Screening for multiple myeloma using routine laboratory test results

Objective: In our academic intensive care unit (ICU), there is excess ordering of routine laboratory tests. This is partially due to a lack of transparency of laboratory-processing costs and to the admission order plans that favor daily laboratory test orders. We hypothesized that a program that involves physician and staff education and alters the current ICU order sets will lead to a sustained decrease in routine laboratory test ordering. Design: Prospective cohort study. Setting: Academic closed medical ICU (MICU). Patients: All patients admitted to the MICU. Methods: We consistently educated residents, faculty, and staff about laboratory test costs. We removed the daily laboratory test option from the admission order sets and asked residents to order needed laboratory test results every day. We only allowed the G3+I-STAT (arterial blood gas only) cartridges in the MICU in hopes of decreasing duplicative laboratory test results. We added laboratory review to the daily rounding checklist. Measurement and Main Results: Total number of laboratory tests per patient-day decreased from 39.43 to an average of 26.74 ( P <.001) over a 9-month period. The number of iSTAT laboratory tests per patient-day decreased from 7.37 to an average of 1.16 ( P < .001) over the same time period. The number of iSTAT/central laboratory processing duplicative laboratory tests per patient-day decreased from 0.17 to an average of 0.01 ( P < .001). The percentage of patients who have daily laboratory test orders decreased from 100% to an average of 11.94% ( P <. 001). US$123 436 in direct savings and US$258 035 dollars in indirect savings could be achieved with these trends. Intensive care unit morbidity and mortality were not impacted. Conclusion: A simple technique of resident, nursing, and ancillary staff education, combined with alterations in order sets using electronic medical records, can lead to a sustained reduction in laboratory test utilization over time and to significant cost savings without affecting patient safety.

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Routine laboratory blood tests predict SARS-CoV-2 infection using machine learning

10.1101/2020.06.17.20133892 ◽

2020 ◽

Cited By ~ 1

Author(s):

He Sarina Yang ◽

Ljiljana V. Vasovic ◽

Peter Steel ◽

Amy Chadburn ◽

Yu Hou ◽

...

Keyword(s):

Machine Learning ◽

Laboratory Test ◽

Patient Care ◽

Characteristic Curve ◽

Rapid Identification ◽

Routine Laboratory ◽

Test Results ◽

Rt Pcr ◽

Diagnostic Strategies ◽

Laboratory Test Results

AbstractBackgroundAccurate diagnostic strategies to rapidly identify SARS-CoV-2 positive individuals for management of patient care and protection of health care personnel are urgently needed. The predominant diagnostic test is viral RNA detection by RT-PCR from nasopharyngeal swabs specimens, however the results of this test are not promptly obtainable in all patient care locations. Routine laboratory testing, in contrast, is readily available with a turn-around time (TAT) usually within 1-2 hours.MethodWe developed a machine learning model incorporating patient demographic features (age, sex, race) with 27 routine laboratory tests to predict an individual’s SARS-CoV-2 infection status. Laboratory test results obtained within two days before the release of SARS-CoV-2-RT-PCR result were used to train a gradient boosted decision tree (GBDT) model from 3,346 SARS-CoV-2 RT-PCR tested patients (1,394 positive and 1,952 negative) evaluated at a large metropolitan hospital.ResultsThe model achieved an area under the receiver operating characteristic curve (AUC) of 0.853 (95% CI: 0.829-0.878). Application of this model to an independent patient dataset from a separate hospital resulted in a comparable AUC (0.838), validating the generalization of its use. Moreover, our model predicted initial SARS-CoV-2 RT-PCR positivity in 66% individuals whose RT-PCR result changed from negative to positive within two days.ConclusionThis model employing routine laboratory test results offers opportunities for early and rapid identification of high-risk SARS-COV-2 infected patients before their RT-PCR results are available. This may facilitate patient care and quarantine, indicate who requires retesting, and direct personal protective equipment use while awaiting definitive RT-PCR results.

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