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The Art Of The Apology: What Not To Say When Things Go Wrong

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By TONY JEWELL

There were two high-profile apologies in the news this week — by the Leader of the Free World and by a Man Who Makes Yoga Pants.

Neither was well executed and neither was well received.

Let’s start with President Obama, who offered his belated apology on the rollout of the federal health exchange at the heart of the Affordable Care Act. After more than five weeks of shifting stories, blame and timelines, the president sat down with Chuck Todd to say “I’m sorry” for repeatedly saying some variation of, “If you like your health plan, you can keep it. Period.”

Sort of.

“I am sorry that they are finding themselves in this situation based on assurances they got from me,” he told NBC News. “We’ve got to work hard to make sure that they know we hear them and we are going to do everything we can to deal with folks who find themselves in a tough position as a consequence of this.”

Critics quickly and loudly objected to the president’s use of passive voice — and the fact that he claimed people found themselves with cancelled plans “based on assurances they got from me.” They pointed out that it wasn’t the assurances that cancelled the plans; it was the way Obama’s administration wrote the regulations that required insurance companies to cancel the plans.

In short, Obama didn’t own the cause of the pain. He only apologized for the “assurances” (which, by almost all accounts, are better known as “lies”).

Now, the Man Who Makes Yoga Pants.

Lululemon founder Chip Wilson got in hot water for blaming women’s bodies for well-publicized problems with his company’s yoga clothes, including see-through pants and pilling:

“Even our small sizes would fit an extra large, it’s really about the rubbing through the thighs, how much pressure is there … over a period of time, and how much they use it,” he said.

Well, then.

This, of course, led to a predictable backlash — particularly on the company’s Facebook page, where women shared their views of the company and Wilson’s basically saying “You’re too fat to wear our clothes.”

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Information Asymmetry – The Politics of Health IT Policy

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By ADRIAN GROPPER, MD

Let’s recognize Healthcare.gov as the dawn of mass patient engagement – and applaud it. Before this website, patients were along for the ride. Employers choose most of the insurance benefits, hospital web portals are an afterthought, and getting anything done with an insurance company, for both doctors and patients, means a phone call and paper. Can you imagine going online to find out the actual cost and buy anything? All that changed with Healthcare.gov.

Information is valuable and not evenly distributed. The haves are immensely valuable corporations. The have nots are patients and doctors. Welcome to the world of health IT politics where the rich get richer ($20 Billion of “incentives” have caused massive health IT consolidation and a hidden health surveillance state) and the poor get frustrated (talk to an independent physician about their EHR or to a patient trying to access her own health records).

Information asymmetry drives $1 Trillion waste of our $2.7 Trillion health care cost. That waste is about $3,000 per year per citizen.

The politics of health IT policy are not left vs. right but institution vs. individual. Politicians and regulators alike are now scrambling to understand the role of health IT policy in that $3,000 annual waste per citizen.

The asymmetry that drives health IT policy is easy to understand when you consider that health IT is sold to corporations. As physicians and patients, we do not prescribe or buy information technology and we are paying the price through a total lack of price and quality transparency.

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UCSF’s Wikipedia Experiment: Should Med Students Get Credit For Curating Medical Information Online?

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By JOHN SCHUMANN, MD

You’re a loyal THCB reader. You have a symptom. You Google it. One of the first three hits will be an entry about the symptom or an associated condition on Wikipedia.

As an informed lay person, you wonder, “How accurate is Wikipedia for medical information?”

You’ve always been a little skeptical of Wikipedia, but over the years you’ve found it more and more reliable for celebrity tidbits (e.g. “How old is Jane Lynch?” or “What was the name of that guy in “Crash?”) and sports trivia (“How many Super Bowls have the Minnesota Vikings lost?”).

In fact, it’s become quite useful for understanding geopolitics, ancient and recent history, and helping explain science topics (Higgs Boson, anyone?).

So why not medicine?

We in academic medicine look down our noses at Wikipedia. “Show us original texts,” we harrumph. “Where does the original data come from?” we ask our residents and students.

Just like high schoolers and college kids are warned NOT to use Wikipedia as a research tool, medical professors hold the site lowly in regard to seriousness of purpose.

Well, it’s time to accept reality.

We all use it, whether we admit it or not. Some of us a lot. The good news is, Wikipedia’s going to get even better in the medical realm.

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Hospital Exec Pay: If P4P is Good Enough for Doctors, Why Not the CEO?

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By Ashish Jha, MD

In my previous blog, I made the argument that whatever strategy we use to improve care in hospitals will not be implemented and executed well without proper focus by hospital leadership.  So, it is in this context, that we recently published some pretty disappointing findings that are worth reflecting on.

