Wow...you are simply deluded and choose to remain ignorant then. Not much more to say here as you have your opinion based on dialogue with peers, and I have mine based on personal real time experience.

It's ironic that you think my personal experiences are worth less than yours, but ignoring that. Let's approach this from a different perspective.

National data shows that there are between 300,000 and 400,000 out of hospital cardiac arrests annually in the U.S. I chose cardiac arrest because it is a patient population with well-reported data and who clearly needs resuscitation; I obviously recognize that there are may be other patients, not in cardiac arrest, but who are still critically ill. I believe the general principle displayed by this assumption holds for my larger point, however. Another source puts it at 111 per 100,000 people. With a U.S. population of 330,000,000, that means there are 366,300 OHCAs every year. Divided by 365 days a year, that comes out to 1003.56 arrests a day. There are ~4000 hospitals in the US. That means, on average, each hospital is expected to see 0.25 arrests a day.

(Now, this "model" makes significant simplifying assumptions, but which I think are appropriate for a back-of-napkin calculation like this. For example, these numbers are reliant on every OHCA being transported to an ER. Additionally, we assume that each ER sees an equivalent number of arrests each day, which we know is not accurate, since higher volume centers will see a larger absolute number of arrests, by definition. However, because we're interested in a smaller-than-average sized ER, my calculation will actually overestimate the true event rate, which is fine.)

We can model the number of cardiac arrests seen in an ER by a Poisson distribution. Again, a Poisson distribution is not perfect, but it is a good enough approximation. The average rate is 0.25, and our random variable is 2 (that is, we are interested in how often any given ER should see >=2 OHCAs a day). The probability of X>=x (or of seeing at least 2 arrests a day) is 0.02650, or 2.65%. However, remember that this is over a full 24 hour period; the likelihood of seeing 2 (or more) arrests within one hour, where the single provider would already be tied up and unavailable to come see the new patient, is much much lower.

To summarize:

Do I think that having more critically unstable patients than you have providers is theoretically possible? Yes.

Do I think that having more critically unstable patients than you have providers actually happens? Of course it does.

Do I think that having more critically unstable patients than you have providers happens regularly? Or is commonplace? Or is "taking place quite commonly in many, many places [and] is the current reality"? No.

I'm not saying that you aren't seeing more critically unstable patients than you have providers available to see in a timely manner, or that you aren't overwhelmed with patients, or even that this isn't an infrequent occurrence in your experience. Most things in the real world follow a distribution, and distributions have tails that hold outliers and extreme values, and due to unique geography/patient factors/happenstance/luck, you could work at ER(s) that see an unexpectedly large number of critically unstable patients. Who am I to say whether you do or not? You work there, I don't. However, it is not true that this experience is generalizable or largely applicable to most other ERs, who do fall closer to average values.