Solution is to support proper scientific procedures, support civic organizations carrying out the important tasks of vetting claims, and being an example of someone who values the correct protocols when evaluating data and making conclusions (or not making them).
It's a very slow process, and we're lucky we're in a timeline where the work of various people throughout history has gotten us here. We'll have to work to keep it going further, and literacy in math, statistics, and the scientific process is crucial.
Compare the two statements: "10 out of 80 people that took the drug lived a month longer but were extremely miserable."
Versus: "A new cancer drug doubles the average survival rates scientists say".
Which one do you understand better? Here I just made up some examples, but as a scientist I'll tell you just about all the papers I read are in the second category, it takes an unreasonable amount of effort to get the first type of infomration out of the publications.
When I use the word statistics in this conversation, I mean the use of math to analyze and compare data. This can be done inappropriately, of course, but the problem doesn't lie with the principles of math (including statistics), but the agent using them inappropriately.
And medical (or biology related) statistics are used most inappropriately, due to various cognitive biases and financial incentives. But the problem is not statistics, and it's still the best tool we have unless we can find a Magic School Bus to shrink us down and go observe the chemical reactions in real time. But I know that stats are abused, so anytime I see a fantastical claim, especially in medicine, I approach it much skepticism.
Psychology journal bans P values
https://www.nature.com/news/psychology-journal-bans-p-values...
I happen to agree with the sentiment expressed above that the entire concept of hypothesis testing is fundamentally flawed. This is what you call the "best tool". It is not, it is the tool that is used because it allows for the most fudging of results.