We examined the pay of CEOs across U.S. hospitals and found that some CEOs got paid a lot more than others.  This was not surprising.  CEOs of larger, urban, teaching hospitals get paid a lot more than CEOs of small, rural, non-teaching institutions.  But the disappointment was around quality:  we found no relationship between a hospital’s quality performance and the pay of the CEO.  Holding size, teaching, and other factors constant, what was the pay of CEOs of hospitals with high mortality rates?

About the same as CEOs of hospitals with low mortality rates.  What about other quality measures?  Most of them didn’t really seem to matter, with the exception of patient experience, which correlated nicely with CEO compensation.  It seems that when setting CEO compensation, patient outcomes are not a big part of the discussion.  How could this be, and why does it matter?

How you set incentives for senior managers says a lot about your priorities.  Boards generally set the salary for their CEOs and they clearly reward patient satisfaction scores.  That’s good.  They also seem to reward the things that build hospital reputations: having the latest technology such as a PET scanner or academic status.  But are boards rewarding CEOs based on mortality rates or adherence to basic quality metrics?  Not so much.  Why not?  I’ve spoken to a lot of board chairpersons over the years and the answer is not that they don’t care.  Most boards want to reward quality and believe that they do.

The problem is that most board members lack sufficient expertise on quality metrics and can’t decipher, from the large number of quality metrics, which ones are important (like mortality rates) and which ones are not.  Hamstrung, they focus on satisfaction but also end up rewarding things that feel like proxies for quality, such as having the latest technology.  And here’s the part that’s frustrating – our national efforts on quality measurement and improvement are not helping.  We seem to have done very little to prioritize what’s really important, and shine a light on them.

So what do we do to move forward?  Some states have started requiring that boards undergo training in quality.  Medicare, as a condition of participation, could certainly require that boards (or at least some members thereof) show a degree of expertise with quality.  I like these ideas but worry that training programs would themselves be of variable quality, and for some boards it would become an onerous requirement without achieving real gains in expertise.

Of course, if we really want to help boards be more effective and engage healthcare leaders, the biggest thing that we could do is actually reward hospitals, in a meaningful way, based on quality.  Yes, we have the value-based purchasing program, and it is well-intentioned.  But, as I’ve written before, it has several big problems.  First and foremost:  the incentives are very weak and there is little reason to believe it will have a meaningful impact on patient outcomes.  Second, the measures are diffuse – we have too many of them, some of which matter (mortality) and many which don’t in the absence of the appropriate clinical context (checking the ejection fraction on a heart failure patient).  It’s hard for hospital boards to really get a clear signal on what matters if they aren’t seeing it clearly and consistently from national leaders on quality.

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Hyperdiagnosis: The Wellness Industry Doubles Down on Overdiagnosis

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By AL LEWIS and VIK KHANNA

By now we are all familiar with the concept of overdiagnosis, where “we” is defined as “the readers of THCB and a few other people whose healthcare literacy is high enough to know when not to seek testing and/or when not to automatically believe the test results.”

The rest of the country hasn’t gotten the memo that, quite counter-intuitively, many suspected clinical problems should simply be left alone.  Many insignificant conditions get overdiagnosed and subsequently overtreated, at considerable cost to the health plans and risk to the patient.

For more information on that we  refer you to the book Overdiagnosed.   The thesis of that book is that insured Americans are far more likely to be harmed by too much care than too little.

Rather than use its resources and influence with human resources departments to mitigate overdiagnosis, most workplace wellness companies have opted for the reverse, taking overdiagnosis to a level which, were they physicians billing the government for this work, could cost them their licenses and possibly their freedom.   Instead, they win awards for it.

We call this new plateau of clinical unreality “hyperdiagnosis,” and it is the wellness industry’s bread-and-butter.  It differs from overdiagnosis four ways:  It is pre-emptive.  It is either negligently inaccurate or purposefully deceptive.  It is powered by pay-or-play forfeitures.  The final hallmark of hyperdiagnosis is braggadocio – wellness companies love to announce how many sick people they find in their screens.

1. Pre-Emptive

Most cases of overdiagnosis start at the doctor’s office, when a patient arrives to join the physician in a generally good faith search for a solution to a manifest problem.  The patient comes in need of testing.   By contrast, in hyperdiagnosis, there is neither a qualified medical professional providing adult supervision nor good faith.  The testing comes in need of patients, via annual workplace screening of up to seventy different lab values.  Testing for large numbers of abnormalities on large numbers of people guarantees large numbers of “findings,” clinically significant or not.  It is a shell game that the wellness vendor cannot lose.

