Literature DB >> 33568009

No lab is an island: universal coding of laboratory test names.

Michael K Martin1.   

Abstract

The local laboratory with a local client-base, that never needs to exchange information with any outside entity, is a dying breed. As marketing channels, animal movement, and reporting requirements become increasingly national and international, the need to communicate about laboratory tests and results grows. Local and proprietary names of laboratory tests often fail to communicate enough detail to distinguish between similar tests. To avoid a lengthy description of each test, laboratories need the ability to assign codes that, although not sufficiently user-friendly for day-to-day use, contain enough information to translate between laboratories and even languages. The Logical Observation Identifiers Names and Codes (LOINC) standard provides such a universal coding system. Each test-each atomic observation-is evaluated on 6 attributes that establish its uniqueness at the level of clinical-or epidemiologic-significance. The analyte detected, analyte property, specimen, and result scale combine with the method of analysis and timing (for challenge and metabolic type tests) to define a unique LOINC code. Equipping laboratory results with such universal identifiers creates a world of opportunity for cross-institutional data exchange, aggregation, and analysis, and presents possibilities for data mining and artificial intelligence on a national and international scale. A few challenges, relatively unique to regulatory veterinary test protocols, require special handling.

Entities:  

Keywords:  artificial intelligence; data mining; laboratories; language; logical observation identifiers names and codes

Mesh:

Year:  2021        PMID: 33568009      PMCID: PMC8120069          DOI: 10.1177/1040638721994829

Source DB:  PubMed          Journal:  J Vet Diagn Invest        ISSN: 1040-6387            Impact factor:   1.279


  3 in total

1.  LOINC, a universal standard for identifying laboratory observations: a 5-year update.

Authors:  Clement J McDonald; Stanley M Huff; Jeffrey G Suico; Gilbert Hill; Dennis Leavelle; Raymond Aller; Arden Forrey; Kathy Mercer; Georges DeMoor; John Hook; Warren Williams; James Case; Pat Maloney
Journal:  Clin Chem       Date:  2003-04       Impact factor: 8.327

2.  The Indiana network for patient care: an integrated clinical information system informed by over thirty years of experience.

Authors:  Paul G Biondich; Shaun J Grannis
Journal:  J Public Health Manag Pract       Date:  2004-11

3.  PulseNet: the molecular subtyping network for foodborne bacterial disease surveillance, United States.

Authors:  B Swaminathan; T J Barrett; S B Hunter; R V Tauxe
Journal:  Emerg Infect Dis       Date:  2001 May-Jun       Impact factor: 6.883

  3 in total
  2 in total

1.  Leveraging and enhancing the value of veterinary diagnostic laboratory data.

Authors:  Brian McCluskey
Journal:  J Vet Diagn Invest       Date:  2021-05       Impact factor: 1.279

Review 2.  Gaps in standards for integrating artificial intelligence technologies into ophthalmic practice.

Authors:  Sally L Baxter; Aaron Y Lee
Journal:  Curr Opin Ophthalmol       Date:  2021-09-01       Impact factor: 4.299

  2 in total

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