Preventing overuse of laboratory diagnostics: a case study into diagnosing anaemia in Dutch general practice
Abstract Background More 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. Methods Logistic 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 fr... Mehr ...
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Dokumenttyp: | Artikel |
Erscheinungsdatum: | 2020 |
Reihe/Periodikum: | BMC Medical Informatics and Decision Making, Vol 20, Iss 1, Pp 1-11 (2020) |
Verlag/Hrsg.: |
BMC
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Schlagwörter: | Anemia / Data analysis / statistical / Diagnoses and laboratory examinations / General practice / Optimal testing / Overuse / Computer applications to medicine. Medical informatics / R858-859.7 |
Sprache: | Englisch |
Permalink: | https://search.fid-benelux.de/Record/base-27020273 |
Datenquelle: | BASE; Originalkatalog |
Powered By: | BASE |
Link(s) : | https://doi.org/10.1186/s12911-020-01198-8 |
Abstract Background More 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. Methods Logistic 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. Results Only 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. Conclusions In 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.