In yet another red state/blue state divide, The New York Times has another fascinating article by Robert Pear with a supporting infographic that measures the cost and quality of Medicare. The data from the Dartmouth Atlas of Health Care compares health care quality and costs for Medicare recipients. The findings suggest that “areas that spend the most do not always produce better quality care”. Quality data was compiled by the Agency for Healthcare Research and Quality, a unit within the U.S. Department of Health and Human Services. They reviewed over 100 criteria to assess the state’s performance.
Interestingly, WI ranked as the number one state in Medicare quality with expenditures of $6,798/recipient. Kudos to our health care professionals! (Now if we could only do something about our weather, we’d become an even bigger retiree magnet.) The state with the lowest spending was HI at $5,311, with the highest spending – NY at $9,564 and with the highest spending, lowest quality – LA at $9,401. The states in the lowest third, in terms of quality, were primarily states in the South or Southwest (AR, LA, MS, GA, TN, KY, OK, FL, TX) with the exceptions being IN, ILL, NM and DC. The states with the highest quality and lowest costs included WI, IA, WA and MN.
According to the article, the Medicare Payment Advisory Commission (MedPAC) found “that much of the variation could be explained by local differences in the cost of providing care and in the health status of beneficiaries”. While I can understand the health status issue, I’m less certain about what is in the bucket “local differences in the cost of providing care’ comment. This could include a wide variety of factors that would require research to determine what really is at the heart of of these costs. MedPAC, is one of the agencies that would gain greater power under many health care reform plans that would make it what Ezra Klein at The Washington Post called “the Federal Reserve for Medicare.”
Great post – this is an interesting look at this. You also did two things that earn bonus points in my book. You were willing to admit that there was some uncertainty and that there are other factors that need to be uncovered (as you do with the “local difference” issue. And you pointed out a potential source bias (of MedPAC).
Not surprisingly, I have a little different take on this, especially in the context of a massive national healthcare system ahead. I think trying to come up with quality metric is very important and on the right track. But the driver seems to be, “we’re providing good quality but getting less money so necessarily we’re getting screwed.” Where does that lead us? Only to even greater price inflation. We should be using the high quality and low cost states as the model to strive for. Their quality and efficiency need to be the targets. Instead with the politicians and their pork attitude, we’ll see the funding go up for the the efficient areas, no drop in the inefficient ones and overall costs go up without improving quality. Lose-lose.
To the larger issue, geographic differences bring up another point. The more control we get from centralized control from Washington, the more we lose customizing solutions to the geographic regions. A one-size-fits-all approach may bring the bottom performers up. But it tends to push the top down as well. This isn’t necessarily bad – whether the gain on one end is worth the loss on the other is a judgement call. But let’s call a duck, a duck and admit there ARE tradeoffs. There always are – we don’t have unlimited resources and to pretend otherwise or that there are silver bullets (from either side) is disingenuous and dishonest.
Finally I just couldn’t let this one slide:
I agree with your magnet metaphor – unfortunately, the poles are the same, and we’re repelling retirees, not attracting them. We were a net loser of retirees – 11.3 per thousand from 1995-2000 according to the Pew Center on the States. I don’t have time to further but $1 says that number has only gone up (probably dramatically) since 2000.
Thanks for the nice comment and for your data from Pew.
I see the world differently when it comes to retirement. We are seeing that cities that place well on “the creative class” index like Madison or are spending on re-development like Milwaukee are drawing in seniors. In fact, the AARP in 2007 listed Milwaukee as one of 5 Great Places to Live (see http://www.aarpmagazine.org/lifestyle/best_places_2007.html)saying it was “urban renewal at its best and represented affordable waterfront living.” Madison has been called a great place for biking by TopRetirement (http://www.topretirements.com/tips/Best_Communities/15_Great_Biking_Towns_for_Retirement.html) and with the surrounding community has won many best or near best rankings for farmer’s markets, suburban towns, entertainment, restaurants, etc. These quality of life issues are somewhat negated by the cold weather, snow and having to shovel for retirees. I am however convinced that today’s retirees and others will seek high quality, diverse, dynamic and engaging communities with good health care, good transportation, good entertainment, good natural amenities and clean politics; all of which our state is lucky to have.
For my parent’s generation, these factors did not play as much in their retirement planning as low taxes and no snow; but for today’s boomer and near boomer generations these are the factors that will play well for retirees. I might add that for my parent’s final retirement, they came back to Wisconsin where they reside in Union Grove Cemetery for eternity.
I had just found the Pew site – I have no idea about the quality of their data or if there’s any agenda or motives so I wouldn’t vouch for them as far as that goes, but really like the quick visual of how the states compare on a quite a few different statistics – and a nice datasheet with raw numbers is only a click away.
For a really tremendous tool that does all that and a ton more only with countries, I can’t recommend gapminder highly enough. It is just plain awesome for a visualization of data – and I hope they expand their software to cover US data.
OK Full blown tangent here, but I convinced it will be worth it. Not only is gapminder something all readers here should see, but if you haven’t done so, please watch it’s creator, Hans Rosling’s presentations at TED. You will be amazed, you may just be changed, and you most definitely won’t be disappointed. Software itself – Trendalyzer that Hans used to create gapminder is was so compelling, Google bought it shortly after he first gave a presentation using it at TED.
Retirement Update – Steven’s Point is named among Money Magazine’s top 25 cities for retirees http://money.cnn.com/galleries/2009/moneymag/0909/gallery.bpretire_top25.moneymag/18.html
I question the method for naming “top cities.”
I note that Providence RI, was ranked ahead of Point, despite having high taxes and high crime (5th highest property crime in the Country for cities over 100,000).
Anyone can produce a list of “Top cities that…” so a large grain of salt with such lists is in order. That said, even if there were some sort of consensus on those sort of things about where the best places for retirees to live, the bottom line is there is data showing the actual migration numbers. Lists present the reasons why one place or another “should” be a good place to go. The data shows where they are actually going.
I agree with both of your points. Thanks for commenting. I do however know that people look at lists as part of their review process whether for a college to attend, a country to visit or a state/city for retirement. These lists could have an impact down the road.
Your point is well-taken as well – though I would discount many such lists, there are certainly good ones too. And to the degree that their sponsors/publishers carry weight & influence people (Money Magazine & AARP certainly do) their lists can be a leading indicator.
My guess is, most retired people will consider – proximity to family, weather, and taxes most heavily in their decisions. Community, food and entertainment, I’m sure factor in, but I’d bet those and other factors fall much lower than the first three.