Author Archives

maithri

Healthcare.gov and the History of Failed IT Projects

Apr 3, 2014• 14

By Niam Yaraghi

Many years before the creation of Healthcare.gov, President Obama embraced data analytics during his early years in the Senate.

In 2006, he and senator Tom Coburn (R-Okla.) successfully sponsored the Federal Funding Accountability and Transparency Act, which resulted in creation of usaspending .gov, “a significant tool that makes it much easier to hold elected officials accountable for the way taxpayer money is spent“.

A History of Failed Federal IT Projects

A considerable amount of taxpayer money is spent on federal IT projects, but in contrast to the aspirations of Obama in his early years in the Senate, it is not spent responsibly.

According to the Standish Group report, from 2003 to 2012 only 6% of the federal IT projects with over 10 million dollars of labor cost were successful.

52% of them were either delayed, went over budget or did not meet user expectations. The remaining 41% of the IT projects were abandoned or started from scratch. Perhaps most troubling is that healthcare.gov is just a one example among many.

7.1 Million. Will the Obama Administration Regret Today’s Announcement?

Apr 1, 2014• 22

By Robert Laszewski

Politics is about expectations.

The Obama administration blew the doors off Obamacare’s enrollment expectations this week and scored big political points.

But in doing so, they may have set Obamacare’s expectations going forward at a level that can only undermine their credibility and that of the new health law.

What happens when the real number––the number of people who actually completed their enrollment––comes in far below the seven million?

What happens when the hard data shows that most of these seven million were people who had coverage before?

What happens when it becomes clear that the Obamacare insurance exchanges are making hardly a dent in the number of those uninsured?

Yesterday, the Los Angeles Times reported that the non-profit Rand Corporation estimated that two-thirds of the first six million people to enroll in Obamacare were previously insured––only two million were previously uninsured.

If all of the one million people who signed up in the last week were previously uninsured, that would mean that only three million previously uninsured people have purchased coverage in the government-run exchanges.

Rand also estimated that about nine million people have enrolled directly with the insurance companies, bypassing the government-run exchanges. But Rand also reported that the vast majority of those were previously insured.

If 20% do not pay, as has been the case since Obamacare launched, then the real Obamacare exchange enrollment number is about 5.7 million.

The Rest of the Story on Health Exchange Enrollment

Apr 1, 2014• 3

By Paul Keckley

This morning, the tally of enrollees in health exchanges is between 6 and 7 million.

Many of these will not finalize their paperwork until April 15, and many more might not pay their premiums.

Nonetheless, given the underwhelming rollout of Healthcare.gov, and well-funded campaigns in some states to discourage enrollment, the number is impressive. But the rest of the story is more important.

In coming weeks, these questions will be answered:

How many of these new enrollees will actually pay their premiums next month and be insured?

Are the new enrollees healthy or sick and in need of medical attention? How will the delivery system respond to these needs?

Did the penalty induce enrollment, or were other factors more important to individuals? Was it the attractiveness of subsidies or something else?

How will employers that provide health coverage assess the viability of health exchanges in their benefits strategies? Can these exchanges serve as a viable marketplace for employee insurance purchases (and allow employers to shift purchasing responsibility to their employees)?

More Evidence That Patient Centered Medical Homes Don’t Work

Apr 1, 2014• 18

By Al Lewis

A state the size of Vermont claiming savings of $120,000,000 through a patient-centered medical home (PCMH) program should raise eyebrows.

North Carolina made similar claims about its PCMH model, only to have the results so thoroughly debunked that consulting firm, Milliman, was forced to retract its key assertion.

I expect more from Vermont, if only because I’m a Democrat and Vermont has turned so “blue” that in 2008 John McCain received only 10,000 more votes than Calvin Coolidge garnered in 1924. However, it turns out red states don’t have a monopoly on invalid PCMH data.

A brief summary of the Vermont Blueprint for Health, as described in the enabling legislation, would be: “a program for integrating a system of healthcare for patients, improving the health of the overall population…by promotion health maintenance, prevention, and care coordination and management.”

This is to be achieved by emphasizing the usual suspects — patient-centered medical homes and various support mechanisms for them. The idea is to achieve “a reduction in avoidable acute care (emergency visits and inpatient admissions).”

Growth in participation has been phenomenal. In 2009, only a few practices and a dozen employees were involved, so we can call that the baseline year. The report’s findings take us through 2012, by the end of which two-thirds of the state’s primary care practices (104) and population (423,000) were involved, along with 114 full-time employees.

The State’s Analysis

Through the end of 2012, the state — by using the classic fallacy (also embraced by the wellness industry) of comparing participants to non-participants — was able to show savings of $120,000,000 and a double-digit ROI.

Where the ACOs Are

Apr 1, 2014

By Peter Ubel, MD

The Affordable Care Act established several programs to promote the formation of Accountable Care Organizations.

