Tag: Quality

You Get What You Pay For

Jun 18, 2012• 15

By David Dranove

Two recent research papers remind us that it may be difficult to cut U.S. healthcare spending without harming quality. The first, written by a research team led by University of Chicago economist Tomas Philipson, appears in the latest issue of Health Affairs and has deservedly garnered a fair bit of media attention. The authors examine cancer spending and survival times for patients in the United States and ten European countries during the period 1983-1999 (later data were not available.) Their data confirm what we already know about health spending; the average cost of treating a cancer patient was about $15,000 higher in the United States. But the data also show that the typical U.S. cancer patient lives nearly two years longer; most of the difference is attributable to prostate and breast cancer patients. The gain appears to be due to greater longevity rather than early diagnosis. Using generally accepted measures of the value of a life, they conclude that the benefits of additional health spending outweigh the costs by a factor of 4:1 or higher. The latter calculation does not consider QALYs (quality adjusted life years) and so may be overstated. The authors acknowledge that other nations may do a better job of cancer prevention, so that their overall approach to cancer may be superior to that in the U.S., but they can find no evidence of this one way or another.

Philipson’s study suggests that U.S. healthcare consumers may get a substantial bang for their higher bucks. Maybe the U.S. system is not so inefficient after all. What about efficiency within the U.S. system? Some providers are far more expensive than others. Is the higher cost worth it? A new study by a team led by MIT economist Joseph Doyle, and released as an NBER Working Paper, suggests that you may get what you pay for within the United States. Doyle and his colleagues ask whether higher cost hospitals in the United States achieve better outcomes than lower cost hospitals. It is not easy to answer this question, because higher cost hospitals may admit more severely ill patients. This results in a statistical problem known as selection bias that is difficult to eliminate with available severity measures.

Why the Supreme Court’s Healthcare Decision Will Mean a lot … and Not so Much

Jun 18, 2012• 4

By Bob Wachter, MD

Like waiting outside the Vatican for the puff of white smoke, the nation sits on edge awaiting the Supreme Court’s ruling on the Affordable Care Act. The ruling, which is likely to be announced next week, could toss out the entire healthcare reform bill, chop off one of its limbs (probably the so-called individual mandate), or leave the ACA intact. Whatever the ruling, it will be chum for the blogosophere, particularly in the heat of presidential silly season.

The two fundamental challenges to American healthcare today are how to improve value (quality divided by cost) and how to improve access (primarily by insuring the tens of millions of uninsured people). The bill sought to address these twin challenges in ways that were complex and intertwined. I’ll argue that a decision by the Court to throw out all or part of the ACA will have a profoundly negative effect on the access agenda, but surprisingly little impact on the value agenda. To understand why requires that we focus less on the bewildering details (mandates, insurance exchanges, PCORI, CMMI, IPAB, etc.) and more on some big picture truths and tradeoffs.

The job of any healthcare system is to deliver high quality, safe, satisfying care to patients at the lowest possible cost. Although America certainly does specialty and high tech care like nobody’s business, on all of the key dimensions of value we aren’t very good. The numbers tell the sorry tale: we provide evidence-based care about half the time, there are huge variations in how care is delivered, we kill 44,000-98,000 patients per year from medical errors, and we spend 18% of our gross domestic product on medical care, far more than any other country.

A Funny Thing Happened on the Way to Meaningful Use

Jun 13, 2012• 22

By Rob Lamberts, MD

This July will mark the 16th anniversary of the installation of our electronic medical record.

Yup. I am that weird.

Over the first 10-14 years of my run as doctor uber-nerd, I believed that widespread adoption of EHR would be one of main things to drive efficiency in health care. I told anyone I could corner about our drive to improve the quality of our care, while keeping our cash-flow out of the red. I preached the fact that it is possible for a small, privately owned practice to successfully adopt EHR while increasing revenue. I heard people say it was only possible within a large hospital system, but saw many of those installations decrease office efficiency and quality of care. I heard people say primary care doctors couldn’t afford EHR, while we had not only done well with our installation, but did so with one of the more expensive products at the time. To me, it was just a matter of time before everyone finally saw that I was right.

