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Closing the Loop on The Need for Better Telemedicine

The Healthcare Blog - Wed, 11/25/2015 - 15:06

I’ve had the great privilege of presenting our virtual care company, CirrusMD, to potential customers and investors at some of the premier health technology conferences this fall, making the cut for both the Health 2.0 Traction event and this week in the finals of the mHealth Summit and HIMSS Venture+ event. (Breaking: we won the mHealth Summit and HIMSS Venture+ mature startup company award!)

Still, we often get an initial response, “Who needs another telemedicine company with the likes of Teladoc and American Well raising big rounds this year?” One writer even went so far as to share the thought in Forbes on the fragmentation of the digital health landscape after Health 2.0.

I want to take the opportunity to use an analogy to explain why were are different from other telemedicine offerings on the market, and why we are getting such great traction and recognition. In fact, we’re working to “unfragment” the healthcare landscape by closing up some very loose ends that occur in a typical telemedicine experience.

Today, finding our way to an unfamiliar address is easy with Google Maps or a GPS system. We just enter an address and go. The system knows where we are, where we are headed, can offer several options on how to get there, even make local recommendations along the way based on people who know the area. That’s where telemedicine needs to be, but not where it is with many of the major vendors.

Imagine if you didn’t know where you were, where you were going, and had no map. You’re lost and you find an old pay phone. You dial a number on a billboard that says “Directions and other Help”.

“Hi, I’m lost, and I have a flat tire and a bent rim,” you say.

“Where are you?” a voice asks.


“Where in Wyoming?”

“Um, on a side road, that’s about all I know.”

“Where are you headed?”

“Somewhere better than here.”

“Well if you can get to a major highway I might be able to help you. I have a map of the major highways.”

“But I only have a bicycle.”

“Well, I can tell you how to fix your tube, but for a rim and tire, you’ll need to go to find a store. Good luck!”

That’s where many telemedicine customers are today. They can get a hold of someone, but the person on the other end of the line has little information on who or where the patient is, little idea of where the patient is in their care plan, and limited ability to effectively direct them on where they need to go. The professional on the line will have little understanding of how well the patient is capable of getting where they need to go and might have a different set of maps from what the patient and their care team have used in the past. At best, they can offer imprecise advice. That advice can only get the person vaguely in the right direction and the person won’t be able to speak to the same person again. There’s little to no opportunity for follow-up and course correction.

Having cohesive medical direction is equivalent to making sure everyone is working from the same map. When you move from one disconnected physician, to another, you may get very different advice, particularly when there is no common management or reciprocity between these two unaffiliated providers. Standards of care may, and often do, vary from practice to practice. That can cause conflicts and misdirection.

A longitudinal history ensures everyone agrees on where the patient is on “the map”. It assures that the best decisions are made under the context of care continuity. To maintain coordination, virtual care providers must have access to the patient’s primary medical record, and bricks and mortar/physical providers must have access to and notification of any virtual encounters that occur.  Additionally, the virtual and physical providers must be able to communicate and coordinate with one another around a patient’s care plan. A patient can wind up going around in circles.  Without the complete view of the patient, different decisions can be made in their care, and those decisions can lead to less than optimal outcomes. We see this happening with many of the virtual care services on the market today, especially for patients that have more complicated medical histories (remember 50% of adult Americans are living with a chronic condition).

We recently had an encounter with a patient suffering from a chronic condition who was traveling in Europe and lost their medications. They had a secure text conversation over the CirrusMD platform, and the physician was able to review their medical record and notes from the patient’s regular specialist and access their medications list.  The doctor knew that replacement medications were available over the counter in Europe and instructed the patient on what to get. The doctor then helped the patient manage their condition over several days to ensure that they were comfortable with the new medications and that the flare-up was being controlled.

That’s the power of telemedicine that knows the patient, their history and their care plan.

On another occasion, an individual with a debilitating chronic disease asked us, “If the person on the other side of the connection does not know my pathology, my meds, my symptoms with my disease, should they really be giving me medical advice?” The short answer, we believe, is “no”. We ensure our patients and physicians have access to the information needed, and the patient’s record is kept up to date through data integrations to HIEs and EMRs.

Documenting where the patient is with follow-up as they move through their care plan is also critical. Telemedicine solutions must ensure a patient receives the proper follow-up care, whether that care is in a physical clinic or via telemedicine. Virtual follow-ups are not currently enabled with the majority of telemedicine services on the market right now, and they cannot provide physical, in-person follow-ups as the doctors are generally not connected to the patient’s local healthcare establishment.  Without the ability to enable follow-up, a telemedicine visit becomes an island, a one-off event known only to the patient, and they can quickly become lost again.  This leads to fragmentation in patient care.

Finally, to guide a patient effectively as they go forward, providing the right referrals for follow-up care is also critical. To provide proper direction, you have to know the local area and where to go for the right service. Our doctors are local to the patient and have that ability.

It will be very difficult for the majority of telemedicine services today to provide common medical direction, longitudinal data access, follow-ups and referrals. With most vendors you’ll likely get a new doctor every time you call, and even if they are licensed in your state (which doesn’t mean they are in your state), they may know next to nothing about the patient, they are operating under very loose clinical guidelines with high variability in quality of care from doctor to doctor, and in some cases the telemedicine physician’s recommendations may fly in opposition to a patient’s current care providers.

We can and are doing better with our clients. We are bringing telemedicine solutions that are more consistent and work in context of a patient’s local healthcare landscape and offer full data continuity between virtual care providers and their regular doctors.

Our closed-loop telemedicine methodology solves these issues with the ability to bring physical and virtual continuous care together, including: a complete and consistent map (a more complete view of the patient with a care plan developed under consistent standards of practice), a continuous pathway of access (opportunity for follow-up and ongoing management), and local knowledge of the area to make specific recommendations on how to get what’s needed to get on track (ability to do local referrals).  With closed-loop telemedicine, we’ll know where patients are, where they are headed with more precise direction all along the way.

Andrew Alterdorfer is the CEO of CirrusMD

Categories: OIG Advisory Opinions

How to Safeguard your Career in Treacherous Healthcare Times

The Healthcare Blog - Wed, 11/25/2015 - 14:07

Dear medical student,

I am honored by the opportunity to offer some advice on how to safeguard your professional career in a treacherous healthcare system.

I will not elaborate on why I think the healthcare system is “treacherous.”  I will assume—and even hope—that you have at least some inkling that things are not so rosy in the world of medicine.

I am also not going to give any actual advice.  I’m a fan of Socrates, so I believe that it is more constructive to challenge you with pointed questions.  The real advice will come to you naturally as you proceed to answer these questions for yourself.  I will, however, direct you to some resources to aid you in your reflections.

I have grouped the questions into three categories of knowledge which I am sure are not covered or barely covered in your curriculum: economics, ethics, and philosophy of medicine.

I have found that reflecting on these questions has been essential to give me a sense of control over my career.  I hope that you, in turn, will find them intriguing and worth investigating.

One more thing before we proceed.  Don’t be overwhelmed by the depth of the questions posed and don’t attempt to answer them today, in a week, or in a year.  In many ways, these are questions for a lifetime of professional growth.  On the other hand, I believe that the mere task of entertaining these questions in your mind will be helpful to you.

So here we go:

Your understanding of economics

Sample questions:

  • Is there a shortage of doctors? Is there a glut?  How would you know?  How can you anticipate the demand for services in your specialty of interest?
  • As a physician, how should your economic value (i.e., your earnings) be determined?
  • Who will ultimately be the hand that feeds you?
  • Will you and the hand that feeds you see things similarly in regards to how your work should be valued?
  • How does a society become prosperous and how does it become poor?
  • What is a fair way to distribute resources in society?
  • Does the national debt matter? How could it affect your career?

If you don’t have some clarity about the answers to these questions, you may be proceeding in your professional life with some naïve optimism and inadequately prepared to safeguard yourself financially.

Granted, knowledge of economics does not always mean you will be immune from the effect of economic realities that are beyond your control.  But economic knowledge will afford you to take these realities into account as you make informed decisions about your career path, and allow you to weather any potential storm better than if you were caught by complete surprise.

Granted, economists themselves often disagree with each other, and economics may be the only discipline where the Nobel committee can grant a prize to two economists with completely opposing views.