These ACOs are a relatively new way of organizing healthcare delivery, in which healthcare providers join together – perhaps across physician groups and hospitals – to care for a population of patients, and are then held accountable both for the cost and quality of the care they deliver to those patients.

This accountability cuts both ways – if they spend too much money on such patients and provide low quality of care, they might face financial repercussions, but if they offer high quality at a lower than expected cost, they might be rewarded with part of those cost savings.

A recent study gives us a glimpse of where the ACOs are forming in the United States. You will see they are not being formed everywhere, but instead are heavily concentrated in the southern and eastern United States:

The study also shows that these organizations are disproportionately made up of large, nonprofit healthcare systems, but not ones classified as public hospitals.

Is Medicine a Big Data Problem?

Mar 29, 2014• 4

By Ted Driscoll

Human beings are big data. We aren’t just 175 pounds of meat and bone. We aren’t just piles of hydrogen and carbon and oxygen. What makes us all different is how it’s all organized and that is information.

We can no longer treat people based on simple numbers like weight, pulse, blood pressure, and temperature. What makes us different is much more complicated than that.

We’ve known for decades that we are all slightly different genetically, but now we can increasingly see those differences. The Hippocratic oath will require doctors to take this genetic variability into account.

I’m not saying there isn’t a place for hands-on medicine, empathy, psychology and moral support. But the personalized handling of each patient is becoming much more complicated. The more data we can gather, the more each individual is different from others.

In our genome, we have approximately 3 billion base pairs in each of our trillions of cells. We have more than 25,000 genes in that genome, sometimes called the exome. Each gene contains instructions on how to make a useful protein. And then there are long stretches of our genomes that regulate those protein-manufacturing genes.

In the early days, some researchers called this “junk DNA” because they didn’t know what it did. But this was foolish because why would evolution conserve these DNA sequences between genes if they did nothing? Now we know they too do things that make us unique.

For Hospitals and Health Systems: Strategies for Doing More with Less

Mar 28, 2014• 20

By Joe Flower

The conversation has changed.

The old conversation: “You cost too much.”

“But we have these sunk costs, patients who can’t pay … ”

“OK, how about a little less then?”

The new conversation: “You cost too much. We will pay half, or a third, of what you are asking. Or we will take our business elsewhere. Starting now.”

“But … but … how?”

Exactly: How will you survive on a lot less money? What are the strategies that turn “impossible” to “not impossible”?

New Strategies
The old conversation arises from the classic U.S. health care model: a fully insured fee-for-service system with zero price transparency, where the true costs of any particular service are unknown even to the provider. The overwhelmingly massive congeries of disjointed pieces that we absurdly call our health care “system” rides on only the loosest general relationship between costs and reimbursements.

It’s a messy system littered with black boxes labeled “Something Happens Here,” full of little hand waves and “These are not the droids you’re looking for.”

With bundling, medical tourism, mandated transparency, consumer price shopping, and reference pricing by employers and health plans, we increasingly are being forced to name a price and compete on it. Suddenly, we must be orders of magnitude more precise about where our money comes from and where it goes: revenues and costs.

We must find ways to discover how each part of the strategy affects others. And we need some ability to forecast how outside forces (new competition, new payment strategies by employers and health plans, new customer handling technologies) will affect our strategy.

Key Strategy Questions
For decades, whenever some path to profit in health care has arisen (in vitro fertilization, urgent care, retail, wellness and the others) most hospitals have said as if by ritual, “That is not the business we are in.” As long as we got paid for waste, few health care organizations got serious about rooting it out.

And most have seemed content with business structures that put many costs and many sources of revenue beyond their control.

In the Next Health Care, the key strategy questions become:

Why are you not capturing as many revenue streams as possible?

How PCORI’s Research Will Answer the Real World Questions Patients Are Asking

Mar 27, 2014• 8

By Joe Selby, MD

As a physician, I know the challenge of helping patients determine which health care options might work best for them given their personal situation and preferences.

Too often they — and their clinicians — must make choices about preventing, diagnosing and treating diseases and health conditions without adequate information. The Patient-Centered Outcomes Research Institute (PCORI) was created to help solve this problem — to help patients and those who care for them make better-informed health decisions.

Established by Congress through the Patient Protection and Affordable Care Act as an independent research institute, PCORI is designed to answer real-world questions about what works best for patients based on their particular circumstances and concerns. We do this primarily by funding comparative clinical effectiveness research (CER), studies that compare multiple care options.

But more research by itself won’t improve clinical decision-making. Patients and those who care for them must be able to easily find relevant evidence they can trust. That’s why our mandate is not just to fund high-quality CER and evidence synthesis but to share the results in ways that are meaningful to patients, clinicians and others.