2.Inaccurate or Deceptive

Most of these findings turn out to be clinically insignificant, no surprise given that the US Preventive Services Task Force recommends annual screening only for blood pressure, because otherwise the potential harms of screening outweigh the benefits.  The wellness industry knows this, and they also know that the book Seeking Sickness:  Medical Screening and the Misguided Hunt for Diseasedemolishes their highly profitable screening business model.   (We are not cherry-picking titles here—there is no book Hey, I Have a Good Idea:  Let’s Hunt for Disease.)  And yet most wellness programs require annual screens to avoid a financial forfeiture.   This includes the four programs covered on THCB this year — CVS, Nebraska, British Petroleum, and Penn State.

Those four programs and most others also obsess with annual preventive doctor visits.  Like screening, though, annual “preventive” visits on balance cause more harm than good, according to academic and lay reports.  The wellness industry knows this as well.  We have posted it on their LinkedIn groups, and presumably they have also access to Google.  They addressed the data by banning us from their groups.

3. Pay-or-play forfeitures

Because of the lack of value, the inconvenience, and privacy concerns, most employees would not submit to a workplace screen if left to their own devices.  The wellness industry and their corporate customers “solve” that problem by tying large sums of money annually — $600 for hourly workers at CVS, $1200 at Penn State and $521 on average – to participation in these schemes.  Yet participation rates are still low.  At Penn State, for example, less than half of all employees got screened despite the large penalty.

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Posts of Note: The 2013 Harvard Business School Cyberposium

By Grant Ho

This past weekend, I attended Cyberposium at Harvard Business School where I was invited to speak on the Healthcare Technology panel. Cyberposium is one of the largest MBA student-run tech conferences in the country and typically gets around 1,000 attendees — students, industry professionals, press, and VCs. This year was no different.

The atmosphere was buzzing. There’s always a certain energy at these events, and when you’re surrounded by individuals who are passionate about innovation and the curiosity and sense of possibility that come with it, it’s an exciting place to be.

The morning’s keynote featured Bill Clerico, CEO of WePay (a competitor to PayPal in the online payments space). Bill told us about his motivations for starting WePay, their journey to raise $20M, and how he and his team worked relentlessly to scale the organization.

His two big takeaways on what it takes to be a successful entrepreneur, especially if you’re just starting out: 1) you have to be scrappy and 2) you have to have maniacal focus on the customer (both when you acquire and service them). I couldn’t agree more. Personally, it was a reminder that as we grow bigger at CareCloud, we can never lose sight of our entrepreneurial roots.

After the keynote, I headed off to the Healthcare Technology panel. On the panel, I was joined by HCIT folks from Activate Networks, athenahealth, HealthTap, and Operating Analytics. Our panel was moderated by Zen Chu, serial healthcare entrepreneur and founder of MIT’s H@cking Medicine program (who earlier in the day, told me about a startup he recently invested in called Figure1 — think of it as a Pinterest for doctors).

The 50-minute discussion focused on the future of healthcare, from the impact of reform to emerging business models and trends in HCIT investing. As I think back on the panel and dozens of conversations throughout the day, a few things stood out:

1) Big data’s a big deal: Our panel immediately jumped into big data, with one of the more interesting discussions around what’s needed to reach the promised land called population health. For me, it’s about starting with a platform that can easily house both patient and claims data. You can’t have one or the other, you need both – especially as providers take more financial risk for care delivery.

More critically, as you build analytics on top of that, the platform needs to be scalable, have enough horsepower to aggregate and analyze all the information, and is interoperable so you can bring in new data sets from different sources (think genomics or the quantified self). The combination of storing administrative, financial, and clinical data in a powerful, cloud-based system is what we have at CareCloud today and in my view, is a critical enabler for big data going forward.

2) Selling to doctors is hard: During the panel, an audience member (a new HCIT entrepreneur) asked what’s the best way to sell to doctors. As a marketer, we work to connect with practices every day – helping them navigate through the pain of declining reimbursements, while easing their struggle with poorly designed HCIT. In my view, it’s a twofold solution.

First, it’s having a simple, flexible business model like SaaS-based pricing that makes finances easier on practices. Secondly, it’s developing products with “design thinking” from the start. You can build all the Meaningful Use features into your EHR, but if you’re making the doctor’s life harder and she can’t go home to see her family, you’ve failed. Usability has always been an obsession with us at CareCloud, and that’s why I’m so encouraged by the great work of our product teams, led by Edwin Miller, to make the fastest, most user-friendly HCIT solutions out there.