Nevertheless, there is great benefit to having some grasp of economic principles.  And if these seem flimsy on the surface, it’s usually because politicians and economists let their political views confuse their economic discourse, and not because basic, well-reasoned economic principles are themselves faulty.

If you want to get started, I can recommend to two excellent and easy-to-read introductory texts: How an Economy Grows and How it Crashes by Peter and Andrew Schiff and Economics in One Lesson, a classic collection of essays superbly written by Henry Hazlitt.

Your understanding of ethics

Sample questions:

  • Do the ends ever justify the means? If so, when and why?  If not, why not?
  • Are there ethical principles that should always be respected? If so, which ones and why?
  • Should medicine aim to provide the most good for the greatest number? Why or why not?
  • Should doctors serve both the individual and society? Can they?
  • How important is it to have good moral character? Why? (And what does that mean?)
  • What is the goal of medicine?

Make no mistake about it, medicine is first of all an ethical endeavor.  Medicine is not about applying medical science or medical techniques, but about doing the right thing for the patient.

Science will inform you about the best means to achieve certain goals, and good techniques will help you achieve them.  But neither science no technology can tell you what those goals should be.

We live in a pluralistic society where basic ethical principles are frequently a matter of dispute.  This lack of ethical consensus and the potential for conflicts to arise understandably contribute to keeping ethics education to a minimum.

You, however, will benefit from having as clear an understanding of your own ethical principles as possible.  Otherwise, sooner or later you will realize that being ambivalent about the right course of action could cost you.

Whether it’s a matter of properly allocating financial resources in the care of patients, or issues of life, death, and justice, you don’t want to be in a position where hesitancy interferes with your ability to take a stand or make firm decisions, especially once you have committed to a job or a position where you are expected to make decisions.  (Remember, that’s what “M.D.” stands for).

Ethical principles are not necessarily obvious nor intuitive, otherwise, there would be no ethical conflicts in society.  The more you can articulate and defend the principles that you stand for, the better prepared you will be in a system where ethical conflicts are likely to be increasingly common.

You may wish to familiarize yourself with Principles of Biomedical Ethics by Beauchamp and Childress.  I do not necessarily endorse its content, but this is a commonly cited and influential text which reflects mainstream ideas about medical ethics.  This should only be a start.

Philosophy of Medicine

Sample questions:

  • Is obesity a disease? Why or why not?
  • Is hypercholesterolemia a disease?
  • If a disease is defined by a cut-off number (say, BMI>30) is it a “real” entity? Is it a “social construct?”
  • What is a disease?
  • Do you agree with the W.H.O. definition of health? Why or why not?
  • What does “normal” mean in a medical context?
  • Should the medical community define what is healthy and what is not? If so, using what criteria?
  • What can science tell us about health and disease?
  • What are the main current problems in the philosophy of biology?
  • What is a human being?

I hope you have found these philosophical questions somewhat relevant to the practice of medicine.  I believe that they are.

Unfortunately, not many people agree with me.  Instead, the common attitude is to think that these questions are difficult to answer and that medicine has made great strides without having to resolve them.  Why make a philosophical fuss?

I think a philosophical fuss is definitely in order when the healthcare system is teetering on the brink.  Deep seated problems often mean that we’ve been operating on assumptions that need revisiting.

As mere doctors, we may not always solve philosophical problems, but we should be able to recognize the assumptions on which medical doctrine and healthcare policy rest.  Sometimes, those who promote a certain viewpoint will prefer that its assumptions remain unexamined.  I think we can all benefit from having philosophical antennas.

Because the field of “philosophy of medicine” is virtually non-existent as an academic discipline, there is no standard textbook I can point you too.  However, there are two compendia of essays that were edited in the last decades and that address some of the questions I have raised here.  These are Concepts of Health and Disease: Interdisciplinary Perspectives, edited by Caplan, Engelhardt, and McCartney in 1981, andHealth, Disease, and Illness: Concepts in Medicine, edited by Caplan, McCartney, and Sisti in 2004.  Either one would be a good place to start.

Are you still with me?

If you are, you have realized that what I am giving you is a massive reading assignment.  I’ll admit it.  If I could summarize my recommendation in one word it would be this: Read!

Read more.  If you haven’t done so already, you need to develop the habit of reading all the time and of reading long form: books and long essays.  Read outside of your comfort zone.  Reading is the only activity that will quickly give you real knowledge that you need not only to survive, but to really thrive in these tumultuous times.

And don’t get discouraged by the sheer volume of the knowledge to be gained.  As I said earlier, the point here is to stimulate your curiosity about the proper questions, at a time when medical school demands are likely to quash you sense of wonderment.

Rome was not built in a day, and all you have to do is to keep on hand some material to gently chew on at your own pace, not to embark on an ill-advised intellectual binge for wisdom.  Once you get into that habit, you will find out that knowledge is not only empowering, but it is liberating.

And you’re not training to become a doctor to be at the mercy of an unhealthy system, are you?

Michel Accad is a cardiologist based in San Francisco. 

Categories: OIG Advisory Opinions

Obamacare is failing? Not so fast.

The Healthcare Blog - Mon, 11/23/2015 - 19:21

“See? Obamacare is failing!” according to industry expert C. Little, citing Wolf Report 712A just filed by Boy W. Cried.

What is the hue and cry about this time? United Healthcare is saying it has lost large bales and wads of money on Obamacare exchange plans, and just may give up on them entirely. Anthem and Aetna allow that they are not making very much either. Some new not-for-profit market entrants have gone belly up, and the others are having a hard time.

Before we perform the Last Rites over Obamacare, perhsp we should think for a moment about the hit ratio of the first 711 Wolf Reports from Boy W. Cried and ask a few questions.

First: Do we trust implicitly the numbers that the health plans are giving out in press releases, citing unacceptably high medical loss ratios? Medical loss ratios (MLRs) are self-reported. Yes, there is a certain amount of accountability. The numbers have to square with expenses given on their corporate tax forms and so on, but there is wiggle room in just what is reported and how. If is a reasonable supposition that if you wanted to look for the professionals with the greatest skill in juggling numbers, you would find them working for insurance companies, especially health plans, because the stakes are so high. These numbers people at the top of their game have huge incentives to report a high MLR, so if there is wiggle room, I am sure they will find it.

Beyond that, MLR is reported by state, by market segment (large group, small group, individual), against what portion of a premium is “earned” within that reporting period, and by calendar year rather than any company’s financial year. To say, “Our MLR is X” is to claim that X the correct aggregate number across their entire multi-state system, from all their subsidiaries, appropriately weighted for the size of each region. We don’t have access to those numbers, just to what they are telling us. There are plenty of reasons for them to want to report the highest MLR they can get away with, plenty of reasons to be skeptical of the numbers they are giving out, and plenty of reasons not to base drastic policy changes on such pronouncements.

But let’s get down to business here. So they lost money (or barely made it) in 2014 and 2015, and they are projecting the same in 2016? Doesn’t this mean that they misjudged the cost of healthcare, so they need to raise premiums? And they didn’t realize this soon enough to do raise them appropriately for the 2016 year?

Sounds like somebody (or a pile of somebodies) made faulty business judgments. This is not too surprising, given that these are new business models in new markets. Pricing, risk analysis, and utilization projections are hard enough in established markets, doubly difficult in emerging ones, and exponentially more difficult for a new company scrambling to grab any market share at all, like the failed cooperatives.

Well, waah. Welcome to competition, market capitalism, all that stuff. None of this is in the least surprising.

But does it mean that “Obamacare has failed”? Does it even mean that these companies have failed in Obamacare markets? No, it means what it is: These companies have failed to make the profits that they hoped for in the opening three years of Obamacare. And they are telling us all about their pain so that the government (through regulation) or the body politic (by repealing Obamacare) will make it easier for them to churn a profit.

So what’s the real problem here? In any kind of economy, you need to price your products so that (in aggregate, over time) your total cost of ownership is less than what you sell your products for. There’s your margin, the oxygen of your business. These folks are claiming that the aggregate total cost of ownership of what they are selling (access to healthcare) is close to what they are selling it for. Hmmm. That’s a problem. It has two paths out: Lower the total cost of ownership (get the actual costs of healthcare down) or raise the premium.

