Evidence map›Paper›PMID 38224401›Full record

ReviewAnnals of intensive care2024

Interventions to improve appropriateness of laboratory testing in the intensive care unit: a narrative review.

Luigi Devis, Emilie Catry, Patrick M Honore, Alexandre Mansour, Giuseppe Lippi, François Mullier, Mélanie Closset

Registry-linked trialAbstract readReview
In one paragraph

Review in Annals of intensive care, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07629219 (Optimization of Low-Value Medical Testing Practices in Hospitalized Patients in Argentina), which is not on this map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT07629219 nacompletednot on this mapstarted 2025, after this paper: background citation

Optimization of Low-Value Medical Testing Practices in Hospitalized Patients in Argentina (OPTIMIZAR)

TypeinterventionalSponsorHospital Italiano de Buenos AiresRan2025 to 2025Enrolled600ConditionsLow-Value Care, Costs and Cost Analysis, Implementation Science, Public HealthArmsOPTIMIZAR Multicomponent Diagnostic Stewardship Bundle
3 · Its place in the literature

Who cites it

8 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
  4. Article
  5. [Summary of the S1 guideline on sustainability in intensive care and emergency medicine].Medizinische Klinik, Intensivmedizin und Notfallmedizin · 2025
    Article
  6. Article
  7. Article
  8. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Luigi DevisDepartment of Laboratory Medicine, Biochemistry, CHU UCL Namur, Université catholique de Louvain, Yvoir, Belgium.
Emilie CatryDepartment of Laboratory Medicine, Biochemistry, CHU UCL Namur, Université catholique de Louvain, Yvoir, Belgium.
Patrick M HonoreDepartment of Intensive Care, CHU UCL Namur, Université catholique de Louvain, Yvoir, Belgium.
Alexandre MansourDepartment of Anesthesia and Critical Care, Pontchaillou University Hospital of Rennes, Rennes, France.
Giuseppe LippiSection of Clinical Biochemistry and School of Medicine, University Hospital of Verona, Verona, Italy.
François MullierDepartment of Laboratory Medicine, Hematology, CHU UCL Namur, Université catholique de Louvain, Yvoir, Belgium.
Mélanie ClossetDepartment of Laboratory Medicine, Biochemistry, CHU UCL Namur, Université catholique de Louvain, Yvoir, Belgium. melanie.closset@chuuclnamur.uclouvain.be.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Healthcare expenses are increasing, as is the utilization of laboratory resources. Despite this, between 20% and 40% of requested tests are deemed inappropriate. Improper use of laboratory resources leads to unwanted consequences such as hospital-acquired anemia, infections, increased costs, staff workload and patient stress and discomfort. The most unfavorable consequences result from unnecessary follow-up tests and treatments (overuse) and missed or delayed diagnoses (underuse). In this context, several interventions have been carried out to improve the appropriateness of laboratory testing. To date, there have been few published assessments of interventions specific to the intensive care unit. We reviewed the literature for interventions implemented in the ICU to improve the appropriateness of laboratory testing. We searched literature from 2008 to 2023 in PubMed, Embase, Scopus, and Google Scholar databases between April and June 2023. Five intervention categories were identified: education and guidance (E&G), audit and feedback, gatekeeping, computerized physician order entry (including reshaping of ordering panels), and multifaceted interventions (MFI). We included a sixth category exploring the potential role of artificial intelligence and machine learning (AI/ML)-based assisting tools in such interventions. E&G-based interventions and MFI are the most frequently used approaches. MFI is the most effective type of intervention, and shows the strongest persistence of effect over time. AI/ML-based tools may offer valuable assistance to the improvement of appropriate laboratory testing in the near future. Patient safety outcomes are not impaired by interventions to reduce inappropriate testing. The literature focuses mainly on reducing overuse of laboratory tests, with only one intervention mentioning underuse. We highlight an overall poor quality of methodological design and reporting and argue for standardization of intervention methods. Collaboration between clinicians and laboratory staff is key to improve appropriate laboratory utilization. This article offers practical guidance for optimizing the effectiveness of an intervention protocol designed to limit inappropriate use of laboratory resources.

Indexed as

Artificial intelligenceInappropriateIntensive care unitInterventionsMinimum retesting intervalOverusePrescriptionTests

Identifiers

PMID38224401
PMCPMC10789714

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.