in diagnosis of anaemia for primary care patients |url=https://www.biochemia-medica.com/en/journal/31/2/10.11613/BM.2021.020702 |journal=Biochemia medica |volume=31 |issue=2 |pages=250–257 |doi=10.11613/BM.2021.020702 |pmc=PMC8047786 |pmid=33927552}}</ref><ref>{{Cite web |date=2022 |title=Sanela LIMS (Lab Information Management System) |url=https://sanelahealth.com/lims-software.html |publisher=Sanela Health |accessdate=17 April 2024}}</ref>) Those DSS may be guided with the help of supervised [[machine learning]] (ML) algorithms or other AI components.<ref name="EgliDigital20" /> However, such systems have their own acquisition and implementation costs, and maintaining the DSS with relevant data at regular intervals to ensure the DSS' usefulness adds additional costs the microbiology lab must weigh.<ref name="RhoadsClin14" />
*'''Decision support systems for medical microbiology''': Just as there are [[decision support system]]s (DSS) built into some LIMS that can guide pharmacogenomics (PGx) decisions made with the aid of [[molecular diagnostics]] testing<ref name="EmgenexLIS24">{{cite web |url=https://www.emgenex.com/lis |title=Redefining LIS |publisher=Emgenex, Inc |date=2024 |accessdate=17 April 2024}}</ref>, a handful of LIMS or HIS options may incorporate DSS to better guide microbiology-based decisions on antibiotic prescription.<ref name="RhoadsClin14" /><ref name="EgliDigital20">{{Cite journal |last=Egli |first=A. |last2=Schrenzel |first2=J. |last3=Greub |first3=G. |date=2020-10 |title=Digital microbiology |url=https://linkinghub.elsevier.com/retrieve/pii/S1198743X20303670 |journal=Clinical Microbiology and Infection |language=en |volume=26 |issue=10 |pages=1324–1331 |doi=10.1016/j.cmi.2020.06.023 |pmc=PMC7320868 |pmid=32603804}}</ref> (DSS has already been used for other purposes in LIMS.<ref>{{Cite journal |last=Díaz-Gimenez |first=Macarena |last2=Carratala Calvo |first2=Arturo |last3=Vinyals-Bellido |first3=Inmaculada |last4=Corchon-Peyrallo |first4=Africa |last5=Hervas-Romero |first5=Ausias |last6=Pozo-Giraldez |first6=Adela |last7=Rodriguez-Borja |first7=Enrique |date=2021-06-15 |title=Decision support system through automatic algorithms and electronic request in diagnosis of anaemia for primary care patients |url=https://www.biochemia-medica.com/en/journal/31/2/10.11613/BM.2021.020702 |journal=Biochemia medica |volume=31 |issue=2 |pages=250–257 |doi=10.11613/BM.2021.020702 |pmc=PMC8047786 |pmid=33927552}}</ref><ref>{{Cite web |date=2022 |title=Sanela LIMS (Lab Information Management System) |url=https://sanelahealth.com/lims-software.html |publisher=Sanela Health |accessdate=17 April 2024}}</ref>) Those DSS may be guided with the help of supervised [[machine learning]] (ML) algorithms or other AI components.<ref name="EgliDigital20" /> However, such systems have their own acquisition and implementation costs, and maintaining the DSS with relevant data at regular intervals to ensure the DSS' usefulness adds additional costs the microbiology lab must weigh.<ref name="RhoadsClin14" />

Revision as of 22:49, 17 April 2024

Sandbox begins below

Daily Operations in the Microbiology Lab Aboard USNS Comfort (49826560406).jpg

Title: What are the key elements of a LIMS for medical microbiology?

Author for citation: Shawn E. Douglas

License for content: Creative Commons Attribution-ShareAlike 4.0 International

Publication date: April 2024

Introduction

This brief topical article will examine the informatics needs of the medical microbiology lab, specifically addressing the base set of laboratory information management system (LIMS) or laboratory information system (LIS) functionality (i.e., system requirements) that is critical to fulfilling the information management and workflow requirements of this type of lab. (Going forward, for simplicity, this article will discuss these requirements largely in the scope of a LIMS; however, note that an LIS is equally viable here.) Additional unique requirements will also be briefly discussed.

Note: Any citation leading to a software vendor's site is not to be considered a recommendation for that vendor. The citation should however still stand as a representational example of what vendors are implementing in their systems.

Base LIMS requirements for medical microbiology labs

Like other labs, medical microbiology labs increasingly require an informatics solution that meets all or most of its workflow requirements. These requirements are often driven by standardized test methods, in turn driven by regulations and accreditation requirements. This requires a pre-configured and future-configurable solution that enables medical microbiology personnel to quickly select and use standardized test methods and forms, and make the changes they need to those methods and forms if those changes make sense within the overall data structure of the LIMS.