How about getting aggressive about the real cost of healthcare? Two problems with that part of the equation: 1) It’s really hard and takes years. 2) It does not benefit just them. It will benefit the whole market. So it’s not a path to greater profitability.

A health plan’s profit (margin) is some percentage of the total cost of care for the people they cover. So they have an incentive on the one hand to cover a lot of people (that is, increase their market share). They have an incentive to keep their premiums competitive not in absolute terms but relative to other payers in each regional market. On the other hand, they have no incentive to get aggressive about actually lowering the underlying real costs of healthcare for the whole market. That would not give them a competitive advantage.

What’s the business concern with raising their premiums appropriately? The concern is that these lower-cost narrow network exchange plans are price inelastic. If they raise their premiums, they will lose market share. But wait, if the cause really is the underlying high costs of healthcare, won’t everyone’s premiums have to go up the same amount? This complaint sounds more like an assumption that others can provision the market more efficiently, keep their premiums more competitive, and gobble up market share.

Again, is this a failure of the Obamacare model? Or is it actually proof of concept? To say that the Obamacare exchanges are failing because some companies might give up on them is to imagine that the purpose of Obamacare, the metric on which it should be measured, is to make health plans comfortable and profitable. Wrong.

The core idea of the Obamacare exchanges has been that health plans should compete on a level playing field to see who could offer the best service and the best access to healthcare at the lowest price. That’s what markets are for. The assumption built into this logic is that some organizations will do it better than others, some will not be good at it, and the market will shake out. If nobody ever failed in the Obamacare exchanges, then we would have to say that they failed to establish anything resembling a true market.

Joe Flower is a healthcare futurist and author. He is a contributing editor with THCB.

Categories: OIG Advisory Opinions

A Radical Policy Proposal: Go Easy On Older Docs

The Healthcare Blog - Mon, 11/23/2015 - 15:43

Through Dec. 15, federal regulators will accept public comments on the next set of rules that will shape the future of medicine in the transition to a super information highway for
Electronic Health Records (EHRs).  For health providers, this is a time to speak out.

One idea:  Why not suggest options to give leniency to older doctors struggling with the shift to technology late in their careers?

By the government’s own estimate,in a report on A 10-Year Vision to Achieve an Interoperable Health IT Infrastructure, a fully functioning EHR system, for the cross-sharing of health records among providers, will take until 2024 to materialize.The technology is simply a long way off.

Meanwhile, doctors are reporting data while the infrastructure for sharing it doesn’t exist.  Now, for the first time, physicians will be reporting to the federal government on progress toward uniform objectives for the meaningful use of electronic health records.  Those who meet requirements will be eligible for incentive payments from Medicare and Medicaid, while those who don’t may face penalties. In addition, audits are expected to begin in 2016.

Amid this shift to a new, data-driven healthcare system, the nation needs older doctors to keep practicing to meet presentneeds of an aging population, as well as an expanded Medicaid system. If burdensome reporting rules encourage retirements, as some studies indicate, the building of an information highway may result in the unintended consequence of a bottlenecked road to seeing a physician.  The likely result:  Nurse practitioners will deliver a greater share of the nation’s healthcare.

Some critics say the medical profession exaggerates a coming shortage of physicians.

Yet concierge medical practices are growing in number, luring those willing to pay a premium to see a doctor quickly for extended-time visits.

Last year, the New York Times reported on long wait times for doctor appointments as a new norm, and not just in traditionally under-served rural areas.  The article pointed to one study that found patients waiting an average of 66 days for a physical examination in Boston, and 32 days for a cardiologist appointment in Washington.

Think of what the wait times would be if mass retirements materialized, as suggested by findings of a 2014 survey of 20,000 physicians by The Physicians Foundation. Thirty-nine percent indicated plans to accelerate retirement due to changes in the healthcare system.Others reported plans to cut back on patient caseload or seek different jobs.

The potential for disruption is even more startling when you consider the number of older doctors in practice.  According to R. Jan Gurley, a physician writing on the  blog of the University of Southern California’s Center for Health Journalism, one in three doctors is over 50, and one in four is over 60 – despite roughly 20,000 newly medical school graduates a year.

Because of what’s at stake — potentially the very underpinnings of our nation’s healthcare system — health providers should speak out forcefully during the government’s open comment period.  Yes, it is late in the rulemaking game for EHRs.But new rules are being written for 2018 and beyond, and modifications are being made to rules in effect through 2017.

Would an outpouring of thoughtful, well-documented recommendations make a difference?  In a democracy, the answer should be yes.  The value of keeping older doctors in practice far outweighs the benefit of driving them crazy as they try to meet reporting requirements with often-clumsy EHR technology.  The challenge is to find a middle ground.

Diane Evans is a former Akron Beacon Journal editorial writer and columnist, and now publisher of the recently introduced MyHIPAA Guide, a news and information service for HIPAA-covered organizations trying to stay up with the seismic shift to a data-driven electronic health system. is hosting a forums discussion that is open to all who would like to share insights on key points that should be conveyed to CMS and government regulators. 

Categories: OIG Advisory Opinions

25 Reasons It is Time to Kill Meaningful Use

The Healthcare Blog - Sun, 11/22/2015 - 18:46

Over the last half decade, the Federal Government has successfully convinced a majority of physicians and hospitals to begin using electronic health records by providing $30+ billion dollars in subsidies to those who use an ONC Certified electronic health record (EHR) according to the “Meaningful Use” guidelines.

Although the physician community usually consists of a multiplicity of dogmatic opinions, on the subject of Meaningful Use (MU), there is now near unanimous agreement that the MU train has not succeeded in achieving its intended purpose, which was to improve quality or reduce the cost of healthcare. Earlier this month, 111 medical organizations, led by the AMA, sent a letter to Congress asking that MU Stage 3 be delayed and MU Stage 2 be redesigned.

Dissatisfaction with MU even extends to the Chief HIT Geek, John Halamka, M.D., who has concluded MU “Stage 2 and Stage 3 will not improve (health) outcomes” and has called to “Replace the meaningful use program with alternative payment models and merit-based incentive payments.”

In an attempt to objectively assess the MU program, I put together a list of reasons to help me determine whether the MU program should be continued or terminated:

Reasons to Continue the Meaningful Use Program (Pro MU)

  1. Some late adopting physicians and hospitals will continue to receive significant financial payments from the Federal Government if they participate in MU programs.
  1. Computerized Physician Order Entry (CPOE) and electronic prescribing have been demonstrated to reduce medical errors.

Reasons to Terminate the Meaningful Use Program (Con MU)

