To the owners and operators of skilled nursing facilities: If you don’t think you and hospitals aren’t much alike, think again. That seemed to be one of the strongest messages out of a focus group I recently took part in.
The purpose of the focus group was to gauge the thoughts and opinions of long-term care operators regarding rehospitalizations. Was it a hot topic? You bet. There was emphatic unanimity that preventing avoidable rehospitalizations was a top priority, if not the top priority, for their organizations.
And — get this — their overall sentiment was that only some of the more progressive hospitals “get” that they need to work better with long-term care providers. “Others don’t yet, or are waiting to see what really will be necessary in the future,” according to a report on the group.
Hmmm. Sounds a lot some of your LTC colleagues doesn’t it? Not you, of course, but others.
Bigger companies are getting up to speed quicker, but then their challenge is in filtering the understanding down through the ranks so that those who interact with the public “get it” sooner.
Why this all matters so much, of course, is that come Oct. 1, hospitals are going to start getting dinged by federal regulators if their rehospitalization rates are too high. They need good post-acute providers who won’t be sending patients back to the hospital.
The LTC providers around the table were most intrigued about ways they might be able to “slice and dice” their outcomes data. Who’s good in one treatment area might not be good in another. Besides, “every hospital wants something different,” one provider pointed out.
But the message was clear: Data was, and is, king for helping prove your case. Analytical ability is crucial, they agreed.
If you can break down your discharges by diagnosis, great. Perhaps even better would be the ability to classify the patient population by doctor. The day’s hosts from PointRight agreed on both points and noted they would also like to be the first to develop the latter aspect.
The most intriguing reactions out of the providers came when they saw a product that could cross-analyze their own outcomes results and compare them to competitors’. The idea of knowing an opponent’s weaknesses delighted, it seemed, until it was realized that they also could do exactly the same thing to you.
“Scary” was the label one provider gave it.
“Great system, if it’s used properly” was another.
“You can’t hide. And you can’t make excuses,” another concluded.
And isn’t that the way it should be?