In recent years, the health care system has increasingly relied on predictive data analytics in the prosecution of physicians, turning what was once a tool for improving care into an instrument of punitive measures by the U.S. government. Thousands of U.S. physicians, particularly those working with vulnerable populations, have been targeted based on flawed or biased data patterns, with many facing prosecution and imprisonment. Predictive data analytics, initially designed to enhance patient outcomes, now serve as a social health credit system, flagging medical professionals and their patients without due process or adequate transparency. This misuse of artificial intelligence technology has created a chilling effect within the medical community, resulting in unjust punishment and the erosion of trust between doctors and their patients.
This systemic issue is compounded by a gender disparity in pain treatment, where more than 50 million Americans suffering from chronic pain, the vast majority of whom are women, are particularly vulnerable. Women experience pain more frequently and more intensely than men, with studies revealing they are disproportionately affected by conditions like endometriosis, rheumatoid arthritis, fibromyalgia, and migraines. Yet, the health care system not only overlooks their suffering but perpetuates disparities that worsen the situation.
Women are more likely to seek help for their pain, but the health care system often fails them. Research shows they wait longer in emergency rooms, are prescribed fewer painkillers, and are more likely to be told their symptoms are psychological, a phenomenon highlighted by Elizabeth Reynolds Losin, the director of Pennsylvania State University’s Social and Cultural Neuroscience Lab. In a study conducted by Losin and her colleagues, both male and female patients reporting the same pain intensity were perceived differently, with female pain behaviors discounted. This bias leads to women receiving psychotherapy instead of pain medication, further deepening the psychological dismissal of their physical suffering.
The bias against women in pain treatment is not just anecdotal but supported by extensive research. Studies have shown that health care providers are less likely to prescribe strong analgesia to women, even in cases of severe pain, and when they do, women typically wait longer to receive it. These disparities are evident in emergency room settings, cancer pain clinics, and during procedures like IUD insertions, where women frequently receive little or no pain relief despite describing the procedure as one of the most painful experiences of their lives.
The failure to address women’s pain adequately in the United States is not just a result of poor treatment but is also rooted in research. Pain studies have historically focused on male biology, including 80 percent of rodent studies in leading journals conducted on male subjects. This male-centric approach has hindered the development of effective pain treatments for women, a large gap that remains despite efforts to include female subjects in research in recent years.
The biases and dismissive attitudes toward female pain patients reflect the same underlying problem seen in the prosecution of U.S. physicians through government artificial intelligence and predictive data analytics. Physician and patient advocacy groups around the nation have argued that machine and artificial intelligence biases are driven by flawed data, lack of transparency, and systemic biases that disproportionately harm the most vulnerable populations. Women in pain and the doctors who treat them are being marginalized by a health care system that now values algorithmic decision-making over patient care, leaving both groups to fight for their voices to be heard.
As the U.S. health care system continues to rely on predictive data analytics to target physicians, it risks further alienating those most in need of care, particularly women suffering from chronic pain. The chilling effect on doctors, combined with the dismissal of women’s pain, is creating a radioactive health care environment that demands urgent attention. Health care professionals must challenge the misuse of artificial intelligence predictive tools, ensure transparency in health care practices, and close the gender gap in pain treatment if our profession is to address this growing crisis. Only through systemic reform can we hope to restore trust in the health care system and provide the care that all patients, regardless of gender, deserve.
Neil Anand is an anesthesiologist.