  1. The majority of physicians already use EHR and there is no reason to continue to incentivize them.
  1. There is a ground swell of discontent among physicians arising from the poor design of many Certified EHRs and the current MU program further enshrines the use of these EHRs.
  1. Many physicians believe that MU program interferes with the physician-patient relationship by forcing physicians to spend time acknowledging clinically meaningless Certified EHR prompts.
  1. Hospital resources devoted to meeting MU requirements have hindered some hospital’s ability to update their IT infrastructure by drawing resources away from important IT problems.
  1. MU mandates have onerously consumed EHR vendor and healthcare provider resources while decreasing resources which can be devoted to creating innovative healthcare solutions.
  1. Physicians do not believe (nor is there data to demonstrate) that forcing patients to visit the physician’s MU mandated patient portal promotes the health of their patients.
  1. Physician practices are overburdened with bureaucratic mandates (Rx appeals, insurance requests for records) and MU tasks consume staff and physician time, thus diverting them from patient care.
  1. There are substantial financial penalties and psychological costs which physicians will incur if they are audited as a result of their participation in the MU program and these financial penalties are disproportionate to the financial incentives arising from the MU program.
  1. Only 12% of physicians have completed MU stage 2 and fewer will likely participate in MU3.
  1. The collective burden of all the workflow changes required by three stages of Meaningful Use regulations will make it hard for clinicians to spend adequate time on direct patient care (John Halamka, M.D.,
  1. The public health reporting requirements required by MU will be hard to achieve in many locations due to the heterogeneity of local public health capabilities (John Halamka, M.D.)
  1. There is no data which proves that achieving MU Stage 1 or Stage 2 improves the quality or reduces the cost of healthcare
  1. A majority (68%) of physicians report MU measures do not help them improve patient care or safety. (Survey of Texas Physicians Meaningful Use. Texas Medical Association)
  1. A decision to work towards a “delay” in MU Stage 3 program will enshrine the currently intrusive and wasteful MU1 and MU2 work protocols as part of the standard office visit.
  1. While there is great promise which may derive from true HIT interoperability, there are many ways to achieve HIT interoperability independently of the MU
  1. It is illogical to hold physicians responsible for implementing HIT mandates which are clearly beyond their ability to create, pay for and/or implement
  1. Meaningful use has ” created … a monster, when really what we were shooting for was good patient care.”  (Factors Affecting Physician Professional Satisfaction and Their Implications for Patient Care, Health Systems and Health Policy. The RAND Corporation, American Medical Association 2013)
  1. Reducing the cumulative burden of rules and regulations may enhance physicians’ ability to focus on patient care. (Factors Affecting Physician Professional Satisfaction and Their Implications for Patient Care, Health Systems and Health Policy)
  1. The current approach to automated quality reporting does not yet deliver on the promise of feasibility, validity and reliability of measures or the reduction in reporting burden placed on hospitals. (A Study Of The Impact Of Meaningful Use Clinical Quality Measures. Floyd Eisenberg,Caterina Lasome, Aneel Advani, Rute Martins, Patricia A. Craig, Sharon Sprenger. 2013)
  1. The workflow changes to meet the MU eCQM reporting tool requirements have added to physician and nursing workload, providing no perceived benefit to patient care. (A Study Of The Impact Of Meaningful Use Clinical Quality Measures. Eisenberg et al)
  1. EHRs are not designed to capture and enable re-use of information captured during the course of care for later eCQM reporting. (A Study Of The Impact Of Meaningful Use Clinical Quality Measures. Eisenberg et al)
  1. Champions of EHR adoption within hospitals …. have been significantly challenged by Meaningful Use Program eCQMs that are complex, inaccurate, outdated and that require incredible detail to be documented (often in duplicative ways) in a structured form in the EHR with no perceived additional value to patient care.  (A Study Of The Impact Of Meaningful Use Clinical Quality Measures. Eisenberg et al)
  1. Fifty two percent of Texas physicians report all or most of the (MU) measures are not meaningful to care. (Survey of Texas Physicians Meaningful Use. Texas Medical Association)
  1. There is essentially no data which demonstrate that the vast majority of meaningful use measures (excluding clinical decision support and computerized provider order entry) improve the quality of patient care.  (Ann Intern Med. 2014;160:48-54)
  1. The existing MU program has had a deleterious effect on physician morale. (Robert Wachter, The Digital Doctor: Hope, Hype Harm at the Dawn of Medicine’s Computer Age)

I fully acknowledge that the above lists are imperfect and that some will quibble over specific items on the lists. I want to encourage readers to add items to the “Pro” and “Con” lists in the comments section of this article, but please do so respectfully and in a measured manner. Inflammatory rhetoric will only denigrate the effectiveness of this conversation and serve no useful purpose.


Despite the imperfect nature of the above lists, I think we can objectively conclude that it is time for the Federal Government to immediately terminate the MU program.


I believe that the AMA’s strategy to delay/revise the MU program is the wrong goal. If they succeed in delaying the implementation of MU3, they will have enshrined MU1 and MU2 protocols into the practice of medicine and this will permanently interfere with our ability to provide care to our patients while making it very difficult to implement innovative healthcare solutions which have the potential to solve our healthcare cost/quality problem.


Until there is objective evidence that the MU program has a salutary effect on our health care system, not only should the MU program be terminated, but the Federal Government and private insurers should also be prohibited from creating financial incentives and disincentives arising from the MU program.



Hayward Zwerling, M.D., FACP, FACE

President, ComChart Medical Software (no longer for sale)

The Lowell Diabetes & Endocrine Center



Categories: OIG Advisory Opinions

A Blue Jumps the Wellness Shark

The Healthcare Blog - Sat, 11/21/2015 - 13:34

I know it’s not always about me (my ex-wife was quite clear on that point), but I was deeply saddened to see one of the Blues – specifically, Blue Cross of Tennessee — descending into the fabricated-wellness-outcomes abyss.

By way of background, regular readers of this irregular column and/or have seen multitudinous examples of vendors telling lies that any fifth-grader could see through. Perhaps the best two examples on this site are Staywell and Mercer reporting mathematically impossible savings for British Petroleum and Health Fitness Corporation admitting they lied about saving the lives of cancer victims in Nebraska.

In both cases, the de facto leader of the wellness industry, Dr. Ron Goetzel of Truven Health Care, was so appalled by this dishonesty that he assembled a group of other self-described industry leaders to give them awards. Not just any awards, but awards named after the most respected Surgeon General in history, Dr. C. Everett Koop. (No doubt the irony was lost on Dr. Goetzel.)

In all fairness, wellness vendors have to lie, since it turns out that achieving savings is mathematically impossible. If they told the truth, they’d all be fired. Even so, Blues should be held to a higher standard for integrity than independent wellness vendors, because lies told by one Blue affect all the others by sullying one of the most readily identified and respected trademarks in America.

Before continuing, I do want to emphasize that this isn’t about “the Blues,” which are all independent of one another. It’s specifically about Blue Cross of Tennessee (BCBSTN). By contrast, other Blues – Massachusetts, Rhode Island, Louisiana, Carefirst and South Carolina come to mind (along with the Blue Care Network subsidiary of Blue Cross of Michigan) – have created exemplary outcomes reports. For them, integrity trumps impossibility. Two have even been validated by the Intel-GE Care Innovations Validation Institute, the gold standard in outcomes measurement.

Not so BCBSTN. They published a report in which Onlife Health showed some of the best outcomes in wellness history. BCBSTN calls Onlife their “partner” company in this report. However, a corporate lawyer – or BCBSTN itself, in this other press release – would call Onlife a “subsidiary,” for the simple reason that BCBTN owns them. By contrast, you don’t own your “partner.”

In other words, BCBSTN is validating itself, not a “partner.”

The “intervention” was that these admittedly overweight employees walked an extra 2500 steps (about 19 minutes) a day. Here’s what those literal and figurative “baby steps” (as the report calls them) achieved. This is cut-and-pasted from the report:

  • Emergency room visits and inpatient hospital stays were more than 50 percent lower in the moderate exercise group, as well. There were 219.6 ER visits and 59.9 inpatient stays per 1,000 for overweight non-exercisers compared to 73.6 ER visits and 30.1 inpatient stays per 1,000 for overweight moderate exercisers.

Let’s consider ER and Inpatient separately. About 40-million ER visits a year are specifically caused by injuries, or roughly 126 per 1000 people. This injuries-only figure dwarfs BCBSTN’s all-in ER visit figure of 73.6 per 1000 allegedly achieved by this program. In other words, walking an extra 19 minutes a day not only wiped out every single non-injury-related ER visits, but also about 40% of all injury-related ER visits.

Next, let’s consider the inpatient stays. Their 30 stays per 1000 includes birth events, as compared to the more typical figure, which BCBSTN also experienced in the control group, of about 60 per 1000. All birth events combined are about 15 to 20 per 1000. Taking those birth events out of the BCBSTN tally yields 10-15 admissions per 1000, a Nobel Prizewinning figure. And all achieved by walking an extra 19 minutes a day.

Another way of looking at it: here are the top 21 admissions categories for Tennesseans insured through their employer. With the exceptions of #9 and #10 (morbid obesity and heart attacks), probably not one single admission in any of these categories could have been prevented by walking an extra 19 minutes a day. Even in those two categories, optimistically only a handful of admissions would be prevented by short walks.


In addition – this is also part of wellness vendor DNA as this Wellsteps example shows – BCBSTN’s numbers contradict themselves. Compare these three bullet points from the study (italics are ours):

  • Contrary to the popular guideline of 10,000 steps a day, employees who took as few as 5,000 steps per day, had annual healthcare costs nearly 20 percent lower than their sedentary counterparts who did not exercise. Spending was $2,038 per member per year (PMPY) for non-exercisers compared to $1,646 PMPY for moderate exercisers.
  • Average claims cost PMPY dropped from $5,712 for non-users to $4,248 for employees who participated in one program and $3,120 for those participating in two programs. Employees engaged in three programs saw their claims cost cut almost in half at $2,892.
  • Looking at BCBST overall, Danny Timblin, president and CEO of Onlife Health, noted, “Over a three-year period of time when we did this study, their claims were essentially flat.

