Bibliographic record
Abstract
As an undergraduate, I learned a few juxtaposing pieces of information about our nation's healthcare system that stuck with me. The first was that those who gave birth in the United States were more likely to die from pregnancy-related complications than those who gave birth in other developed nations.1 The second is that pregnancy-related deaths occurred in the United States at a rate that disproportionately affected people of color.2 The third and final fact is that, compared with all other global nations, the United States spent the most money on healthcare per capita.3 In the years that followed, I watched these statistics come to life. After graduating, I moved to a nearby city to work as a medical scribe in the ED of a community hospital situated in one of the city's lowest-income neighborhoods. At the time, about 90% of patient encounters at the hospital occurred in the ED, and nearly a quarter of patients were uninsured. It was there that I came toe-to-toe for the first time with some of the social determinants of health that I had previously only read about in textbooks. I quickly came to find that the ED was a neighborhood staple for much more than just medicine. It was as much an ED as it was a primary care office, a trauma center, a sexual health clinic, a detox facility, a wound care clinic, a pharmacy, a warm bed, a guaranteed meal, a domestic violence shelter, a holding cell, a refuge from prison, and a social worker's office. Emergency medical care was just the tip of the iceberg. At work, I watched public health crises unfold before my eyes. My public health degree in tow, I often considered the multitude of factors that led these patients to the ED. When I saw patients having strokes, heart attacks, blood clots, or diabetic emergencies, I often thought of how I, too, would suffer from these ailments had I lived in a food desert in which it was too dangerous to exercise. When patients came to the ED intoxicated or overdosed, I often thought of how I, too, might try to cover years of pain with those substances. These patients and their ailments were affected by their surrounding environment. I silently thanked my formal education for allowing me to recognize these medical problems in the context of larger public health issues. But my empathy had its limits, as I also found myself frustrated with patients. I got frustrated with those who came to the ED for work notes or sexually transmitted infection screenings. I got frustrated with homeless patients who had perfected the art of prolonging their stay just enough to secure a bed for the night. I got frustrated with patients who routinely experienced medical emergencies by taking their medications incorrectly. It seemed that these nonemergent and often preventable issues stood in the way of our ED's ability to treat conditions that I considered true emergencies. I eventually left my job at the hospital and moved to a new state to begin a physician associate/assistant (PA) program. In my second year, I was assigned to a clinical rotation at a mobile primary care clinic for uninsured patients. I found solace in the similarities between these patients and the ones at my old hospital. Caring for medically underserved patients again felt like coming home. How lucky I was to have two different opportunities to provide medical care for those who seldom received it. It quickly became clear that these were the patients to whom I would dedicate my medical career. I joked that I would never leave for my next rotation. This was my niche, I was sure of it. But with my newfound sense of purpose came a nagging sense of guilt. Just a few years earlier, I had silently denigrated patients in the ED for what I perceived at the time to be intentional misuse of emergency services. My brief stint as a primary care provider drove me to the sobering realization that such misuse had been far from intentional. Patients who might have gotten bus passes and sandwiches in the ED arrived for their appointments at the mobile clinic after walking in the heat for miles on empty stomachs. Patients whose hospital stays doubled as healthcare and housing arrived at the clinic after sleeping in cars, on sidewalks, in parks, or on friends' couches. Inadequate access to healthcare extended well beyond my one-dimensional view from my vantage point in the ED. At my old hospital, my compassion ended abruptly where my privilege began. Had I, a college-educated, health-literate, privately insured White woman, sought routine medical care at the ED, it would have been a choice, and an ill-informed and/or deliberately irresponsible one at that. Many patients had neither the luxury of being informed nor that of having a choice. I would never truly know the bone-chilling fear of persecution that undocumented patients felt. I would never understand what it was like to be wary of a healthcare system that just a few decades ago had experimented on patients like me without consent. I would, fundamentally, never experience the world the way that many of my patients at the clinic did. What business did I have caring for these people when there were clinicians who truly understood and could empathize with them? After all, it had taken me years to grasp just how extensively the social determinants of health had laid roots in medicine. Perhaps I had not found my niche, but instead a hook on which my ego could hang its hat. In a twist of fate, I learned while rotating at the mobile clinic that I had received a full-tuition scholarship that was awarded to students in medicine in exchange for at least 2 years working as a primary care provider in a medically underserved region. Despite my moral dilemma, I accepted the scholarship. It seemed only right for me to pursue primary care; that was what the PA career was originally intended for, after all.4 In light of the scholarship, I began to view my time at the mobile clinic as fundamental to my future practice. In fact, I began to feel that this service-learning opportunity had been an essential clinical experience regardless of where I would practice after graduation. Rotating at the mobile clinic forced me to make clinical decisions that would not have been the correct answer on a test, but in reality were the most likely to get a patient the best possible care. In fact, the efficacy of my medical decisions had been entirely contingent on patients' social determinants of health. During the rotation, I often thought of the statistics I had learned as an undergraduate about poor maternal outcomes for minority patients in the United States, despite the nation's exorbitant healthcare spending. To be as naive to the social determinants of health as I had been was to inherently compromise the quality of care I could provide to some of the most medically vulnerable patients in the country. Nevertheless, it had been pure luck that I had this service-learning opportunity as opposed to another primary care rotation. Surely, integrating more service-learning and social determinants of health curriculum into medical education would improve health outcomes for underserved patients. If we as clinicians truly intend to do no harm, we must first ensure that access to medical education is equitable across all demographics. People with personal experience being medically underserved would be, by nature, the best possible clinicians for underserved patients. Research suggests that the medical community has historically broken trust with racial and ethnic minorities.5,6 Given that most US medical providers, including PAs and NPs, are White, we must recruit, support, and train substantially more racially and ethnically underrepresented clinicians to equitably serve our patients.7 Perhaps by seeing more clinicians to whom they could relate, patients of color—including those who account for the vast majority of pregnancy-related deaths—would stand more of a fighting chance in the US healthcare system.2 At the very least, racial concordance between patients and clinicians has been shown to improve patients' overall perception of their medical encounters.8 Although years of intergenerational medical trauma cannot be undone, there is hope that the same may not necessarily be true of present-day attitudes toward healthcare providers. By continuing to omit service learning in medical education, we effectively seal an unfortunate fate for patients who, statistically, are already at a disadvantage. Until there is better access to medical education and more minority representation among clinicians, we must teach prospective clinicians how to practice medicine with respect to patients' social determinants of health. The failure to do anything else only further contributes to systemic negligence. Students like myself owe it to these patients to bridge the gap.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".