The passage of the EHR incentive program (aka “meaningful use” criteria) was a huge validation for me: EHR was so good that the government would pay doctors to adopt it. I figured that once docs finally could implement an EHR without threatening their financial solvency, they would all become believers like me.

But something funny happened on the way to meaningful use: I changed my mind. No, I didn’t stop thinking that EHR was a very powerful tool that could transform care. I didn’t pine for the days of paper charts (whatever they are). I certainly didn’t mind it when I got the check from the government for doing something I had already done without any incentive. What changed was my belief that government incentives could make things better. They haven’t. In fact, they’ve made things much worse.

Medicare Advantage Star Ratings: Detaching Pay from Performance

May 23, 2012• 5

By Douglas Holtz-Eakin

Rewarding quality health plans is an admirable goal for the Medicare Advantage program. Unfortunately, the current system of linking star ratings to bonus payments and rebate adjustments instituted by the Patient Protection and Affordable Care Act (and expanded by the CMS Quality Bonus Payment Demonstration) fails to achieve that goal, and depending on its specific implementation, may even be counterproductive.

Because criteria for evaluation are not published until after the period for which performance will be evaluated, there is no possibility that MA plans will be able to improve their performance to achieve the goals CMS intends to incentivize. Any adjustment plans will be able to make to their bids or plan offerings would have to be aimed at increasing enrollment in counties with the highest bonuses and rebates based on data from performance in previous years, possibly at the expense of improving their performance in the future.

The system rewards beneficiaries for choosing those plans favored by the selected CMS criteria, rather than the plans that best meet their needs. In effect patients whose preferences, health status, and even counties of residence, don’t match the CMS model of a highly rated plan will be at a disadvantage. Simultaneously, the system will likely reduce the scope of choice available to MA-eligible beneficiaries, and reduce competition among MA plans.

Finally, the system rewards beneficiaries for living in counties with low poverty rates (since relatively wealthier counties tend to have more plans with higher ratings), thus adversely impacting poor beneficiaries even more than non-poor beneficiaries.

These impacts are inconsistent with the overall policy purpose. The goal of incentivizing quality health plans is legitimate and admirable; that goal will not be achieved by the rating structure currently being put into place.

Why the Fragility of Health Outcomes Research May Be a Good Outcome for Health

Apr 5, 2012• 1

By David Shaywitz, MD

Durably improving health is really, really hard.

I’ve discussed this in the context of drug discovery, which must contend with the ever-more-apparent reality that biology is incredibly complex, and science remarkably fragile. I’ve discussed this in the context of patient behavior, focusing on the need to address what Sarah Cairns-Smith and I have termed the “behavior gap.”

Here, I’d like to focus on a third challenge: measuring and improving the quality of patient care.

I’ve previously highlighted the challenges faced by Peter Pronovost of Johns Hopkins in getting physicians to adhere to basic checklists, or to regularly do something as simple and as useful as washing hands, topics that have been discussed extensively and in a compelling fashion by Atul Gawande and others.

Several recent reports further highlight just how difficult it can be not only to improve quality but also to measure it.

Consider the recent JAMA article (abstract only) by Lindenauer et al. analyzing why the mortality rate of pneumonia seems to have dropped so dramatically from 2003-2009. Originally, this had been attributed to a combination of quality initiatives (including a focus on processes of care) and clinical advances. The new research, however, suggests a much more prosaic explanation: a change in the way hospitals assign diagnostic codes to patients; thus, while rates for hospitalization due to a primary diagnosis of pneumonia decreased by 27%, the rates for hospitalization for sepsis with a secondary diagnosis of pneumonia increased by 178%, as Sarrazin and Rosenthal highlight in an accompanying editorial (public access not available).

