Showing posts with label NEJM. Show all posts
Showing posts with label NEJM. Show all posts

Diabetes Care: The Spectrum of Success

Today’s Managing Health Care Costs Indicator is  8.3%

Diabetes is a major killer in the US – the disease strikes about one in twelve  Americans ( 8.3% in the entire population; one in four over age 65), is responsible for over 70,000 deaths, and is the leading cause of blindness and kidney failure.   The Centers for Disease Control and Prevention estimates that the annual cost of diabetes in the US is $168 billion in medical treatment, and $58 billion in lost productivity.

I’m struck by two studies published in the last week that use diametrically opposed approaches –and both appear to work.  (Both studies are small, though , so it’s possible that the results will not be sustained in larger samples).

The NEJM  published two studies showing that intensive surgical intervention helps.   Italian researchers showed that bariatric surgery (the most invasive surgical treatments) could “cure” diabetes in 75-95% of those treated, compared to NO cures in the medically treated group.  American researchers showed that those who had less-invasive surgical treatments were three times as likely to have an excellent diabetes control (Hemoglobin AIC of <6).   The conclusion –for diabetics with morbid obesity, surgical treatment is strikingly effective.  Other  studies have shown that bariatric surgery can pay off in a few years in the general population – this set of studies provides further evidence that we should cover this expensive ($11-$26,000) procedure for those with morbid obesity.

The Annals of Internal Medicine published an elegant study  which randomized 118 African American veterans with diabetes to usual care, financial rewards ($100-$200), and peer mentoring.  The financial reward for better HbAIC led to a 0.4% average decrease in HbAIC, while the peer mentoring led to a 1.1% decrease in HbAIC.

There are often many roads that lead to the right outcome in health care – and these studies are all small and did not include similar groups – so shouldn’t be compared.   It’s nice to know that both high tech and low tech solutions can have a substantial impact, and have the potential to decrease diabetic complications in our increasingly-obese population.

A Tough Week


Today’s Managing Health Care Costs Indicator is Five


It’s been a tough week for health care wonks of my persuasion.  

The Supremes – or at least the all-important Anthony Kennedy – suggested that the individual mandate could be toast, which would mean that the Affordable Care Act would insure millions fewer Americans.  Scalia et al suggested that if the mandate fell, the Court should invalidate the entire law, which would mean years or decades before we start trying the many good ideas embodied in this bill – including a path to generic biologic drugs, more comparative effectiveness research, and pilots to bundle payment.   The ACA is imperfect – but is chock full of good ideas for how to improve value in health care.  Many of these ideas won’t work as well as we would hope – but if we aren’t experimenting responsibly, our health care cost crisis will just continue to get worse and worse.

We need five justices to uphold the mandate, or at least to fail to declare the entire ACA unconstitutional. 

Two studies that came out this week also heightened my sense of malaise.  

The Premier Medicare Pay for Performance pilot – in which a group of 252 hospitals could earn bonus payments for improving certain quality metrics – showed no effectiveness whatsoever in lowering 30 day mortality.  NOW- this project wasn’t aiming to lower mortality. The bonuses were to encourage higher scores in certain evidence-based quality metrics – such as use of beta blockers and aspirin for heart attacks  and rapid antibiotics for pneumonias.   The reasoning was that this could improve quality and lower costs.
 Click Image to Enlarge. Source 

There are a lot of reasons why the Premier Medicare project might not have worked

·      The quality metrics might not actually be associated with lower mortality (good ideas –but not effective at diminishing death rates)
·      30 day mortality might be a bad metric itself – perhaps the hospital has more control over 15 day mortality, or 45 day mortality
·      The risk adjustment could have been flawed
·      The incentive might not have been large enough. The incentive was distant from the action, and although there was a potential penalty, hospitals could drop out if they faced a penalty.
·      The communication with the thousands of medical staff of these hospitals might have been ineffective


But all of this is whining.  Bottom line – this is  a deeply disappointing study.    Kudos to CMS, Premier, and Jha et al for publishing these negative results.  The only way to move forward effectively is to publish both positive AND negative results.

Ashish Jha had a double header in the NEJM last week – he also had an editorial suggesting that the emphasis on preventing hospital readmissions might be misdirected.  Hospital readmissions are staggering in the US Medicare population (almost one in five in 30 days).  However, readmissions are much lower in those under 65.   Further, Jha points to a literature review from the Canadian Medical Association Journal (The JAMA of the North) that showed that with clinical record review less than 12% of readmissions were judged to be preventable.  Overall only 2.2% of discharges led to a preventable readmission in this literature review.  Jha points out that penalties for high readmission rates could inadvertently penalize hospitals with lower mortality rates (who discharge patients who are by definition sicker).  Emphasizing the “wrong” measure draws our attention from other areas that may lead to better outcomes or more cost savings.

