Literature DB >> 15561793

Frequency of laboratory test utilization in the intensive care unit and its implications for large-scale data collection efforts.

Joseph J Frassica1.   

Abstract

OBJECTIVE: Mapping local use names to standardized nomenclatures such as LOINC (Logical Observation Identifiers Names and Codes) is a time-consuming task when done retrospectively or during the configuration of new information systems. The author sought to identify a subset of intensive care unit (ICU) laboratory tests, which, because of their frequency of use, should be the focus of efforts to standardize test names in ICU information systems.
DESIGN: The author reviewed the ordering practices in medical, surgical, and pediatric ICUs within a large university teaching hospital to identify the subset of laboratory tests that represented the majority of tests performed in these settings. The author compared the results of his findings with the laboratory tests required to complete several of the most frequently used ICU acuity scoring systems.
RESULTS: It was found that between 104 and 202 tests and profiles represented 99% of all testing in the three ICUs. All the laboratory studies needed for six commonly used ICU scoring systems fell into the top 21 laboratory studies and profiles performed in each ICU.
CONCLUSION: The author identified a small subset of the LOINC database that should be the focus of efforts to standardize test names in ICU information systems. Mapping this subset of laboratory tests and profiles to LOINC vocabulary will simplify the process of collecting data for large-scale databases such as ICU scoring systems and the configuration of new ICU information systems.

Mesh:

Year:  2004        PMID: 15561793      PMCID: PMC551555          DOI: 10.1197/jamia.M1604

Source DB:  PubMed          Journal:  J Am Med Inform Assoc        ISSN: 1067-5027            Impact factor:   4.497


  6 in total

1.  A method for the automated mapping of laboratory results to LOINC.

Authors:  L M Lau; K Johnson; K Monson; S H Lam; S M Huff
Journal:  Proc AMIA Symp       Date:  2000

2.  Automated mapping of observation codes using extensional definitions.

Authors:  K A Zollo; S M Huff
Journal:  J Am Med Inform Assoc       Date:  2000 Nov-Dec       Impact factor: 4.497

3.  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

4.  Modeling the severity of illness of ICU patients. A systems update.

Authors:  S Lemeshow; J R Le Gall
Journal:  JAMA       Date:  1994-10-05       Impact factor: 56.272

5.  Paediatric index of mortality (PIM): a mortality prediction model for children in intensive care.

Authors:  F Shann; G Pearson; A Slater; K Wilkinson
Journal:  Intensive Care Med       Date:  1997-02       Impact factor: 17.440

6.  PRISM III: an updated Pediatric Risk of Mortality score.

Authors:  M M Pollack; K M Patel; U E Ruttimann
Journal:  Crit Care Med       Date:  1996-05       Impact factor: 7.598

  6 in total
  7 in total

1.  The design and evaluation of a graphical display for laboratory data.

Authors:  David T Bauer; Stephanie Guerlain; Patrick J Brown
Journal:  J Am Med Inform Assoc       Date:  2010 Jul-Aug       Impact factor: 4.497

2.  Evaluating the state of the art in missing data imputation for clinical data.

Authors:  Yuan Luo
Journal:  Brief Bioinform       Date:  2022-01-17       Impact factor: 11.622

3.  Design of a Personal Health Record and Health Knowledge Sharing System using IHE-XDS and OWL.

Authors:  Li-Hui Lee; Yi-Ting Chou; Ean-Wen Huang; Der-Ming Liou
Journal:  J Med Syst       Date:  2013-01-15       Impact factor: 4.460

4.  A rationale for parsimonious laboratory term mapping by frequency.

Authors:  Daniel J Vreeman; John T Finnell; J Marc Overhage
Journal:  AMIA Annu Symp Proc       Date:  2007-10-11

5.  Effect of different pre-analytical conditions on plasma lactate concentration.

Authors:  Ivana Rako; Ana Mlinaric; Monika Dozelencic; Gordana Fressl Juros; Dunja Rogic
Journal:  Biochem Med (Zagreb)       Date:  2018-04-15       Impact factor: 2.313

6.  Predicting Abnormalities in Laboratory Values of Patients in the Intensive Care Unit Using Different Deep Learning Models: Comparative Study.

Authors:  Ahmad Ayad; Ahmed Hallawa; Arne Peine; Lukas Martin; Lejla Begic Fazlic; Guido Dartmann; Gernot Marx; Anke Schmeink
Journal:  JMIR Med Inform       Date:  2022-08-24

7.  A clinical prediction model to identify patients at high risk of hemodynamic instability in the pediatric intensive care unit.

Authors:  Cristhian Potes; Bryan Conroy; Minnan Xu-Wilson; Christopher Newth; David Inwald; Joseph Frassica
Journal:  Crit Care       Date:  2017-11-20       Impact factor: 9.097

  7 in total

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