Literature DB >> 23331736

A strategic informatics approach to autoverification.

Jay B Jones1.   

Abstract

Autoverification is rapidly expanding with increased functionality provided by middleware tools. It is imperative that autoverification of laboratory test results be viewed as a process evolving into a broader, more sophisticated form of decision support, which will require strategic planning to form a foundational tool set for the laboratory. One must strategically plan to expand autoverification in the future to include a vision of instrument-generated order interfaces, reflexive testing, and interoperability with other information systems. It is hoped that the observations, examples, and opinions expressed in this article will stimulate such short-term and long-term strategic planning.
Copyright © 2013 Elsevier Inc. All rights reserved.

Mesh:

Year:  2012        PMID: 23331736     DOI: 10.1016/j.cll.2012.11.004

Source DB:  PubMed          Journal:  Clin Lab Med        ISSN: 0272-2712            Impact factor:   1.935


  4 in total

1.  Autoverification in a core clinical chemistry laboratory at an academic medical center.

Authors:  Matthew D Krasowski; Scott R Davis; Denny Drees; Cory Morris; Jeff Kulhavy; Cheri Crone; Tami Bebber; Iwa Clark; David L Nelson; Sharon Teul; Dena Voss; Dean Aman; Julie Fahnle; John L Blau
Journal:  J Pathol Inform       Date:  2014-03-28

2.  Design and evaluation of a LIS-based autoverification system for coagulation assays in a core clinical laboratory.

Authors:  Zhongqing Wang; Cheng Peng; Hui Kang; Xia Fan; Runqing Mu; Liping Zhou; Miao He; Bo Qu
Journal:  BMC Med Inform Decis Mak       Date:  2019-07-03       Impact factor: 2.796

3.  Development and implementation of an LIS-based validation system for autoverification toward zero defects in the automated reporting of laboratory test results.

Authors:  Di Jin; Qing Wang; Dezhi Peng; Jiajia Wang; Bijuan Li; Yating Cheng; Nanxun Mo; Xiaoyan Deng; Ran Tao
Journal:  BMC Med Inform Decis Mak       Date:  2021-06-02       Impact factor: 2.796

4.  Use of Middleware Data to Dissect and Optimize Hematology Autoverification.

Authors:  Rachel D Starks; Anna E Merrill; Scott R Davis; Dena R Voss; Pamela J Goldsmith; Bonnie S Brown; Jeff Kulhavy; Matthew D Krasowski
Journal:  J Pathol Inform       Date:  2021-04-07
  4 in total

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