Well, which is it? Is it $2,038 per year for non-exercisers, or $5,712? How is it that “moderate exercisers” only spend $1,646 in the first bullet point but $2,892 in the second? And how can any sizable group of people only spend $1646 per year per person, vs. the more typical $5000-$6000? (Even adding up the cost of just those impossibly low ER and Inpatient utilization figures would total more than $1646.)

And how does “their claims were essentially flat” in the third bullet point reconcile with the massive declines in the second bullet point?

Yet another head-scratcher: these massive savings were achieved despite the wellness industry’s own report admitting wellness loses money. You might say: “So what? Maybe Onlife disagrees with that industry report.” Except that Onlife cowrote that report, unless there is a different Onlife Health that is listed as a collaborator on it:

This Onlife “study,” if nothing else, validates the observation in our book Surviving Workplace Wellness: “In wellness, you don’t have to challenge the numbers to invalidate them. You merely have to read the numbers. They will invalidate themselves.”

Which brings us back to what Blue Cross of Tennessee needs to do next. It seems they have, in the immortal words of the great philosopher Ricky Ricardo, some ‘splainin’ to do. At the very least, perhaps an apology to the Blue Cross Association and to their fellow Blues.

Al Lewis is the founder of and the author of Surviving Workplace Wellness.

Categories: OIG Advisory Opinions

The Limitations of Healthcare Science

The Healthcare Blog - Sat, 11/21/2015 - 11:50

Every once in awhile on the wards, one of the attending physicians will approach me and ask me to perform a literature review on a particular clinical question. It might be a question like “What does the evidence say about how long should Bactrim should be given for a UTI?” or “Which is more effective in the management of atrial fibrillation, rate control or rhythm control?” A chill usually runs down my spine, like that feeling one gets when a cop siren wails from behind while one is driving. But thankfully, summarizing what we know about a subject is actually a pretty formulaic exercise, involving a PubMed search followed by an evaluation of the various studies with consideration for generalizability, bias, and confounding.

A more interesting question, in my opinion, is to ask why we do not know what we do not know. To delve into is a question requires some understanding of how research is conducted, and it has implications for how clinicians make decisions with their patients. Below, I hope to provide some insights into the ways in which clinical research is limited. In doing so, I hope to illustrate why some topics we know less about, and why some questions are perhaps even unknowable.

Negative studies are difficult to publish

A positive study is one that demonstrates a statistically significant result. Anegative study is one that shows no statistically significant difference. Any researcher would agree that it is easier to publish a positive study — after all, it is more exciting to read a study that suggests that some new kind of treatment works, as opposed to a study that shows that a treatment did not do anything. I would also contribute an additional point, which is that it is analytically easier to construct a compelling positive study (“even limitations in our data, we were able to show a statistically significant improvement in mortality in the group that received this surgical technique”) vs. a compelling negative study (“there was no statistically significant difference between the two groups, and we are confident that we are interpreting our data well enough and have a large enough sample size to be able to detect a meaningful difference if there were one”).

So when one delves into a particular research question, one must interpret the literature in the context of possible negative studies that may have been performed and not published. Admittedly, this is a bit like asking this Californian to ponder earthquakes — the ground may be shifting beneath my feet, but it gives me less anxiety to ignore the possibility.

Publication a slow, deliberate process

Briefly, here are the steps:

  • Submit manuscript to journal
  • Hope it does not get rejected immediately. If it does submit to another journal.
  • Wait for peer reviews, hope manuscript does not get rejected based on those peer reviews.
  • Make revisions based on concerns of reviewers
  • Journal officially accept manuscript for publication and eventually publishes it

Each one of these steps can take months. For example, a study that I worked on, ironically titled “Timeliness of Care in US Emergency Departments: An Analysis of Newly Released Metrics From the Centers for Medicare & Medicaid Services.” This data was analyzed and the first draft of the manuscript was written over the course of a week in August 2013. The final manuscript (which was fairly similar to the first draft in my opinion) was published in November 2014.

There are, of course, many ways that researchers get their research out there, such as posters and presentations at conferences, research meetings, blogs, Twitter. But the fact of the matter is that a lot of science is known by someone, long before it gets in the public domain.

Certain populations are systematically underrepresented in medical research

Every study involves an investigation into a particular population sample, which researchers work very delicately to select. Given that researchers use samples, the interpretation of how a study informs the care of any individual patient must consider the generalizability of that study. But if we look across multiple studies, or across even entire fields of research, and examine which samples are being studied, it is apparent that there are large groups of people who are underrepresented in clinical research. For example, much has been written about how clinical research studies enroll disproportionately few minorities. Our science is largely based on a Caucasian population! Much research into hospital quality measures, as another example, is based on fee-for-service inpatient Medicare claims which excludes all the outpatient services that hospitals provide, Medicare Advantage patients, people younger than 65. The quality of care that 27-year-olds like me receive is relatively poorly studied.

Researchers generally choose the samples they study out of convenience, the discussion section of a paper typically pays at least some lip service to the limitations on generalizing the results of that study to other populations. But because of the systematic underrepresentation of certain populations in research, clinicians are left to make assumptions, i.e. a medication will be equally effective in poorly-studied population X as in well-studied population Y. These kinds of assumptions about generalizability are strong ones, ones that basic scientists and social scientists would be more hesitant about.

Clinical research favors a handful of simple methods

Student’s t-test, chi-square test for independence, ordinary least squares regression, logistic regression, and Cox proportional hazards regression account for the vast majority of analytic methods in clinical research. And indeed, those were pretty much all of the analytical methods that I was taught in my evidence-based medicine course in medical school. While these methods are probably sufficient for understanding and performing randomized control trials, there are so many other valuable methods in observational data research that one rarely sees. Without advocating for the adoption the “mathiness” of economics, clinical research could stand to learn about methods seen in other fields. Instrumental variable methods, for example, are part of the fundamentals of econometrics and could deepen our understanding of observational data in medicine.

It is all about the average, when it comes to medical research

A distribution of data might look like this:

Medical research largely concerns itself with where the little triangle below points:

That is the average, a single number that the fundamentally underlies the various statistical methods that are common in medical research, but by itself cannot truly describes an entire distribution. Papers will generally also present standard deviations, which is helpful, but truly only sufficient if one assumes a normal distribution. One rarely sees medians or percentiles in medical research, let alone more obscure concepts like skewness or kurtosis. In a sense, our science is based on how averages relate to averages, and ignores much of the complexity of the entire distributions of what we measure.

This has profound clinical implications. Countless times, my patients ask, “Will this treatment work?” And I might be left to say something like, “85% of people see some response” ← a statement about averages, “but everyone is different, some people respond better, some people respond worse, some people not at all” ← a hand-wavy statement about the rest of the distribution.

Clinical research lives in two dimensions

Treatment and outcome. Independent variable and dependent variable. X and Y. Left-sided and right-sided. Does this surgical technique lower recurrence? Does this drug decrease cardiovascular risk? The majority of clinical research is focused on linking one thing with another thing, in pursuit of establishing a causal relationship. Researchers spend less time thinking about how a third thing (or even a fourth thing) might modulate the relationship between the first two things. To what extent does age influence the effectiveness of this drug in lowering risk of cardiovascular events?

Researchers do investigate those “three-dimensional” questions by using methods like stratification or effect modification, but over all it represents a minority of all research effort (perhaps tucked away in a Table 4 or 5 of a paper). Maybe the “big data” or “precision medicine” movements are the solution.

The easily measurable is favored over the hard-to-measure, let alone the immeasurable

If one is going to perform research, it is of course natural to prioritize the low hanging fruit. This means investigating particular outcomes that are more easily measured than others. Death, for example, is perhaps the simplest outcome that there is to measure in healthcare — in fact, many countries have national registries of when/why every single one of its citizens dies. Probably the next easiest type of outcome to measure are non-death discrete events, e.g. a hospitalization, an adverse drug event, a cancer recurrence. Measuring quality of life is more difficult — you have to go around asking people self-report their quality of life. And if ones believes, as integrative medicine pioneer Dr. Rachel Remen does, that to heal is to help people purse what has meaning and value in life…good luck measuring that outcome!

