Azam Z. Why the Hero Narrative Is Problematic for Health Care Workers Like Me. Harvard Public Health Review. 2020;28.
CAC Foreman 8th floor. Rapid response Klau 4.
The voice in my head is the voice that comes overhead every few seconds.
As a first year internal medicine resident in New York City, the physical and emotional toll the pandemic has placed on me is unmeasurable. My attending physician reminds me of someone commanding a battlefield. I work with my “allied” residents, doctors from different specialties deployed to my floor, “coalition” doctors, and students that graduated early to help us. Medicine has been replaced by wartime rhetoric. Unlike war however, medicine is not a path by which any of us ever expected to lose our lives.
Being on the front line of a global pandemic at a tertiary care center in one of the most populated cities in the world is not only surreal, it’s scary. Not the type of scare you get from running out of groceries at the supermarket. I was scared of the potential cases I was coming into contact with, scared that my mask didn’t fit properly on my face, scared that I would touch it with dirty gloves by mistake. My face hurts from wearing a mask 13 hours a day. My head hurts from trying to find a mask in the chaos of people frantically searching for it.
Walking into a shift one morning, I was handed a Yankees poncho to use as a gown. “Treat it like gold,” one hospital administrator said at a weekly COVID town-hall conference. I can’t come into work without fearing for my life.
At my own hospital, a nurse I worked with a few weeks ago is now in critical condition in our intensive care unit. Yet, hospitals are firing personnel for speaking out, nurses are on leave for bringing their own protective gear to work , and physicians are seeing their compensation cut. This treatment makes the heroic rhetoric voiced in the general public meaningless.
As the death toll continues to spike, I started taking a few seconds out of my day just to hold my patient’s hands as they neared death. I close my eyes and stand in silence with the patient, because, in the chaos of it all, we have become so desensitized. Tomorrow is never promised.
A few mornings later, I started having fever and chills. I was in stern denial. But this could no doubt be a surprise when you’re dispatched to a pandemic with a Yankees poncho.
But worse, I could hear my grandfather with whom I live coughing violently. What was his O2 saturation? How was his breathing? These are the questions I asked strangers for weeks during each of my shifts. Now, here I was bringing my grandfather into the ER.
One of the horrors of being in the hospital during this time is that no family members are able to be by your side. Medical workers are stretched so thin that there are not enough to look after everyone. The care for each patient inevitably becomes compromised.
Day after day, I saw my grandfather through FaceTime. Truthfully, I felt blessed to be able to see him at all. I got to see him and he got to see me, even if it was through a 5-inch screen. It was our lifeline.
One of the calls you dread making as a doctor is telling a family member their loved one is dying. That was the call I received when my grandfather decompensated. We grow accustomed to making the call as clinicians but we never expect to get it ourselves.
I felt for his pulse. Slow but faint. As a doctor, you become desensitized over time. You frantically think of the next steps that will save this body’s life, until you realize “that body” is someone you know.
Death here during this time has no dignity. I’ve experienced a lot in my career by trade. But the deaths during COVID feel particularly brutal. Patients are not allowed to have visitors and often die scared. Someone codes, someone dies, and on you go to save the next life.
A few days later, I prepared to head back to work. I thought about all the patients I treated for COVID-19, never thinking my grandfather would be one. As I headed into work around 7pm, I hear the sounds of people cheering outside. At that moment, I did not feel like a hero.
Society needs to redirect energy to alleviating the struggles of workers rather than glorifying them. The government faltered, but community advocates and grassroot organizers have laid the foundation for reproducible change in addressing the disparate impact of the pandemic and beyond.
The fact of the matter is, nobody wants to be a hero right now. We just want to live to see another day.
Artificial intelligence (AI), specifically machine-learning, provides techniques to uncover complex associations that would normally not be resolved from simple computer algorithms/equations. In medicine, the introduction of AI systems have allowed for an unprecedented analysis of clinical presentations – systems are now able to systematically weigh pieces of information to reach logical conclusions, mimicking a clinician’s thought process 1. In fact, AI systems have evolved to the point where in some clinical settings, their diagnostic accuracy surpasses those of clinicians: AI has been able to out-perform dermatologists in assessing suspicious skin lesions, and more effective at identifying pulmonary tuberculosis on chest radiographs than radiologists 2-3. AI systems have even been given the responsibility of triaging severity of patient symptoms; the National Health Services in the United Kingdom recently employed AI to tend to medical questions from a population of 1.2 million residents, and assess the urgency of medical conditions to subsequently advise of appropriate action (i.e. advising rest, or recommending for immediate emergency room consult) 4.
There has been an increased interest in the use of artificial intelligence (AI) in public health, specifically to assist with health promotion and health protection. For example, personalized and targeted health advice can be provided to different members of the population based on personal health profiles, as identified through electronic medical records. AI can also be used to rapidly analyze data and anticipate subsequent data modulation with respect to disease surveillance and health protection; for example, AI can utilize GPS data from cellular phones to predict areas at risk of outbreak, based on the temporal exposure of a region to the origin/person harbouring an outbreak 5. AI may not only allow for personalized public health but may allow for expedited assessments of complex public health scenarios.