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How Doctors Became Subcontractors

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By MICHEL ACCAD, MD

Screen Shot 2015-10-01 at 9.46.12 AMIn our healthcare system, the “middleman” is not who you think

During my recent podcast interview with Jeff Deist, president of the Ludwig von Mises Institute, I remarked that third-party payers are not, in fact, intermediaries between doctors and patients. In reality, it is the physician who has become a “middleman” in the healthcare transaction or, as I argued, a subcontractor to the insurer.

Important as it is, this reality is not well recognized—not even by physicians—because when doctors took on this “role” in the late 1980’s, the process by which healthcare business was conducted did not seem to change in any visible way.

When health insurance was first introduced on a large scale in the 1940’s and 1950’s, a patient would see a doctor and pay the bill directly. The doctor would issue a receipt and the patient would submit the receipt to the insurance company for reimbursement. The insurance company was, in that sense, a financial intermediary since it would enable the patient to afford the care and see the doctor.

Overtime, as the cost of medical care began to rise rapidly, a practice evolved whereby physicians would take it upon themselves to submit the claim to the insurance company and would not require patients to pay upfront.

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Uber’s Surge Pricing May not Lead to a Surge In Drivers

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By LAUREN KIRCHNER

Screen Shot 2015-10-30 at 3.43.02 PM

Uber has long stirred controversy and consternation over the higher “surge” prices it charges at peak times. The company has always said the higher prices actually help passengers by encouraging more drivers to get on the road. But computer scientists from Northeastern University have found that higher prices don’t necessarily result in more drivers.

Researchers Le Chen, Alan Mislove and Christo Wilson created 43 new Uber accounts and virtually hailed cars over four weeks from fixed points throughout San Francisco and Manhattan. They found that many drivers actually leave surge areas in anticipation of fewer people ordering rides.

“What happens during a surge is, it just kills demand,” Wilson told ProPublica. “So the drivers actually drive away from the surge.”

When contacted this week, Uber said that their own analysis has shown that surge pricing does, in fact, attract more drivers to surge areas. “Contrary to the findings in this report — which is based on extremely limited, public data — we’ve seen this work in practice day in day out, in cities all around the world,” Uber spokeswoman Molly Spaeth wrote in an email.

The researchers also uncovered a few tips about how to avoid surge prices. They found that changing your location, even by a few hundred feet, can influence the price you get. They also discovered that you can often get back to normal fare levels by waiting as few as five minutes.

“The vast majority of surges are short-lived, which suggests that savvy Uber passengers should ‘wait-out’ surges rather than pay higher prices,” the authors wrote in a new study they are presenting at a conference in Tokyo on Friday.

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ACA Open Enrollment Round 3: The Going Gets Tougher

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By STEVE FINDLAY

Screen Shot 2015-08-26 at 12.13.13 PMThe third ACA health insurance exchange open enrollment period begins Nov. 1, and things look iffy. The Obama administration this month reduced the estimate of new enrollees for 2016—possibly to lower expectations but also because signs point to the difficulty of luring the remaining uninsured into the fold over the next few years.

It’s time for some fresh strategies to ramp up enrollment and get where we need to go. At the end of this piece I offer some suggestions and invite yours. (This article assumes the ACA will be in place over the next five years even if a Republican becomes president in 2017.)

Health insurance numbers can be confusing (and hyped out of context from both sides of the political aisle), so here’s a quick rundown of the current situation and the Obama Administration’s new projections.

The current U.S. population is 326 million. According to the Census Bureau’s latest authoritative annual report (released in Sept) 10.4% of the population, or 33 million people, were uninsured for the entire year in 2014. That’s down sharply from 13.3%, or 41.8 million people, in 2013. Thus, as of the end of 2014, there were 8.8 million fewer uninsured people, due primarily to Obamacare.

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Who Is to Blame for Health Care’s Problems? A Tale of Two Narratives

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By JEFF GOLDSMITH

Jeff GoldsmithWhat to do about the seemingly inexorable rise in health spending has been the central health policy challenge for two generations of health economists and policymakers. In 1965, before Medicare and Medicaid, health spending was about 5.8 percent of GDP. In 2013, it was nearly 18 percent. And GDPquadrupled during this same period.

Over the past 30 years, there are been two warring political narratives explaining health spending growth, with two different culprits and indicated remedies. At their cores, these narratives blame the main actors in the health care drama—patients and physicians—for rising costs.

The Conservative Narrative: The Patient As Culprit

The conservative thesis holds that the demand for health care is unlimited because it has been, historically, a free good for many patients. Moreover, the argument runs, much illness is driven by bad personal health choices — for example, smoking and obesity, and the heart disease and diabetes that follows. Thus, much of our cost problem is actually the patient’s fault.

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Sex, Lies and Cheeseburgers

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By AL LEWIS

Screen Shot 2015-10-28 at 7.22.07 AMNumber of deaths attributable to eating processed meat, according to the World Health Organization (WHO): 34,000

Number of people struck by lightning annually: 240,000

And yet the WHO generated a huge headline by saying that eating red and processed meat could increase your risk of colon cancer by 18%.

