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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
Summary
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.
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.
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