What follows is a list of fundamental LIMS functionality important to most any medical microbiology laboratory, with a majority of that functionality found in many vendor software solutions.[1][2][3][4]

Test, sample, and result management

  • Sample log-in and management, with support for unique IDs
  • Sample batching
  • Barcode and RFID support
  • End-to-end sample and inventory tracking
  • Pre-defined and configurable industry-specific test and method management for a variety of physical, mechanical, and chemical analyses
  • Pre-defined and configurable industry-specific workflows
  • Configurable screens and data fields
  • Specification management
  • Test, sampling, instrument, etc. scheduling and assignment
  • Test requesting
  • Data import, export, and archiving
  • Robust query tools
  • Analytical tools, including data visualization, statistical analysis, and data mining tools
  • Document and image management
  • Project management
  • Facility and sampling site management
  • Storage management and monitoring

Quality, security, and compliance

  • Quality assurance / quality control mechanisms
  • Mechanisms for compliance with ISO/IEC 17025, ISO 9000, ASTM, A2LA, ANAB, and other requirements
  • Result, method, protocol, batch, and material validation, review, and release
  • Data validation
  • Trend and control charting for statistical analysis and measurement of uncertainty
  • User qualification, performance, and training management
  • Audit trails and chain of custody support
  • Configurable and granular role-based security
  • Configurable system access and use (i.e., authentication requirements, account usage rules, account locking, etc.)
  • Electronic signature support
  • Data encryption and secure communication protocols
  • Archiving and retention of data and information
  • Configurable data backups
  • Status updates and alerts
  • Incident and non-conformance notification, tracking, and management

Operations management and reporting

  • Configurable dashboards for monitoring, by material, process, facility, etc.
  • Customizable rich-text reporting, with multiple supported output formats
  • Custom and industry-specific reporting, including certificates of analysis (CoAs)
  • Email integration
  • Bi-directional instrument interfacing and data management
  • Third-party software interfacing (e.g., scientific data management system [SDMS], other databases)
  • Data import, export, and archiving
  • Instrument calibration and maintenance tracking
  • Inventory and material management
  • Supplier/vendor/customer management
  • Customer portal

Specialty LIMS requirements

Some laboratory informatics software vendors are addressing medical microbiology laboratories' needs beyond the features of a basic all-purpose LIMS. A standard LIMS tailored for materials testing may already contribute to some of these wider organizational functions, as well as more advanced laboratory workflow requirements, but many may not, or may vary in what additional functionality they provide. In that regard, a materials testing LIMS vendor may also include specialized functionality that assists these labs. This includes the provision of:

  • Derivative asset linking and tracking: Unlike many other labs in the biomedical sciences, a medical microbiology lab will end up creating (e.g., via cell culture) multiple derivative assets from a single accessioned specimen. For example, a specimen suspected of polymicrobial infection may require derivative specimens representing "aerobic bacteria, anaerobic bacteria, mycobacteria, and/or fungi, and all of these need to be linked to the original accession number."[1] As Rhoads et al. note, "properly handling the electronic information associated with a sample, such as tracking its derivatives, modifying descriptions of its derivatives, and linking its derivatives with their accession number, is a unique and essential aspect of the microbiology LIS."[1]
  • Support for notations on primary and derivative assets, as well as other entities: Given the above about primary specimens and the culturing of derivatives, it's vital that careful note-taking is performed at the various stages of analysis and interpretation by microbiologists. This electronic note-taking—in the past performed on physical note cards[1]—in turn can improve quality and patient outcomes. As such, many informatics systems will provide note-taking functions at granular levels for a variety of entities in the system.[1]
  • More robust, standardized, optimized, and automated result reporting: Microbiology labs in particular have multiple requirements and methods for reporting analytical and interpretive results, compared to other clinical laboratory disciplines, which usually report in a largely quantitative way. The microbiology lab will need report and interpret complex qualitative, semi-quantitative, and quantitative data and information, using long and repetitive text strings (e.g., Staphylococcus epidermidis) in both preliminary and final results. Ensuring ease-of-use with keyboard shortcuts for long, repetitive text strings, while also ensuring succinct, standardized terminology and clear and accurate test results or interpretations is imperative. A LIMS can apply a more "synoptic" approach to reporting typically found with surgical pathology, supporting highly configurable layouts, the enforcement of standardized nomenclature, and appropriate result highlighting mechanisms to ensure more confident report interpretation by both microbiologists and treating physicians.[1]
  • Robust support for interfacing with a vast variety of systems and instruments: While system and instrument interfacing is largely de facto required out of most any LIMS, this interfacing is essential to and more complex for a majority of medical microbiology labs. Communication between the LIMS and any hospital information system (HIS), for example, must be unhindered and clear such that analytical and interpretive orders placed in the HIS make their way to the LIMS, and results from the lab are readily transferred back to the HIS in a standardized and readable format. This interfacing must be verified periodically to ensure high levels of quality and patient outcomes. As such, the microbiology LIMS must have robust interfacing support using standardized protocols that ensure clear and rapid bidirectional communication between other informatics systems and laboratory instruments.[1] This includes total laboratory automation (TLA) instruments and systems, which have gradually become more viable for the microbiology lab.[1][4][5] Additionally, as the early promise of automated microbiology image analysis[1] has progressed to full-fledged systems with artificial intelligence (AI) components[6][7], the modern microbiology LIMS need to effectively interface with these systems too. Finally, connections to a wide variety of third-party databases, used for identification of microorganisms, are important and must be addressed by any microbiology LIMS.
  • Analytical and reporting support for susceptibility testing and antibiograms: An antibiogram is a cumulative summary or "overall profile of [in vitro] susceptibility testing results for a specific microorganism to an array of antimicrobial drugs," often given in a tabular form.[8] There are multiple approaches to antibiograms for a wide variety of susceptibility testing, common to microbiology labs.[9] While it's not common for a LIMS or LIS to have extensive data analysis capabilities, some may support the sometimes complex work of generating antibiograms.[1][2][3] At a minimum, the LIMS should have robust reporting capabilities able to handle the nuances of susceptibility testing and antibiograms, particularly to the standard CLSI M39 Analysis and Presentation of Cumulative Antimicrobial Susceptibility Test Data.[1][10] Ideally, the LIMS can even run the analyses themselves, pulling data from the LIMS and HIS, but again this may not be common.
  • Decision support systems for medical microbiology: Just as there are decision support systems (DSS) built into some LIMS that can guide pharmacogenomics (PGx) decisions made with the aid of molecular diagnostics testing[11], a handful of LIMS or HIS options may incorporate DSS to better guide microbiology-based decisions on antibiotic prescription.[1][12] (DSS has already been used for other purposes in LIMS.[13][14]) Those DSS may be guided with the help of supervised machine learning (ML) algorithms or other AI components.[12] However, such systems have their own acquisition and implementation costs, and maintaining the DSS with relevant data at regular intervals to ensure the DSS' usefulness adds additional costs the microbiology lab must weigh.[1]