The tyranny of multiple comparisons vs. the requirements for pre-specified analyses

Most research findings are presented alongside a p-value, which is a way of describing what are the chances that a particular result might be due to randomness in the data, rather than representing a true effect. The lower the p-value, the more valid the result, and a p-value of less <0.05 is the standard, albeit arbitrary, cutoff for statistical significance in clinical research. However, when a researcher performs many different statistical comparisons, the probability that one of those many will achieve statistical significance at a <0.05 level increases, an issue known as the multiple comparisons problem. One solution is to adjust the cutoff for statistical significance — essentially the more tests a researcher performs, the more stringent the cutoff for significance needs to be.

This is all good, but what if a researcher submits a manuscript that contains ten comparisons, but in reality performed one hundred throughout the course of his investigation? The significance cutoff really should be adjusted to account for one hundred comparisons, but was likely only adjusted for ten when it was submitted for publication. It is a problem called data mining. Researchers understand that it is poor form to do this, though “data mining” to one person might be “thoughtfully exploring the data” to someone else. Indeed, data mining typically occurs not because a researcher is actively snooping around the data for a significant result, but because a researcher has worked with the data for so long that it might have just happened by accident.

Besides self-policing, there are two mechanisms to protect against against data mining. Reviewers may ask the authors to run other analyses to see if they support the results that were presented. There also may be a requirement that before any data are acquired, the authors have to specify exactly which analyses they plan to perform. It should be pointed out that such a requirement makes research less efficient. If pre-specified analyses are important, then every data set can only really be analyzed once, and one is restricted from exploring hypotheses that are generated by the results of the initial analyses.

Research is expensive!

The NIH devotes several billion dollars to clinical research on its own, and clinical research is also supported by various state organizations and philanthropy. While this may sound like a lot of money, it is not! Research is quite expensive, if you factor in the cost of salary, equipment/overhead, staff support, data collection, etc. There are unfortunately more interesting research questions than money to properly investigate all of those questions.

Another source of funding is industry…but accepting funding from industry has its issues. Say you have a pharmaceutical company that has developed a new drug, and they then pay a group of researchers to conduct a study that tests the efficacy of that drug. We can all see the problem in this scenario. It is hence critically important for researchers to disclose any conflicts of interests. For better or worse, the knee-jerk reaction of most academics is to discredit studies when there is a blatant conflict of interest.

Given the resource constraints, researchers try to be cost-effective, perhaps even taking shortcuts. It might mean interviewing subjects every other year instead of every year. Or following the subjects for 5 years, instead of 10. Of the common clinical research study designs, randomized control trials tend to be by far the most expensive type of study, followed by cohort studies, case-control studies, cross-sectional studies, and case reports.

Ethical considerations provide boundaries on what kinds of studies are permissible

From 1932 to 1972, an infamous clinical study was conducted by the U.S. Public Health Service, in which African-American men were untreated for syphilis to observe the natural progression of the disease. None of the infected men were told they had the disease, and none were treated with penicillin after the antibiotic became a proven treatment. Public outrage and congressional investigation into the Tuskegee Syphilis Study eventually led to the establishment of the Office of Human Research Protections within the Department of Health and Human Services and a series of federal laws and regulations requiring the protection of human subjects.

Scientists are thankfully much more informed and sensitive to how to ethically conduct research. Ethical considerations rightfully places limitations on which kinds of research are permissible (particularly randomized control trials), but as a result, scientists have to accept that some knowledge is unattainable. You cannot design a study that randomly assigns people to cigarette smoking (a fact touted by the tobacco industry). You can design an ethical randomized control trial that investigates the use of cannabis to reduce nausea and vomiting during chemotherapy. You probably cannot design an ethical randomized control trial that investigates toxicity in recreational use of cannabis.

There is a lot of pressure and competition in academia…and a lot of scientific misconduct

It seems like every month, I read a story in the news about how a researcher was was caught fabricating and falsifying data. This is reflected in the increasing number of studies that are retracted, and I cannot help but think that this is related to increasing pressure and competition in academia. The mechanisms that prevent scientific misconduct are feeble. One has to attest to the integrity of the study when it is accepted for publication. Researchers sometimes attempt to reproduce each other’s results, though researchers are generally much more interested in pursuing their own research. And certainly the consequences of being caught fudging are severe, often grounds for dismissal. But despite the consequences, the temptation to fabricate results is real.

Scientific misconduct erodes the public’s faith in the integrity of science. It is hard to digest research if one has to also entertain the possibility that someone made the stuff up! Furthermore, once a study is out there, it never truly disappears, even if it is retracted. Vaccines and autism, anyone?

Sidney Le is a UCSF medical student and health services researcher

Categories: OIG Advisory Opinions

Academic Tossers

The Healthcare Blog - Sat, 11/21/2015 - 11:48

When John Milton (Al Pacino) chuckled in the Devil’s Advocate “vanity, definitely my favorite sin,” he may have been referring to academics, not attorneys.

In academia skins are thin, hairs are split, emails are long, humor is self-congratulatory, and everyone cites themselves thinking that they’re Shakespeare. In the land of geniuses pettiness lies next to godliness. Wallace Sayre, a political scientist, once said that academic politics is vicious because the stakes are so low.

The iconoclast, Nassim Taleb, reserves special derision for academics. He took Steven Pinker to task for claiming that violence has progressively declined because of a decline in religion. According to Taleb, Pinker was ignoring fat tails – or the long lull before the storm. Pinker responded by saying that Taleb was being fooled by belligerence.

Not even the hard sciences are spared from hair splitters. Bruce Hillman, in The Man Who Stalked Einstein, tells the story of Philipp Lenard, a German physicist who hated Einstein, viscerally. Lenard, a devout Nazi, was no mug – he was awarded a Nobel Prize for his work on cathode rays. Lenard’s hatred of Einstein had roots deeper than anti-Semitism. Lenard was trying to prove the existence of ether, a mysterious substance once believed to fill the universe and produce gravity. While Lenard was experimenting, Einstein, in a flash of inspiration, intuited space-time, which enraged Lenard because ether was not needed to explain gravity, and this implied that Lenard had been seeking something imaginary.

Lenard felt that experimenters, not thinkers, deserved the highest honors. He despised theoretical physicists, who, he felt, merely procrastinated.  Lenard’s exaltation of experimental sciences is not out of place with academia today where experimenters get more credence (and access to the public purse) than theorists. Arthur Eddington, who proved the curvature of space-time by showing that gravity bends light in a solar eclipse, would have shared the honors with Einstein today. But Eddington is a historical footnote compared to Einstein.

Why was the accomplished Lenard so envious of Einstein? The currencies in academia are fame and recognition, not money. Fame cannot exist by itself – more fame for some comes with less fame for others. Fame is a zero sum game. Einstein’s stardom irked Lenard who felt that Einstein was not worthy of any recognition.

Not every academic is petulant. The economists John Maynard Keynes and Friedrich Hayek fought like gladiators but their duel had the aestheticism of a Socratic dialog. Their clash advanced knowledge. Keynes called Hayek’s The Road to Serfdom, a “frightful muddle”, and an example of how “starting with a mistake, a remorseless logician can up in Bedlam.” Privately, Keynes praised Hayek on his tome. The more baroque Hayek said “Keynes is not a highly trained or a very sophisticated economic theorist.” Keynes held the upper hand but both were friends and even hung out during the German air strikes in the Second World War.

A mini-Lenard is embedded in nearly every academic. Scholarly duels have become passive-aggressive – many academics discredit their opponents by ignoring them. A case in point is the clash between the economist, Paul Krugman, and the historian, Niall Ferguson. Ferguson fires the salvo. Krugman returns fire by pretending to ignore the salvo. This is a shame, because as petulant as academia can be, we lose when academics don’t argue.

In a couple of weeks I will be attending the Radiological Society of North America – one of the largest medical meetings in the world. During scientific presentations there is guaranteed to be one person, often me, who will clear his (yes, always a male) throat, walk to the mike and, assuming immeasurable pomposity, with the tone that can only arise by perfected self-love, draw attention to a patently obvious limitation in the study methodology, usually that the study is not randomized, before reminding everyone “in my experience…blah, blah, blah,” compelling the presenter to say “thank you for the thoughtful comments sir, yes, more research is needed.”