The Melody Of Quality Measures: Harmonize And Standardize

Feb 21, 2012• 13

By Thomas Tsang, MD and Faraz Ahmad, MD

With unsustainably high costs and tremendous gaps in quality and patient safety, the health care system is ripe with opportunities for improvement. For years, many have seen quality measurement as a means to drive needed change. Private and public payers, public health departments, and independent accreditation organizations have asked health care providers to report on quality measures, and quality measures have been publicly reported or tied to financial reimbursement or both.

Throughout the Affordable Care Act (ACA), quality measures are tied to reimbursements in multiple programs. It is critical that the Department of Health and Human Services (HHS) move forward with a strategy for measure harmonization that will accommodate local and national needs to evaluate outcomes and value. Additionally, a standard for calculation measures such as the use of a minimal data set for the universe of measures should be considered.

The field of quality measurement is at a critical juncture. The Affordable Care Act (ACA)—which mentions “quality measures,” “performance measures,” or “measures of quality,” 128 times—heightened an already growing emphasis on quality measurement. With so much focus on quality, the resource burden on health care providers of taking and reporting measures for multiple agencies and payers is significant.

Furthermore, the field itself is being transformed with the continued adoption of electronic health records (EHRs). Traditional measures are largely based on administrative or claims data. The increased use of EHRs create the opportunity to develop sophisticated electronic clinical quality measures (eQMs) leveraging clinical data, which when linked with clinical decision support tools and payment policy, have the potential to improve quality and decrease costs more dramatically than traditional ones. Innovative electronic measures on the horizon include “delta measures” calculating changes in patient health over time and care coordination measures for the electronic transfer of patient information (i.e., hospital discharge summary or consultant note successfully transmitted to the primary care physician). Additionally, traditional data abstraction methodologies for clinical data require labor intensive, chart review processes, which would be eliminated if data could be electronically extracted.

Top-Down vs. Bottom-Up

Sep 28, 2011• 2

By BOB WACHTER, MD

In my last post, I discussed the role of physicians in patient safety in the US and UK. Today, I’m going widen the lens to consider how the culture and structure of the two healthcare systems have influenced their safety efforts. What I’ve discovered since arriving in London in June has surprised me, and helped me understand what has and hasn’t worked in America.

Before I arrived here, I assumed that the UK had a major advantage when it came to improving patient safety and quality. After all, a single-payer system means less chaos and fragmentation—one payer, one regulator; no muss, no fuss. But this can be more curse than blessing, because it creates a tendency to favor top-down solutions that—as we keep learning in patient safety—simply don’t work very well.

To understand why, let’s start with a short riff on complexity, one of the hottest topics in healthcare policy.

Complexity R Us

Complexity theory is the branch of management thinking that holds that large organizations don’t operate like predictable and static machines, in which Inputs A and B predictably lead to Result C. Rather, organizations operate as “complex adaptive systems,” with unpredictability and non-linearity the rule, not the exception. It’s more Italy (without the wild parties) than Switzerland.

Complexity theory divides decisions and problems into three general categories: simple, complicated, and complex. Simple problems are ones in which the inputs and outputs are known; they can be managed by following a recipe or a set of rules. Baking a cake is a simple problem; so is choosing the right antibiotics to treat pneumonia. Complicated problems involve substantial uncertainties: the solutions may not be known, but they are potentially knowable. An example is designing a rocket ship to fly to the moon—if you were working for NASA in 1962 and heard President Kennedy declare a moon landing as a national goal, you probably believed it was not going to be easy but, with enough brainpower and resources, it could be achieved. Finally, complex problems are often likened to raising a child. While we may have a general sense of what works, the actual formula for success is, alas, unknowable (if you’re not a parent, trust me on this).

5 Ways You Can Avoid Being Misdiagnosed

Sep 15, 2011• 15

By EVAN FALCHUK

Billionaire Teddy Forstmann has apparently been diagnosed with a serious form of brain cancer. There’s a tragic twist to the story: according to Fox Business News, Forstmann believes that for more than a year, he had been misdiagnosed with meningitis.