Let us assume that they are right. (And we will let the trade associations debate them on the scientific merits of that 34,000 figure.) Even if they are right, this is a perfect example of confusing an increase in relative risk of one disease with absolute risk of dying. To use the lightning example, you probably have a 1-in-a-billion chance of being struck by lightning if a thunderclap is audible but the sky above is clear.

Some states close public pools when that happens. If the sky above is clear but you can see lightning in the distance, your odds of getting struck may jump to 1-in-100,000,000. That’s a 10-times relative increase, but only a 9-in-a-billion absolute increase. So these states inconvenience parents and fidgety kids for basically no reason other than misunderstanding relative and absolute risk.

To make matters worse, the WHO conflates the risk of smoking and asbestos with red meat. Both the former cause perhaps something like an 18% increase in age-adjusted death rates in total, not an 18% increase in one form of cancer. The difference? Probably about a thousand times in total, unvarnished, absolute risk.

Yes, I know it’s not always about me (my ex-wife was quite clear on this) but this is exactly what Quizzify teaches. Newscasters who had taken the Quizzify quiz (and relative-vs-absolute risk is in the advanced level…but they are newscasters so they should get to that level) would have led with the headline: “WHO Demonstrates No Understanding of Health” instead of “You Could Die from Eating Red Meat”.

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Is Health IT Finally Ready to Tackle Last-Mile Analytics?

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By DAN HOUSMAN

DAN HOUSMANI have spent several years working with specialty medical offices like oncology centers, diabetes clinics, IPAs (Independent Practice Associations), and disease advocacy groups seeking to build health care data warehouses and analytics solutions. During that time, I have seen the same concerns pop up over and over: “How can we understand the value and impact of our care if we only see the component of care that we provide? If we can’t understand our value, then how can we make sure that we are optimizing our care, getting reimbursed for our impact, and executing leading research in our specialties that helps find better medical treatments for our patients? How can we really care for patients effectively in the first place?”

Organizations are highly restricted in the ways they share data. HIPAA allows for data sharing between entities, but doesn’t provide for any mechanism or incentives to do so efficiently or in a scalable method. Also, the groups who should be sharing may find themselves in competitive situations where sharing could be perceived as risky. But in spite of this, some exciting developments have quietly been moving forward in the past few years that can help fill in pieces of the data last mile.

The rise of Meaningful Use 2 (MU2) compliant electronic medical records (EMR) with the objective to enable health information exchange (HIE) between systems now represents a potential solution to this challenge that has been exacerbating the fragmentation of the health care industry for years. Public HIEs have not yet demonstrated that they can resolve analytics issues or workflow changes. Instead, there are some new and useful models of HIE that show great promise that are likely being adapted from the lessons learned from the original HIE designs.

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Healthcare’s Deadly Data Problem

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By LEONARD D’AVOLIO

Screen Shot 2015-10-09 at 8.03.52 AMI have read with interest the ongoing conversation about the ProPublica Surgeon Scorecard in THCB and beyond, not because I believe this latest effort at measuring quality will have a significant effect on patient care, but because behind the latest public metric debate – in fact behind all healthcare metric debates – is a major systemic problem.  This problem somehow always seems to remain unseen.  We acknowledge that measuring healthcare quality is difficult and that using medical data is challenging, but I’m not convinced that people completely understand why or how measurement and data are so difficult in healthcare…nor am I certain that everyone understands the repercussions of those challenges.  

As I wrote here, the most promising recent development in medicine is the emphasis on learning from our data.  We are finally digitizing records of clinician and patient interactions via the adoption of EMRs.  Data warehousing technologies are connecting healthcare’s disparate systems and making data accessible to decision makers.  Data will be the foundation for healthcare improvement.  However, it is dangerous to assume that accessing raw data is equivalent to accessing relevant information.

All of today’s widely adopted EMR systems were designed to fulfill three purposes:  financial reimbursement, narrative communication among clinicians, and legal protection.  Now, we aim to use that data for very different purposes: the improvement of health and the discovery of process efficiencies.  The impact of the resulting inconsistencies between design and use cannot be overstated, and yet no one else seems to be stating those impacts at all.  

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Pink is The New Black

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By DAVID EICHLER

Pink is the new black this October, which marks the 30th anniversary of National Breast Cancer Awareness Month. NFL players are clad in bright pink shoes and wrist bands. American Airlines employees are wearing pink uniform accents and serving complimentary pink lemonade. Police departments across the country are patrolling in pink cruisers. It’s all for a great cause. The money and awareness raised through this campaign helps to fight an insidious disease that will kill more than 40,000 women in the U.S. this year.

But the feel-good spirit is clouded by ongoing debate around the value of breast cancer screening, which is sure to be reignited by the recent announcement of new guidelines by the American Cancer Society. A recent study by JAMA Internal Medicine concluded that more frequent mammography screening results in the “widespread overdiagnosis” of breast cancer, and one its authors opined that, because of the harms caused by false alarms and unnecessary treatment of non-life threatening cancers, we should be doing fewer screenings, not more. This logic is based on data that shows more screening is associated with detection of small cancers but not with serious late-stage cancers or the overall death rate due to breast cancer.

The controversy over too much or too little mammography is completely missing the point. The real problem is our one-size-fits-all approach to breast cancer screening. It doesn’t work—especially not for the nearly 50% of women in the U.S. who have dense breast tissue.

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