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Influence of patient race on administration of analgesia by student paramedics
Journal article   Open access   Peer reviewed

Influence of patient race on administration of analgesia by student paramedics

Bill Lord and Sahaj Khalsa
BMC Emergency Medicine, Vol.19, 32
2019
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PDF - Published Version (Open Access)561.86 kBDownloadView
Published VersionPDF - Published Version (Open Access)CC BY V4.0 Open Access
url
https://doi.org/10.1186/s12873-019-0245-2View
Published Version

Abstract

paramedic emergency care prehospital pain management race analgesia
Background: Disparities in the management of pain are associated with factors that include social status, age and race. As there is limited data regarding the influence of race on analgesia provided by paramedics this study investigated associations between patient race and student paramedic management of pain. Methods: Retrospective study of student paramedic records entered in the FISDAP Skill Tracker database between 1 January 2014 to 31 December 2015. Cases were extracted if aged 16 to 100 years, the patient was alert and the primary or secondary impression was trauma. The primary outcome of interest was the association between patient race and student paramedic administration of any analgesia. The adjusted odds of patients receiving any analgesic was tested with logistic regression using a stepped modelling approach. Results: 59,915 cases were available for analysis; median age was 50 years (IQR 39 years), 50.1% were female (n= 30,040). Fall was the most common case type 43% (n= 26,009) of cases. 14.1% of patients received any analgesia (n= 8424). Caucasian patients have significantly higher odds of receiving analgesia than non-Caucasian patients (p < 0.001). When analgesic administration is adjusted for gender, age category and injury cause, African Americans have the lowest logged odds of receiving any analgesia when compared to Caucasian patients (OR 0.60, p < 0.001). Conclusion: The results indicate inequality in the provision of analgesia by student paramedics based on patient race. This suggests a need for interventions to reduce disparities in care based on race.

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