ABC News wonders:

How could such a misfortune befall a billionaire —- a man able to afford the best doctors, best technology and the most sophisticated diagnostic tests?

They’re missing the point. Misdiagnosis happens with shocking regularity – as much as 44% of the time, depending on the illness.

I’m sure that, as with most things, being a billionaire is better. But as a neurosurgeon quoted by ABC News points out, even for a billionaire, getting the right care is “still a bit of a crap shoot.”

So how can you improve your odds? Here are 5 tips that work.

1. Know your family history – and remind your doctor of it. Don’t assume your doctor remembers that time you told him that two of your aunts died of breast cancer, or that your grandfather and father have a history of malformed blood vessels in their brains. Research studies have shown that a family history may be a better predictor of disease than even genetic testing. Find out about your family’s medical history, write it down (the Surgeon General has a good on-line tool to help you do this), and make sure your doctor knows about it – especially if you’re sick and they’re trying to decide what’s wrong.

2. Ask questions. The typical doctor sees as a many as 40 patients a day, spending 15 minutes or less with each one. It’s all too easy to be referred to a specialist and start treatment without having all of your questions answered. But asking questions won’t just make you feel more comfortable – it can disrupt your doctor’s thought process and make him think about your case in a way that may save your life. Dr. Jerome Groopman, one of the world’s foremost researchers on how doctors think (he’s written the definitive book on it) agrees:

“Doctors desperately need patients and their families and friends to help them think. Without their help, physicians are denied key clues to what is really wrong. I learned this not as a doctor but when I was sick, when I was the patient.”

You can find some useful tips on how to do this at the U.S. government’s web site, called “Questions are the Answer.”

New Research Finds EHRs Improve the Quality of Diabetes Care

Sep 6, 2011• 3

By RANDALL D. CEBUL, MD

Two years ago in an address to Congress, President Obama declared his commitment to invest in electronic health records (EHRs), saying he thought it was perhaps the best way to quickly improve the quality of American health care. Just two years later, that hunch is proving true in Cleveland, Ohio.

New EHR Research Findings:

This week, the New England Journal of Medicine released research authored by my colleagues and me at Better Health Greater Cleveland showing that physician practices that use electronic health records had significantly higher achievement and improvement in meeting standards of care and outcomes in diabetes than practices using paper records.

Though most of us assumed EHRs would have some effect on patient care, we were delighted by what’s proving to be the reality in greater Cleveland. Just consider:

Care is better: Nearly 51% of patients in EHR practices received care that met all of the endorsed standards.

Only 7% of patients at paper-based practices received this same level of care– a difference of 44%.
After accounting for differences in patient characteristics between EHR and paper-based practices, EHR patients still received 35% more of the care standards.
Just fewer than 16% of patients at paper-based practices had comparable results.
After accounting for patient differences, the adjusted gap remained 15% higher for EHR practices.

Continue reading…

Peter Pronovost is a Liar. He Must Be. Isn’t He?

Aug 23, 2011• 1

By PAUL LEVY

Peter Pronovost and his subversive friends are at it again. Imagine, first they assert that implementation of a standard protocol and checklist could reduce the rate of central line associated bloodstream infections.

“It wouldn’t work here. Our patients are sicker.”

Then, to make matters worse, they go and contend that reducing the rate of central line infections saves money. Here’s the abstract from the American Journal of Medical Quality:

This study calculates the costs and benefits of a patient safety program in intensive care units in 6 hospitals that were part of the Michigan Keystone ICU Patient Safety Program. On average, 29.9 catheter-related bloodstream infections and 18.0 cases of ventilator-associated pneumonia were averted per hospital on an annual basis. The average cost of the intervention is $3375 per infection averted, measured in 2007 dollars. The cost of the intervention is substantially less than estimates of the additional health care costs associated with these infections, which range from $12,208 to $56,167 per infection episode. These results do not take into account the additional effect of the Michigan Keystone program in terms of reducing cases of sepsis or its effects in terms of preventing mortality, improving teamwork, and reducing nurse turnover.