Please use this identifier to cite or link to this item: http://hdl.handle.net/11054/2823
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dc.contributorKleinig, O.en_US
dc.contributorTo, M.en_US
dc.contributorOvenden, C.en_US
dc.contributorKovoor, Joshuaen_US
dc.contributorGoh, R.en_US
dc.contributorLam, L.en_US
dc.contributorWenzel, T.en_US
dc.contributorTan, Y.en_US
dc.contributorHarish, H.en_US
dc.contributorGupta, A.en_US
dc.contributorGluck, S.en_US
dc.contributorGilbert, T.en_US
dc.contributorBacchi, S.en_US
dc.date.accessioned2024-11-29T03:37:22Z-
dc.date.available2024-11-29T03:37:22Z-
dc.date.issued2024-
dc.identifier.govdoc02792en_US
dc.identifier.urihttp://hdl.handle.net/11054/2823-
dc.description.abstractObjective: The measurement and recording of vital signs may be impacted by biases, including preferences for even and round numbers. However, other biases, such as variation due to defined numerical boundaries (also known as boundary effects), may be present in vital signs data and have not yet been investigated in a medical setting. We aimed to assess vital signs data for such biases. These parameters are clinically significant as they influence care escalation. Methods: Vital signs data (heart rate, respiratory rate, oxygen saturation and systolic blood pressure) were collected from a tertiary hospital electronic medical record over a 2-year period. These data were analysed using polynomial regression with additional terms to assess for underreporting of out-of-range observations and overreporting numbers with terminal digits of 0 (round numbers), 2 (even numbers) and 5. Results: It was found that heart rate, oxygen saturation and systolic blood pressure demonstrated ‘boundary effects’, with values inside the ‘normal’ range disproportionately more likely to be recorded. Even number bias was observed in systolic heart rate, respiratory rate and blood pressure. Preference for multiples of 5 was observed for heart rate and blood pressure. Independent overrepresentation of multiples of 10 was demonstrated in heart rate data. Conclusion: Although often considered objective, vital signs data are affected by bias. These biases may impact the care patients receive. Additionally, it may have implications for creating and training machine learning models that utilise vital signs data.en_US
dc.description.provenanceSubmitted by Gemma Siemensma (gemmas@bhs.org.au) on 2024-10-31T00:40:29Z No. of bitstreams: 0en
dc.description.provenanceApproved for entry into archive by Gemma Siemensma (gemmas@bhs.org.au) on 2024-11-29T03:37:22Z (GMT) No. of bitstreams: 0en
dc.description.provenanceMade available in DSpace on 2024-11-29T03:37:22Z (GMT). No. of bitstreams: 0 Previous issue date: 2024en
dc.titleVital sign measurements demonstrate terminal digit bias and boundary effects.en_US
dc.typeJournal Articleen_US
dc.type.specifiedArticleen_US
dc.bibliographicCitation.titleEmergency Medicine Australasiaen_US
dc.bibliographicCitation.volume36en_US
dc.bibliographicCitation.issue4en_US
dc.bibliographicCitation.stpage543en_US
dc.bibliographicCitation.endpage546en_US
dc.subject.healththesaurusBIASen_US
dc.subject.healththesaurusBOUNDARY EFFECTen_US
dc.subject.healththesaurusBUNCHINGen_US
dc.subject.healththesaurusEVEN NUMBERen_US
dc.subject.healththesaurusROUND NUMBERen_US
dc.subject.healththesaurusVITAL SIGNen_US
dc.identifier.doihttps://doi.org/10.1111/1742-6723.14395en_US
Appears in Collections:Research Output

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