Literature DB >> 23216205

The ideal laboratory information system.

Jorge L Sepulveda1, Donald S Young.   

Abstract

CONTEXT: Laboratory information systems (LIS) are critical components of the operation of clinical laboratories. However, the functionalities of LIS have lagged significantly behind the capacities of current hardware and software technologies, while the complexity of the information produced by clinical laboratories has been increasing over time and will soon undergo rapid expansion with the use of new, high-throughput and high-dimensionality laboratory tests. In the broadest sense, LIS are essential to manage the flow of information between health care providers, patients, and laboratories and should be designed to optimize not only laboratory operations but also personalized clinical care.
OBJECTIVES: To list suggestions for designing LIS with the goal of optimizing the operation of clinical laboratories while improving clinical care by intelligent management of laboratory information. DATA SOURCES: Literature review, interviews with laboratory users, and personal experience and opinion.
CONCLUSIONS: Laboratory information systems can improve laboratory operations and improve patient care. Specific suggestions for improving the function of LIS are listed under the following sections: (1) Information Security, (2) Test Ordering, (3) Specimen Collection, Accessioning, and Processing, (4) Analytic Phase, (5) Result Entry and Validation, (6) Result Reporting, (7) Notification Management, (8) Data Mining and Cross-sectional Reports, (9) Method Validation, (10) Quality Management, (11) Administrative and Financial Issues, and (12) Other Operational Issues.

Entities:  

Mesh:

Year:  2012        PMID: 23216205     DOI: 10.5858/arpa.2012-0362-RA

Source DB:  PubMed          Journal:  Arch Pathol Lab Med        ISSN: 0003-9985            Impact factor:   5.534


  12 in total

Review 1.  Considerations for Group Testing: A Practical Approach for the Clinical Laboratory.

Authors:  Jun G Tan; Aznan Omar; Wendy By Lee; Moh S Wong
Journal:  Clin Biochem Rev       Date:  2020-12

2.  A Map for Clinical Laboratories Management Indicators in the Intelligent Dashboard.

Authors:  Zahra Azadmanjir; Mashallah Torabi; Reza Safdari; Maryam Bayat; Fatemeh Golmahi
Journal:  Acta Inform Med       Date:  2015-07-30

3.  Failure to review STAT clinical laboratory requests and its economical impact.

Authors:  Enrique Rodriguez-Borja; Celia Villalba-Martinez; Esther Barba-Serrano; Arturo Carratala-Calvo
Journal:  Biochem Med (Zagreb)       Date:  2016       Impact factor: 2.313

4.  Patient facing decision support system for interpretation of laboratory test results.

Authors:  Georgy Kopanitsa; Ilia Semenov
Journal:  BMC Med Inform Decis Mak       Date:  2018-07-20       Impact factor: 2.796

5.  Quality and Safety in eHealth: The Need to Build the Evidence Base.

Authors:  Elizabeth Borycki
Journal:  J Med Internet Res       Date:  2019-12-19       Impact factor: 5.428

6.  Evaluation of Hematocrit in Adults with Dengue by a Laboratory Information System.

Authors:  Duangjai Sahassananda; Vipa Thanachartwet; Putza Chonsawat; Benjamaporn Wongphan; Supat Chamnanchanunt; Manoon Surabotsophon; Varunee Desakorn
Journal:  J Trop Med       Date:  2021-03-27

7.  Using text mining techniques to extract prostate cancer predictive information (Gleason score) from semi-structured narrative laboratory reports in the Gauteng province, South Africa.

Authors:  Naseem Cassim; Michael Mapundu; Victor Olago; Turgay Celik; Jaya Anna George; Deborah Kim Glencross
Journal:  BMC Med Inform Decis Mak       Date:  2021-11-25       Impact factor: 2.796

8.  Reqscan: An open source solution for laboratory requisition scanning, archiving and retrieval.

Authors:  Eviatar Bach; Daniel T Holmes
Journal:  J Pathol Inform       Date:  2015-01-29

9.  Implementation of Automated Calculation of Free and Bioavailable Testosterone in Epic Beaker Laboratory Information System.

Authors:  Michael C Chung; Saurabh Gombar; Run Zhang Shi
Journal:  J Pathol Inform       Date:  2017-07-25

Review 10.  Quality Control of Next-Generation Sequencing-Based HIV-1 Drug Resistance Data in Clinical Laboratory Information Systems Framework.

Authors:  Rupert Capina; Katherine Li; Levon Kearney; Anne-Mieke Vandamme; P Richard Harrigan; Kristel Van Laethem
Journal:  Viruses       Date:  2020-06-14       Impact factor: 5.048

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