Now that we see coherent arguments against focusing too much attention on the “core measures” in the Premier demonstration and readmission rates, we just have to identify  on which metrics we SHOULD focus our attention.

Genetic Testing: Another Reason Why It's Not Likely To Lower Costs


Today’s Managing Health Care Costs Number is $299


A number of genetic testing companies suggest that doing genetic testing on individuals or an employee workforce could lower overall health care costs.  The cost of these tests ranges from $299 to $999.

Here’s how this works in theory.   Some people will be found to have genetic predisposition to react badly to some medications, or to need higher or lower doses of these medications.  Doing genetic tests would help individual employees get the best drug for their personal genetic traits in categories including antidepressants and blood thinners.   Further, genetic test could motivate behavior change when some people discover they are at higher genetic risk for certain diseases, including diabetes or heart disease.

The savings claims seem highly unlikely.

The General Accountability Office sent DNA samples from its own employees to multiple genetic testing companies, using both real and fictitious demographic and medical information. The GAO found that there were wild inconsistencies among the companies, and the genetic counseling advice offered was deeply flawed or worse. 

I’m especially interested in the “scared skinny” argument.  This argument goes that when shown evidence that she is at higher risk of diabetes, a test subject will go out and increase exercise and lose weight.    I’m skeptical, of course, since many people already see their parents suffer the complications of diabetes –and that would seem to me to have far more impact than a genetic test report!

The New England Journal of Medicine  published an article on its website this week reporting on 3600 people who personally paid for the Navigenics genetic testing package.   The article focuses on over 2000 people who had the genetic test and then completed 3 month followup surveys. The researchers looked at lifestyle behavior change subsequent to getting the results of the genetic tests, and compared those at high vs. low risk for various conditions.

The good news is that few people had test related distress or anxiety (9.3%) or clinically significant test related anxiety (2.8%) when they got their results.

The bad news (and you have to read the supplementary appendix to see the actual results) is that people found to be at increased genetic risk for obesity increased their intake of fatty foods after receiving the test results.  The only other significant findings related to risk conditions were those at higher risk of breast cancer had decreased exercise and increased their fat intake.  Those found to be at risk for  aneurisms, heart attacks, strokes, and diabetes did not make any significant changes in their lifestyles based on the result of these tests.

Genetic testing is likely to play an important future role in ascertaining the best medical care for each of us as individuals.  This study undermines one of the arguments to do widespread genetic testing right now.   There is no reason to encourage an unselected low risk population to get genetic testing at this point.

By the way, here's a link to a post from two years ago pointing out that genetic testing was promised to save money for those on blood thinners, but rigorous studies showed increased cost.

RAND Cost Saving Estimates, August (MA) and November (US)


(Click on graphic to enlarge)
The Mass Division of Health Care Policy and Finance sponsored an impressive review by RAND researchers of potential cost-saving opportunities in Massachusetts, which was published in August. I blogged about this late this summer, and have always felt that this extensive analysis didn't get nearly enough attention.

The NEJM last week published an article by same RAND researchers extending this analysis to the rest of the country.

This remains an important study - and I'm glad to see an extrapolation getting new press.

I'm also intrigued by the differences in findings.

Hospital rate setting: Maximum savings in MA 4%; US 2%
Healthcare IT: Maximum savings in MA 1.8%; US 1.5%; Maximum increase in costs in MA 0.6%; in US 0.8%
Expand scope of practice for NPs and PAs: MA range savings 0.6%-1.3%; US 0.3%-0.5%
Medical home: MA maximum savings 0.9%; US 1.2%
Disease management:  MA maximum savings 0.1%; US maximum savings 1.3%

It makes sense that rate setting might be more effective in Massachusetts to the extent that prices are higher. In fairness, this might not be a 1:1 comparison since the NEJM lumps a few different options together.  Scope of practice savings might be different based on supply of physician and non-physician providers.  I'm surprised to see higher projections of savings for medical home, since our specialist:primary care ratio is high in Massachusetts.  I also can't explain why disease management would have so much higher projected maximum savings in the US overall compared to Massachusetts.

This analytic work is especially important as we consider what cost-control mechanisms should be included in health care reform.