Self-love is the opium of academics.

About the author: Saurabh Jha is an academic tosser desperately seeking an alter ego. Interested candidates can reach him on Twitter @RogueRad

Categories: OIG Advisory Opinions

UnitedHealth Threatens to Pull the Plug. Why? The Obamacare Business Model Does Not Work

The Healthcare Blog - Thu, 11/19/2015 - 22:06

It’s official. The Obamacare insurance company business model does not work.

UnitedHealth Group just announced they expect to lose $450 million in the Obamacare exchanges and are seriously considering withdrawing from the program in the coming year.

This morning, the Wall Street Journal reported just about everybody else is losing their shirts in Obamacare as well:

Several other big publicly traded insurers also flagged problems with their exchange business in their third-quarter earnings Anthem Inc. said enrollment is less than expected, though it is making a profit Aetna Inc. said it expects to lose money on its exchange business this year, but hopes to improve the result in 2016. Humana Inc. and Cigna Corp. also flagged challenges…

There are signs that broad pattern has continued–and in some cases worsened–this year. A Goldman Sachs Group Inc. analysis of state filings for 30 not-for-profit Blue Cross and Blue Shield insurers found that their overall company wide results were “barely break-even” for the first half of 2015.

Goldman analysts projected the group would post an aggregate loss for the full year–the first since the late 1980s. The analysis said the health-law exchanges appeared to be a “key driver” for the faltering corporate results, and the medical-loss ratio for the Blue insurers’ individual business was 99% in the first half of 2015–up from 91% at that point in 2014, and 82% for the first six months of 2013.

Every health plan I talk to tells me that they don’t expect their Obamacare business to be profitable even in 2016 after their big rate increases. That does not bode well for the rate increases we can expect to be announced in the middle of next year’s elections.

And, then there are the insolvencies of 12 of the 23 original Obamacare co-op insurance companies–the canaries in the Obamacare coal mine–with almost all of the rest of the survivors losing lots of money.

Why is this happening?

Because nowhere near enough healthy people are signing up to pay for the sick.

This from The Robert Wood Johnson Foundation (RWJF) and The Urban Institute (UI) in their October 2015 policy brief regarding the Obamacare insurance exchange enrollment:

We estimate that just over 24 million people were eligible for tax credits for health coverage purchased through Affordable Care Act’s (ACA) health insurance marketplaces in 2015. As of the beginning of March 2015, 10 million people eligible for tax credits had selected marketplace plans, representing a plan selection rate of 41 percent of the population estimated to be eligible for tax credits. By the end of June, 2015, 8.6 million had actually enrolled in marketplace coverage with tax credits, representing an enrollment rate of 35 percent.

In recent post at Forbes, Has the Obama Administration Given Up on Obamacare?, I made the point that the Obama administration’s 2016 almost flat enrollment estimate would constitute only a small fraction of the potential market–I estimated less than 40% of those eligible for a subsidy.

But who am I?

Now, The Robert Wood Johnson Foundation and the Urban Institute have come to largely the same conclusion–enrolling a total of 10 million in the exchanges, based on historic trends, would mean only about 9 million of them would be subsidy eligible. That would amount to only 38% of the 24 million people eligible for a subsidy.

And, don’t forget that the only place a subsidy eligible person can get an Obamacare subsidy is in the state and federal exchanges. They can’t get subsidized commercial health insurance anywhere else.

And, I suggested in the same post that such a poor 2016 open enrollment would be way short of the market share required to create an efficient risk pool–having enough healthy people paying into the pool to support the sick at affordable rates. I also argued that such low enrollment rates could never make the new health insurance law politically sustainable.

That the Affordable Care Act’s individual market risk pool is so far unacceptable was reinforced by a recent McKinsey report that health insurers lost an aggregate $2.5 billion in the individual health insurance market in 2014–an average of $163 per enrollee. They reported that only 36% of health plans in the individual market made money in 2014–and that was before they found out that the federal government was only going to pay off on 12.6% of the risk corridor reinsurance payments the carriers expected and many had already booked.

Because the risk corridor program is revenue neutral, the fact that the carriers in the red are only going to collect 12.6% of what they requested means that the carriers losing money did so at a rate eight times greater than the carriers making money!

I have also regularly argued that the reason that the take-up rate among most of those eligible is so low is that the policies are still too expensive and the deductibles and co-pays are too high for other than the poorest.

In another recent post, Why the Affordable Care Act Isn’t Here To Stay–In One Picture,I pointed to an Avalere Consulting analysis that showed that while three-quarters of the poorest of those eligible for the exchange subsidies have signed up, only 20% of those making between 251% and 300% of the poverty level had so far enrolled.

What did the Robert Wood Johnson Foundation and The Urban Institute find on this count?

They found almost exactly the same thing–the poorest are buying Obamacare and the vast majority of the rest–even if they are subsidy eligible–are not:

And the reason the working and middle-class are not buying it? This from the RWJF/UI policy brief:

The uniformity of 2015 marketplace plan selection rates at different income levels across the 37 states using is striking. In part, it may reflect people’s judgments about the affordability of marketplace coverage at different income levels. Premium tax credits, cost sharing reductions, and actuarial value levels are the same across the states, so marketplace enrollment data may provide valuable information on people’s willingness to pay for marketplace health coverage. This conclusion is reinforced by several studies that have shown many people who shopped for marketplace coverage did not choose a plan, considered the available options to be unaffordable.

When are Obamacare apologists going to stop spinning the insurance exchange enrollment as some big victory that is running smoothly? Yes, Obamacare has brought the number of those uninsured down–because of the Medicaid expansion in those states that have taken it and because the poorest people eligible for the biggest exchange subsidies and lowest deductibles have found the program attractive.

But that Obamacare has been a huge failure among the working class and middle-class–not to mention those who make too much for subsidies and have to pay the full cost for their expensive plans–has once again been confirmed.

How does the Obama administration spin 2015’s unacceptably low health insurance exchange take-up rate of 35% and their projection that it will hardly grow in 2016?

Here is what HHS Secretary Burwell recently said about that:

This open enrollment is going to be a challenge but having fewer uninsured Americans to sign up is a good problem to have.

The arrogance in this spin is astounding.

When will the denial, over the real shape Obamacare is in, end?

The Robert Wood Johnson Foundation and Urban Institute findings have now given additional credibility to the very same conclusion many of us have been trying to make since the Obamacare launch: The Obama administration has NOT been so successful in enrolling those eligible–they’ve got more than 60% of the group remaining!

If the Obama administration signs up the 10 million they are estimating they will sign-up during the current open enrollment, based upon the historic number that are subsidy eligible, they will have less than the 9 million of the 24 million RWJF and UI estimate are in the potential exchange subsidy market–just a 38% success rate. And, that is nowhere near where they will have to be to make these risk pools sustainable for the insurance companies or politically sustainable in the country.

Or keep the likes of UnitedHealth Group in the program.

How can Obamacare be fixed?

First, the Obama administration can improve, but not completely solve, their Obamacare problems by dramatically revisiting their regulations so as to give health plans the flexibility they need to better design plans their customers want to buy.

But that would only be a first step.

Robert Lazewski is a principal at Health Policy and Strategy Associates.

Categories: OIG Advisory Opinions

Three Rules For a Healthy mHealth App

The Healthcare Blog - Thu, 11/19/2015 - 18:08

According to this Wall Street Journal article, the prospect that “your doctor may soon prescribe you a smartphone app” is ushering in a new era of m-healthiness.

e-Researchers from marquee academic institutions are assessing the impact of handheld apps on medication use, symptom management, risk reduction and provider-patient communication. There’s not only an technology platform but an accompanying library of tailored e-prompts, e-reminders, e-pop-ups, e-recommendations, e-messaging, e-images and e-videos.

In other words, mix one part app with one part patient and bake until quality goes up and costs go down.

Unfortunately, however, what the article failed to mention is that much of that app content is based on information that is freely available in the public domain, and that these app developers have reconfigured and adapted it according to the variable interests, expertise and culture of their sponsoring institutions.

While policymakers and researchers would like to believe that on-line and public-domain health information is a commodity, the fact is that buyer, purchaser and provider organizations have been accessing, downloading and branding it for years.

