The problem is cost. You're a good grandson for fighting for your grandpa, but there's no way we can afford the level of care you're demanding for every person close to end of life. It's inherently a futile battle.
You are referencing a pernicious myth - a classic selection bias. For the majority of illnesses we don’t know whether someone is near the end of their life or not. We all “know” that people tend to have expensive care just before they die, but the selection bias occurs because we ignore the counterfactual where people have expensive care and then go on to live for many years afterwards. Edit: A study found “most people who die aren’t expected to, and many people who are expected to die don’t. In particular, less than 10 percent of those who die within 12 months had a predicted mortality above 50 percent. And if beneficiaries are ranked by their predicted mortality, the group with a high chance of dying accounted for only 5 percent of total Medicare spending, and among them about half survived in any case, perhaps in part due to the health care they received. As the study's authors conclude, ‘These findings suggest that a focus on end-of-life spending is not, by itself, a useful way to identify wasteful spending.’” https://archive.ph/gUzzO
Also “total spending on end-of-life care is only 9 percent of the total cost of health care”. Chronic condition are where costs lie.
And US healthcare costs have not really risen: https://randomcriticalanalysis.com/why-conventional-wisdom-o...
That one-quarter of Medicare spending in the United States occurs in the last year of life is commonly interpreted as waste. But this interpretation presumes knowledge of who will die and when. Here we analyze how spending is distributed by predicted mortality, based on a machine-learning model of annual mortality risk built using Medicare claims. Death is highly unpredictable. Less than 5% of spending is accounted for by individuals with predicted mortality above 50%. The simple fact that we spend more on the sick-both on those who recover and those who die-accounts for 30 to 50% of the concentration of spending on the dead. Our results suggest that spending on the ex post dead does not necessarily mean that we spend on the ex ante "hopeless."This is the issue this paragraph is dedicated to refuting. But this thread is not about this issue. So it’s largely just an irrelevant passage. However;
> Here we analyze how spending is distributed by predicted mortality, based on a machine-learning model of annual mortality risk built using Medicare claims. Death is highly unpredictable. Less than 5% of spending is accounted for by individuals with predicted mortality above 50%.
This quote is dumb. As a data scientist I give it an F. Less than 5% of spending is accounted for by individuals with predicted mortality above 50%? Ok but what proportion of individuals is that? Is it 10% in which case they’re underrepresented? 5% in which case they’re average? Or .1% in which case they’re pulling in 50x their share? If we pull the criteria down to 40% what happens? What share of people who died are above 50% in the model? It’s a quote that is basically impossible to make use of on its face but is being used to push a very specific narrative.
Sometimes know, but, admitting it is harder than we want to believe.
I can pull up statistics on a foot ulcer in a geriatric patient and point out that it usually (>50%) leads to amputation and that following an amputation most patients don't live a year and get called an asshole. I realized fairly quickly that the right course was to fight to make the next 12 months - 2 years "as good as possible." Organizing care and finances (dying is expensive).
Sending a nurse to do a wound check daily is much cheaper than ambulatory travel to an ER (or even doctors office).
Moving him to our house was cheaper than a nursing facility.
Hospice was obviously far cheaper than any continuing care.