We’re also charged with improving the methods used in conducting those studies and enhancing our nation’s capacity to do such research.

We will be evaluated ultimately on whether the research we fund can change clinical practice and help reduce the variations and disparities that stand between patients and better outcomes. We’re confident that the work we’re funding brings us and the audiences we serve closer to that goal.

Recently, some questions have been raised in health policy circles about our holistic approach to PCORI’s work. That view holds that direct comparisons of health care options — especially those involving high-priced interventions — should be the dominant if not sole focus of PCORI’s research funding approach as a path to limiting the use of expensive, less-effective options.

We agree that discovering new knowledge on how therapies compare with one another is a critical mandate of PCORI and is essential to improving the quality and effectiveness of care. However, ensuring that patients and those who care for them have timely access to and can use this knowledge, so that they can effectively apply it to improve their decisions, is also very important.

Here’s How We Can Fix Obamacare if We Act Now and Stop Pretending the Problems Don’t Exist

Mar 26, 2014• 30

By Robert Laszewski

To properly price the exchange health insurance business going forward the carriers have to sharply increase the rates.

A senior executive for Wellpoint, which sells plans in 14 Obamacare exchanges, is quoted in a Reuters article telling Wall Street analysts there will be big rate increases in 2015, “Looking at the rate increases on a year-over-year basis on our exchanges, and it will vary by carrier, but all of them will probably be double digits.”

If the health plans do issue double digit rate increases for 2015, Obamacare is finished.

There are a ton of things that need to be fixed in Obamacare. But, I will suggest there is one thing that could save it.

The health insurance companies have to submit their new health insurance plans and rates between May 27 and June 27 for the 2015 Obamacare open-enrollment period beginning on November 15th. Any major modifications to the current Obamacare regulations need to be issued in the next month to give the carriers time to adjust and develop new products.

If the administration goes into the next open enrollment with the same unattractive plan offerings costing a lot more than they do today, they will not be able to reboot Obamacare.

Simply, health insurance plans that cost middle-class individuals and families 10% of their after-tax income and have average Silver Plan deductibles of more than $2,500 a month are not attractive and people won’t buy them any more enthusiastically next fall than they already have. See: Obamacare: The Uninsured Are Not Signing Up Because the Dogs Don’t Like It

Doubling the fines for not buying in 2015 will only give the Democrats more political problems––and it doesn’t look to me like they are going to enforce the fines anyway.

Health insurance plan executives are now faced with a daunting decision. How do they price the 2015 Obamacare exchange plans?

Even if the administration announces they have signed-up about 6 million people by March 31, the number of people enrolling would be well below expectations––only about 25% of those subsidy eligible will have signed up by the deadline. An enrollment that small guarantees the risk pool is sicker and more expensive than it needs to be in order to be sustainable.

But dramatically increasing the rates will only assure even fewer healthy people will sign up for 2015 and some of those who signed up for 2014 will back out over the higher rates. This is what a “death spiral” looks like.

Google Flu Trends Shows Good Data > Big Data

Mar 26, 2014• 3

By Kaiser Fung

In their best-selling 2013 book Big Data: A Revolution That Will Transform How We Live, Work and Think, authors Viktor Mayer-Schönberger and Kenneth Cukier selected Google Flu Trends (GFT) as the lede of chapter one.

They explained how Google’s algorithm mined five years of web logs, containing hundreds of billions of searches, and created a predictive model utilizing 45 search terms that “proved to be a more useful and timely indicator [of flu] than government statistics with their natural reporting lags.”

Unfortunately, no. The first sign of trouble emerged in 2009, shortly after GFT launched, when it completely missed the swine flu pandemic. Last year, Nature reported that Flu Trends overestimated by 50% the peak Christmas season flu of 2012. Last week came the most damning evaluation yet.

In Science, a team of Harvard-affiliated researchers published their findings that GFT has over-estimated the prevalence of flu for 100 out of the last 108 weeks; it’s been wrong since August 2011.

The Science article further points out that a simplistic forecasting model—a model as basic as one that predicts the temperature by looking at recent-past temperatures—would have forecasted flu better than GFT.

In short, you wouldn’t have needed big data at all to do better than Google Flu Trends. Ouch.

In fact, GFT’s poor track record is hardly a secret to big data and GFT followers like me, and it points to a little bit of a big problem in the big data business that many of us have been discussing: Data validity is being consistently overstated.

As the Harvard researchers warn: “The core challenge is that most big data that have received popular attention are not the output of instruments designed to produce valid and reliable data amenable for scientific analysis.”

The amount of data still tends to dominate discussion of big data’s value. But more data in itself does not lead to better analysis, as amply demonstrated with Flu Trends. Large datasets don’t guarantee valid datasets. That’s a bad assumption, but one that’s used all the time to justify the use of and results from big data projects.