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Algorithm-based decision rules to safely reduce laboratory test ordering.

J R Schubart1, C E Fowler, G R Donowitz

  • 1Department of Health Evaluation Sciences, University of Virginia School of Medicine, Charlottesville, VA 22908-0717, USA. jrw5d@virginia.edu

Studies in Health Technology and Informatics
|October 18, 2001
PubMed
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Developing new decision rules for repeat laboratory testing in hospitalized patients can significantly reduce test orders, like serum potassium tests, without compromising patient care quality.

Area of Science:

  • Clinical laboratory science
  • Health services research
  • Medical informatics

Background:

  • Hospitalized patients often undergo routine laboratory testing.
  • Optimizing the frequency of repeat testing is crucial for cost-effectiveness and patient care.

Purpose of the Study:

  • To develop and evaluate algorithm-based decision rules for determining appropriate intervals for repeat laboratory tests in hospitalized patients.
  • To assess the potential reduction in laboratory test utilization.

Main Methods:

  • Utilized data from 5,632 adult patients with a length of stay of five days or more.
  • Analyzed results of three routinely ordered laboratory tests for the first five hospitalization days.
  • Developed an algorithm-based decision rule, illustrated with serum potassium testing.

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Main Results:

  • The proposed decision rule involves initial testing on the first two days, with repeats triggered by non-normal values.
  • An algorithm-based approach demonstrated a 34% reduction in serum potassium tests within the first five hospitalization days.
  • Only one critical value was missed due to occurring on a non-test day.

Conclusions:

  • Algorithm-based decision rules can effectively reduce the number of laboratory tests ordered.
  • This approach shows promise in reducing healthcare costs without compromising patient care quality.
  • Implementation of such algorithms can optimize laboratory test ordering practices.