3) Engaging patients is even harder: Throughout the day, there was a lot of buzz about wearable devices like FitBit, mobile health apps like Ginger.io, and physician networks like HealthTap. While the growth of these tools is exciting, it made me realize how siloed all data is and how hard it will be to get patients to take action (I, for one, don’t walk an extra mile when Jawbone Up tells me I’ve hit less than 10,000 steps on any day).

Perhaps it’s linking all this disparate data into a patient portal so it reaches doctors and EHRs, incentivizing doctors on care planning (not just care delivery), or simply having patients pay a greater share of their healthcare spend.  However, in my view, a combination of integration and incentives are required to reduce the physician/patient asymmetry.

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How Many Patients Did We Hurt Last Month? Learning (But Not Too Much) From The Best Hospitals

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By ASHISH JHA, MD

I was recently chastised by a colleague for being too negative in one of my pieces on hospital care. His is a remarkable story of what happens when things go well, and it has made me think a lot about why, in some places, things seem to work while in others, not so much.

He told me how a few months ago, soon after returning to Boston from a trip to China, he had started feeling short of breath. When his cardiologist convinced him to be evaluated, he found himself at the Beth Israel Deaconess Medical Center (BIDMC), arriving in the ER late one evening.  He was triaged within minutes, had an EKG within 15 minutes, at which time comparisons were made to previous EKGs.  After ruling out a heart attack, his ER physicians quickly ordered a CT Angiogram.

That test, completed within an hour of his initial arrival to the ER, revealed the reason for his shortness of breath:  he had a large saddle pulmonary embolus.  He was started immediately on IV heparin and sent quickly to the ICU, experiencing essentially no delay in care.  He spent three days there and reports receiving care that was attentive, expert, and consistently of the highest quality.  Even after discharge, he received two nursing visits at home to ensure he was doing OK.  In discussing his experience, he repeatedly emphasized the fantastic communication and teamwork that he witnessed.  Weeks after discharge, he continues to get better and feels the benefits of the excellent care he received.

This is the story we all hope for.  And when I heard it, I have to say that I wasn’t surprised.  There’s something about the BIDMC that’s unusual.  Of the 4,500 hospitals that report their mortality rates to Medicare’s Hospital Compare website, only 22 (less than 0.5%) have better than predicted  mortality rates for all three reported conditions:  heart attack, congestive heart failure, and pneumonia.  And, we know that the combined performance on these three conditions is remarkably good at predicting hospital-wide outcomes, including outcomes for pulmonary embolism.

If you are a patient and care deeply about good outcomes, BIDMC seems to be a good place for you.

So what’s so special about them?  What do they do that’s different?  I don’t know, specifically, all of their tactics, but I have some guesses about what seems to differentiate high performing institutions from the rest.  And in a word, it’s leadership.  BIDMC has had two CEOs over the past few years, and both of them have been unusually committed to achieving high quality care.  That commitment translates into real activities that make a big difference.  Let me divert us with a story of what this might actually mean.

A few years ago, I was working on a strategy for improving the quality and safety of VA healthcare.  As part of this effort, I called up senior quality leaders of major healthcare organizations across the nation.  One call is particularly memorable.  Because I promised anonymity, I will not name names but this clinical leader was very clear about his responsibility: every month, he met with his CEO, who began the meetings with three simple questions: “How many patients did we hurt last month? How many patients did we fail to help? And did we do better than the month before?”

The CEO and the entire hospital took responsibility for every preventable injury and death that occurred and the culture of the place was focused on one thing: getting better.  When I looked them up on Hospital Compare, they too had excellent outcomes and they regularly get “A” ratings for patient safety from the Leapfrog Group.

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Letting the Data Speak: Estimating County Health Care Costs In Washington State

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By Frank de Libero

Besides state and higher-level health care expenditures, county level HCE are useful, integral really. For example, to promote the Triple Aim (the best care for the whole population at the lowest cost) you need per capita HCE. And knowing those costs at the county level would help a lot. However, county estimates generally don’t exist. They didn’t in Washington State until a client needed cost estimates for our 39 counties. To supply those estimates I used a regression approach resulting in this model:

percaphce = +0.1*percapinc + 247*pctage65 + 0.71*percapmedaid + 10.5*pctrural – 1349

Washington State Context
Before discussing model rationale and county HCE estimation, here’s some context about Washington State and its counties. You might view Washington as a microcosm of the nation. It has mountains, forests, deserts, rivers and lakes, vast rural areas, major cities, diverse populations and industries, and a varied climate. It is distinguished by active volcanoes and a coastal border. There is a wide range of political, social and economic clusters. In 2010 King County, where Seattle is located, median annual household income was about $67 thousand (the U.S. median was roughly $50 thousand) yet there are state counties where one in three children live in poverty. The total population is approximately 7 million with half of those people living in just three of the 39 counties.1 At the other end about a third of the counties have populations of 30 thousand or less.