Conclusion

References

  1. 1.00 1.01 1.02 1.03 1.04 1.05 1.06 1.07 1.08 1.09 1.10 1.11 1.12 Rhoads, Daniel D.; Sintchenko, Vitali; Rauch, Carol A.; Pantanowitz, Liron (1 October 2014). "Clinical Microbiology Informatics" (in en). Clinical Microbiology Reviews 27 (4): 1025–1047. doi:10.1128/CMR.00049-14. ISSN 0893-8512. PMC PMC4187636. PMID 25278581. https://journals.asm.org/doi/10.1128/CMR.00049-14. 
  2. 2.0 2.1 "Video tutorials - Microbiology Results (Antibiogram)". SLCLAB Informática SL. 2023. https://slclab.com/en/videos-en.aspx. Retrieved 17 April 2024. 
  3. 3.0 3.1 "Molecular ID LIS Solution". BGASoft, Inc. 2023. https://www.limsabc.com/molecular-id/. Retrieved 17 April 2024. 
  4. 4.0 4.1 Futrell, K. (5 December 2023). "Address Lab Staffing Shortages with Integrated Automation Solutions - White Paper". Orchard Software. https://www.orchardsoft.com/white_paper/automation-contributes-to-laboratory-efficiency/. Retrieved 17 April 2024. 
  5. Antonios, Kritikos; Croxatto, Antony; Culbreath, Karissa (30 December 2021). "Current State of Laboratory Automation in Clinical Microbiology Laboratory" (in en). Clinical Chemistry 68 (1): 99–114. doi:10.1093/clinchem/hvab242. ISSN 0009-9147. https://academic.oup.com/clinchem/article/68/1/99/6490228. 
  6. Sandle, T. (22 December 2021). "Enhancing rapid microbiology methods: how AI is shaping microbiology". European Pharmaceutical Review. https://www.europeanpharmaceuticalreview.com/article/166302/enhancing-rapid-microbiology-methods-how-ai-is-shaping-microbiology/. Retrieved 17 April 2024. 
  7. "BIOMIC V3". Giles Scientific, Inc. 2024. https://www.biomic.com/biomic-v3.html. Retrieved 17 April 2024. 
  8. Antimicrobial Resistance and Stewardship Initiative, University of Minnesota (February 2020). "How to Use a Clinical Antibiogram" (PDF). https://arsi.umn.edu/sites/arsi.umn.edu/files/2020-02/How_to_Use_a_Clinical_Antibiogram_26Feb2020_Final.pdf. Retrieved 17 April 2024. 
  9. Gajic, Ina; Kabic, Jovana; Kekic, Dusan; Jovicevic, Milos; Milenkovic, Marina; Mitic Culafic, Dragana; Trudic, Anika; Ranin, Lazar et al. (23 March 2022). "Antimicrobial Susceptibility Testing: A Comprehensive Review of Currently Used Methods" (in en). Antibiotics 11 (4): 427. doi:10.3390/antibiotics11040427. ISSN 2079-6382. PMC PMC9024665. PMID 35453179. https://www.mdpi.com/2079-6382/11/4/427. 
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