ReviewDiagnostics (Basel, Switzerland)2021
Laboratory Demand Management Strategies-An Overview.
Review in Diagnostics (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
8 citing papers in PubMed.
- The impact of demand management on vitamin D testing.Biochemia medica · 2025Article
- A 5-step root cause analysis model for test overutilization: A study on its application to plasma transferrin testing.American journal of clinical pathology · 2024Article
- Interventions to improve appropriateness of laboratory testing in the intensive care unit: a narrative review.Annals of intensive care · 2024Review
- Article
- Machine Learning in Laboratory Medicine: Recommendations of the IFCC Working Group.Clinical chemistry · 2023Article
- Appropriateness of laboratory expenditure for primary health care facilities across South Africa.African journal of primary health care & family medicine · 2023Article
- Evaluation of tumour marker utilisation and impact of electronic gatekeeping in the province of KwaZulu-Natal, South Africa.African journal of laboratory medicine · 2023Article
- Blood tests - too much of a good thing.Scandinavian journal of primary health care · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Inappropriate laboratory test selection in the form of overutilization as well as underutilization frequently occurs despite available guidelines. There is broad approval among laboratory specialists as well as clinicians that demand management strategies are useful tools to avoid this issue. Most of these tools are based on automated algorithms or other types of machine learning. This review summarizes the available demand management strategies that may be adopted to local settings. We believe that artificial intelligence may help to further improve these available tools.
Indexed as
Identifiers
What OpenQuestion holds
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.