An Aside about Seattle Weather
You may have been told that it rains all the time in Seattle. I live in Seattle and can tell you that’s a myth. Seattle’s average annual rainfall is less than New York City’s. However, during a good part of the non-summer months Seattle, and Puget Sound generally, is grey and cloudy. I once heard a story about the original settlers who landed in November, 1851, at Alki near present-day Seattle. The story is they were there for months before the weather finally cleared and they saw Mt. Rainier for the first time. I don’t know if that story is historically true, but as a Seattleite it’s believable. Regardless, Seattle is a summer paradise. Seattle summers, like most of Puget Sound, are characterized by pleasant sunny days, cool nights and no mosquitoes.

Background for the County HCE Estimates
Last year Empire Health Foundation of Spokane, Washington, asked me to estimate HCE for the 39 counties in the state. The purpose was for an upcoming meeting of policy types such as county commissioners, members of various health organizations, and other stake holders. A theme would be Donald Berwick’s Triple Aim, so cost estimates were wanted for benchmarks and context. The CMS2 Office of the Actuary had recently developed state HCE.3 If I could build a reasonable regression model on state-level data to predict state HCE, and there were similar variables at the county level, I could use the state model to estimate county HCE. That’s the approach I took. A caveat is my understanding was that acceptance—believability and reasonableness of the estimates to a lay audience—were as important as accuracy.

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Quality Measurement 2.0

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By John Halamka, MD

I’ve written several posts about the frustrating aspects of Meaningful Use Stage 2 Certification.   The Clinical Quality Measures (CQMs) are certainly one of problem spots, using standards that are not yet mature, and requiring computing of numerators and denominators that are not based on data collected as part of clinical care workflow.

There is a chasm between quality measurement expectations and EHR workflow realities causing pain to all the stakeholders – providers, government, and payers.   Quality measures are often based on data that can only be gathered via manual chart abstraction or prompting clinicians for esoteric data elements by interrupting documentation.

How do we fix CQMs?

1.  Realign quality measurement entity expectations by limiting calculations (call it the CQM developers palette) to data which are likely to exist in EHRs.   Recently, Yale created a consensus document, identifying data elements that are consistently populated and of sufficient reliability to serve in measure computations.   This is a good start.

2.  Add data elements to the EHRs over time and ensure that structured data input fields use value sets from the Value Set Authority Center (VSAC) at NLM.    The National Library of Medicine keeps a Meaningful Use data element catalog that is likely to expand in future stages of Meaningful Use.

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World of Health 2.0 – Interview with Matthew Holt, Co-Chairman

By Harriet Messenger

The following is an interview of Matthew Holt, Co-Chairman of Health 2.0.

Harriet Messenger – How did Health 2.0 begin?

Matthew Holt – My interest in health began in the early 90s when I found myself doing a study on healthcare in Japan. That then led to getting involved in Japanese versus American comparative health care; which, finally led to me getting a job in health care policy at a place called Institute for the Future. They had a huge technology forecasting component but no one was doing health information technology, so I put the two together.

Around that time the internet got going; there was a sort of E-health stock boom in the late Nineties, so I was involved in looking at that. Some years later I began a blog called The Health Care Blog and as part of that I was spending a lot of time looking at the re-emergence of ‘Web 2.0’, which was the re-emergence of information technology on the web, reaching out to the consumers, doctors, entrepreneurs, etc.

At the same time I met Indu Subaiya, who is my co-founder and my co-chairman. We realised that no one was paying attention to these guys, and that’s when we thought about creating a conference that brought all these great minds together. And that is how Health 2.0 started.

HM – And would you say that Health 2.0 is living up to your initial vision?

MH – Yes, but it takes forever to do anything in health care. Health care has the same problems it’s always had: getting data to the decision maker – whether that is patient or the doctor – and getting the right treatment plans in place for the patient. These are the same problems across the world. However, with the advent of new technology, mostly in the last 20 years, there have been big advances and changes in the way that health care is both consumed and delivered.

I’ve never thought Health 2.0 was going to change the world in three years. I believe that this type of technology is a big deal, but it is going to take time. We are now in the middle of that time – it’s starting now.

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