Evidence map›Paper›PMID 32736551›Full record

ArticleBMC medical informatics and decision making2020

Preventing overuse of laboratory diagnostics: a case study into diagnosing anaemia in Dutch general practice.

Michelle M A Kip, Martijn L J Oonk, Mark-David Levin, Annemarie Schop, Patrick J E Bindels, Ron Kusters, Hendrik Koffijberg

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC medical informatics and decision making, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.3field-weighted citation impact, top 34% of its field
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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 2 citations in OpenAlex.

  1. 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 at 4 institutions in 1 country.

Michelle M A KipDepartment of Health Technology and Services Research, University of Twente, Technical Medical Center, Faculty of Behavioural, Management and Social Sciences, Enschede, the Netherlands. m.m.a.kip@utwente.nl.ORCID 0000-0002-6405-6789
Martijn L J OonkDepartment of Health Technology and Services Research, University of Twente, Technical Medical Center, Faculty of Behavioural, Management and Social Sciences, Enschede, the Netherlands.
Mark-David LevinDepartment of Internal Medicine, Albert Schweitzer Hospital, Dordrecht, the Netherlands.
Annemarie SchopDepartment of Internal Medicine, Albert Schweitzer Hospital, Dordrecht, the Netherlands.
Patrick J E BindelsDepartment of General Practice, Erasmus MC, Rotterdam, the Netherlands.
Ron KustersDepartment of Health Technology and Services Research, University of Twente, Technical Medical Center, Faculty of Behavioural, Management and Social Sciences, Enschede, the Netherlands.
Hendrik KoffijbergDepartment of Health Technology and Services Research, University of Twente, Technical Medical Center, Faculty of Behavioural, Management and Social Sciences, Enschede, the Netherlands.
University of Twente · NLAlbert Schweitzer Ziekenhuis · NLErasmus MC · NLJeroen Bosch Ziekenhuis · NL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMore information is often thought to improve medical decision-making, which may lead to test overuse. This study assesses which out of 15 laboratory tests contribute to diagnosing the underlying cause of anaemia by general practitioners (GPs) and determines a potentially more efficient subset of tests for setting the correct diagnosis.

methodsLogistic regression was performed to determine the impact of individual tests on the (correct) diagnosis. The statistically optimal test subset for diagnosing a (correct) underlying cause of anaemia by GPs was determined using data from a previous survey including cases of real-world anaemia patients.

resultsOnly 9 (60%) of the laboratory tests, and patient age, contributed significantly to the GPs' ability to diagnose an underlying cause of anaemia (CRP, ESR, ferritin, folic acid, haemoglobin, leukocytes, eGFR/MDRD, reticulocytes and serum iron). Diagnosing the correct underlying cause may require just five (33%) tests (CRP, ferritin, folic acid, MCV and transferrin), and patient age.

conclusionsIn diagnosing the underlying cause of anaemia a subset of five tests has most added value. The real-world impact of using only this subset should be further investigated. As illustrated in this case study, a statistical approach to assessing the added value of tests may reduce test overuse.

Indexed as

AnemiaGeneral PracticeFerritinsHumansLaboratoriesFerritinsAnemiaData analysis, statisticalDiagnoses and laboratory examinationsGeneral practiceOptimal testingOveruse

Identifiers

PMID32736551
PMCPMC7395377
OpenAlexW2901107900

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.