Physicians do not prescribe opioid analgesics for pain treatment equally across groups. Latino and African Americans, for example, are significantly less likely than whites to receive opioid analgesics following a major surgical procedure (1-4), and opioid prescriptions rates for women and senior citizens appear low relative to their reports of chronic pain (4-6). Such disparities in pain treatment may pose significant public health concerns. Many recognize pain as the “fifth vital sign” of health (7, 8); undertreatment of pain is associated with a variety of disadvantages such as diminished quality of life, physical functioning, mental acuity, sexual functioning, and sleep. Undertreated pain is also associated with increased (and costly) returns to the hospital (9, 10). Therefore, it is critical to identify factors that might bias doctors’ treatment of pain.
Undertreatment for pain results from many factors that operate in combination including pain’s ambiguous diagnostic criteria, cultural stereotypes around particular groups’ experience of pain, and institutional constraints that affect doctors’ ability to diagnose pain. Because pain often lacks clear physical markers, doctors are forced to elicit information directly from patients to determine whether opioid analgesic treatment is necessary (11-13). However, subjective assessments of patients’ pain needs are highly subject to implicit bias (14). For example, doctors often mistakenly assume that African Americans have more pain tolerance and have more illicit motivations for seeking pain treatment than do whites (15-19). Long-standing stereotypes about women’s lack of pain tolerance appear to bias doctors to both over-treat and undertreat women’s pain (4, 20). Preferences for patients who are culturally similar to doctors may lead doctors to reduce attention to the suffering of patients from lower socio-economic groups (11, 16, 21, 22) thereby limiting doctors’ ability to make informed diagnoses. Institutional constraints also play a role in doctors’ treatment decisions. Some evidence suggests that doctors are more likely to over-treat pain during periods of increased time-pressure, such as when it is late at night or when emergency departments are crowded (15, 23). Such time constraints may intensify doctors’ implicit biases by increasing their likelihood to rely on implicit assumptions about patient diagnostic categories to inform treatment (13, 24).
Although there are many studies about how institutional constraints and cultural stereotypes influence doctors’ treatment of pain, quantitative evidence is mixed. Recent research suggests that doctors are biased towards over-treating patients during periods of time constraint and hospital crowding (15, 23), but such claims seem to contradict a small body of evidence that doctors are averse to prescribing opiates when under time-constraint (4, 25). Gendered biases in pain treatment have been documented in a fairly large body of ethnographic research (4, 20), but these biases are not well-supported by quantitative evidence (3, 26, 27). In fact, even though race may be the best documented source of provider bias in opioid pain treatment, prior studies have only examined these biases in reference to Latino and African American patients. There have been no substantial attempts to explain how other racial backgrounds, such as Asian heritage, is associated with pain treatment.
Sociological research suggests that some discrepant findings may be due to overlooked mediators and moderators of other cultural and institutional constraints (14, 15, 20, 28). For example, high frequency of opioid treatment of pain for patients late at night may reflect selection biases in patients’ medical histories rather than doctors’ time pressures. Many demographic correlates with pain treatment might be induced by related factors, such as such as patient race, gender, age, marital status, or medical history. Ignoring how multiple factors simultaneously contribute to bias in pain treatment likely subjects much prior research to omitted variable bias.
To understand how institutional constraints and patient demographics influence pain treatment, this paper examines a large longitudinal dataset of electronic medical records gathered at an emergency department of a large private hospital in the United States. We study how opioid treatment for pain is simultaneously influenced by multiple factors and how this may bias pain treatment. Specifically, we examine how pain treatment is influenced by the intersection of emergency department crowding and race, the time patients visited the emergency department, patients’ medical histories, patients’ diagnoses, age, sex, marital status, and year of analysis. This is one of the largest and most comprehensive longitudinal study of demographic and institutional predicates of opioid pain treatment in the literature, and it is one of only a few studies that examine multiple factors associated with pain treatment in tandem and over time. Our findings inform dominant hypotheses about provider bias, clarify prior mixed evidence, and provide evidence for under-explored avenues of bias in pain treatment.