Sex bias in pain management decisions

Abstract

In the pursuit of mental and physical health, effective pain management stands as a cornerstone. Here, we examine a potential sex bias in pain management. Leveraging insights from psychological research showing that females' pain is stereotypically judged as less intense than males' pain, we hypothesize that there may be tangible differences in pain management decisions based on patients' sex. Our investigation spans emergency department (ED) datasets from two countries, including discharge notes of patients arriving with pain complaints (N = 21,851). Across these datasets, a consistent sex disparity emerges. Female patients are less likely to be prescribed pain-relief medications compared to males, and this disparity persists even after adjusting for patients' reported pain scores and numerous patient, physician, and ED variables. This disparity extends across medical practitioners, with both male and female physicians prescribing less pain-relief medications to females than to males. Additional analyses reveal that female patients' pain scores are 10% less likely to be recorded by nurses, and female patients spend an additional 30 min in the ED compared to male patients. A controlled experiment employing clinical vignettes reinforces our hypothesis, showing that nurses (N = 109) judge pain of female patients to be less intense than that of males. We argue that the findings reflect an undertreatment of female patients' pain. We discuss the troubling societal and medical implications of females' pain being overlooked and call for policy interventions to ensure equal pain treatment.

Keywords: decision-making; healthcare disparities; pain management; sex bias.

Fig. 1.

Likelihood of receiving an analgesic prescription by patient’s sex and by (A) age group (N = 17,576), (B) reported pain score (VAS) (N = 6,825), and (C) physician’s sex (N = 17,576) (Study 1). Error bars denote 95% CI. *P < 0.05; **P < 0.01; ***P < 0.001

Fig. 2.

Likelihood of receiving (A) any type of analgesic prescription, (B) an opioid analgesic prescription, and (C) a nonopioid analgesic prescription by patient’s sex and reported pain level (Study 1). Error bars denote 95% CI. *P < 0.05; **P < 0.01; ***P < 0.001

Fig. 3.

Likelihood of receiving an analgesic prescription by patient’s sex and reported pain level (VAS) (Study 2). Error bars denote 95% CI. *P < 0.05; **P < 0.01; ***P < 0.001.