They’ve taken a special pride of ownership in the other half of the wording, editing, formatting and presentation of that content.  That’s what makes it “theirs” for both their providers and their patients.

After all, all healthcare is local.

This has important implications for the smartphone app industry.  While the academic e-researchers and business e-developers dream of having their apps used by delivery systems everywhere, the problem is that their apps are often intertwined with their own organizations’ content.

In other words, you can have any breast cancer, heart failure or post-hospital discharge smartphone-based solution that you want, just so long as you also import their prompts, reminders, pop-ups, recommendations, messages, images and videos.

What then, are three rules to have your smartphone app be adopted by health systems everywhere?

1) Architecture Trumps Content: Smart app developers understand that the value proposition of the underlying technology architecture is separate from the value proposition of the content.  The app itself needs to be independently stable, secure and snappy with minimal branching logic, an easy-to-use interface and freedom from annoying bugs, whether it’s heart failure for a hundred patients in Halifax or a dozen persons with diabetes in Des Moines.

2) Architecture Must Support Any Content: Very smart app developers also understand that the architecture should be able to accommodate any content that is preferred by their customers. If ABC Regional Health System wants their in-house policies, procedures, pamphlets, web-pages, in-house guidelines and electronic record prompts to be reflected in a smartphone app, then the app’s framework should be able to import it in a seamless plug and play fashion.

3) Architecture Should Come With Content: That being said, not every buyer, purchaser or provider will have all the content needed to manage a target population. That means app developers will need to have generic content ready to go to fill in the gaps.

Bottom line:

The business case for apps may be similar to selling a house.  First off, make sure the foundation is solid and the roof is intact.  Be prepared to move knock out walls and move windows, if that’s what the buyer wants.  And, if the house needs to be furnished with some furniture, do it; if the buyer wants some or all of their furniture to furnish the house, do it.

<em>Jaan Sidorov, MD is chief medical officer at MedSolis.</em>

Categories: OIG Advisory Opinions

Yes, People Shop for Health care. But are they Good at it?

The Healthcare Blog - Thu, 11/19/2015 - 11:53

We used to hear “no one shops for health care.” But we know that not to be true;here’s a blog post I wrote about how people are doing just that.

So, now that we know they do shop, do they do it well? That’s a good question too.

recent study from some Berkeley economists found that people on high deductible plans don’t shop well. Sarah Kliff, writing about it in Vox, says the study “shows that when faced with a higher deductible, patients did not price shop for a better deal. Instead, both healthy and sick patients simply used way less health care.”

I read the paper, by Zarek C. Brot-Goldberg, Amitabh Chandra, Benjamin R. Handel and Jonathan T. Kolstad, and had some questions and thoughts: First, the company studied has relatively well-paid workers — “employees at the firm are relatively high income (median income $125,000-$150,000),” we are told. Higher income=Less price sensitivity.

Also, we know women shop more for health care and men shop less; women make 80 to 90 percent of the health care decisions in the U.S., and they are deeply in touch with this issue, while men aren’t. I did not see a gender breakdown in the methodology. So I wonder: Men or women?

Also, we learn that workers got tools to use to assess care, but we don’t see those tools — and believe me, I have seen some terrible ones. For example, here’s a post from one of our partners, Elana Gordon at WHYY public radio in Philadelphia, about how bad one insurer’s tools were for one couple.

Also, we don’t know what kind of education on their new system the workers got, so it’s a little bit murky (though the original study is incredibly long).

The rational health care shopper

Taking up the topic again, in a recent piece titled “Patients aren’t consumers, but the fiction of the rational health care shopper continues,” my friend Trudy Lieberman puts forth an argument that people are not rational health care shoppers. I sort of agree, but disagree deeply on the causes. One big reason that people aren’t “rational” shoppers:  they don’t have information. Other reasons: 1) They’re sick and don’t want to shop. 2) They don’t expect to get robbed at the doctor’s office.

Lieberman discusses the Berkeley study in her piece, for the Center for Health Journalism at the University of Southern California Annenberg Center, then quotes me as saying our work on price transparency is good journalism and good public service. She then concludes:

“That may be, but the evidence, including the latest strong results from the Berkeley study, tells us that the focus on turning patients into shoppers has significant downsides. When people can’t distinguish between low- and high-value care or forego needed treatment because even a ‘cheap’ price is too high for the family budget, the cost of treating them may eventually be far greater. Remember, that was one of the arguments for the Affordable Care Act. But the high cost-sharing the exchange policies demand turns that premise on its head. I’m all for transparency and think Pinder’s work, as well as Steven Brill’s in Time and Elisabeth Rosenthal’s in The New York Times, goes a long way to acquaint the public about the American cost of health care. Just don’t count on 320 million people looking for the cheapest CT scan to lower the high price tag for American health care.”

I am not a Berkeley economist, and didn’t see the data or do the analysis they did, and my questions about that study persist. Also, I deeply respect and admire Trudy, and will always treasure our friendship. Her work is amazing. And I am a pig for a compliment, and so thanks, Trudy!

And yet, I have some thoughts on this piece.

Information is hard to find

From the boldfaced passages above:

1. Quality transparency is broken. People have a hard time distinguishing between high- and low-value care because the information that would help them decide what’s high and low value is hard to find. There’s some promising work being done, but it’s hard to find good, actionable information.

2. Price transparency is broken. People may skip treatment because they see the terrifyingly high sticker (Chargemaster) prices on bills.  Why are those prices so crazy high to begin with — $6,221 for an MRI? Really? Also, perhaps they don’t realize that a cash price might be lower, or they might pay a negotiated rate under their plan, not the sticker price. Also, lower-cost treatment alternatives with nearly equal merit might be available.

3. High cost-sharing is not limited to exchange policies via the Affordable Care Act: it’s rife in employer policies now too. Here’sa recent Kaiser studydetailing the rising premium cost to employees of employer-sponsored care (the employee share of premiums averages $4,955 a year for a family, almost double what it was in 2005), and the rising deductibles in employer-sponsored care (now an average of $1,077, more than triple what it was in 2006).

4. People who know prices might choose to pay less. Further, once they understand that health care pricing is random and capricious, we might see real policy change. We’re not counting on The Little Guy or Gal to be able to effectively cut through the murk, profiteering and doublespeak effectively and thus fix the health care marketplace. But we’re trying to help.

Of course, the health care experience is fraught with emotion: it’s not like shopping for a tomato or a car. People don’t want to “shop” for health care when they’re in an emergency. Truly, they don’t want to “shop” for health care at all, in my experience: they just want to get treated and get well. But increasingly, they realize that they must find information about price and quality to protect themselves.

People don’t like this, and they don’t like being in the dark. Look at this study remarking on how people want to know — and how hard they say it is to find information. (I blogged about it here.) Funded by the Robert Wood Johnson Foundation and completed by Public Agenda, the study found:

  • 56 percent of Americans have tried to find information about health care prices before getting care.
  • Most Americans seem open to looking for better-value care. The majority of Americans do not believe that higher-priced care is necessarily better quality.
  • Most Americans who have compared prices say they saved money.

Also, there’s this study about how higher prices are not necessarily better. And there’s this about high- and low- priced hospitals and links to quality.

Also, perspectives matter: if you have great health insurance with low co-pays and deductibles, and no co-insurance — and a good income and good health — you may be seeing the entire market through that prism, and may believe that others don’t shop. But they do shop, and often quite well — when they have the tools to do so.

An inexpensive MRI.

What you will see is that some people bought that MRI for $475, or $575, or $580, while others paid much more (see screenshots at right).

One insured person was charged $2,885; insurance paid $944.97, and the individual paid $1,940.03.

Some places charge $6,221 for that MRI.

Here’s our KPCC partnership page; here’s our WHYY partnership page.

A pricey MRI.

MRI charge: $580.“I was told procedure would be 1850. I have a 7500 deductaible. So I talked to the office mgr who said if I paid upfront and agreed not to report the procedure to Blue Cross, that it would be $580″

MRI charge: $3,163. “High deductible so paid the whole thing and then found out I could have had it done for *HALF* the price only blocks away. My first foray into individual insurance and it sucked. Need to shop around assuming can even get a price quote.”

Then there was the woman who called ClearHealthCosts from Missouri to say her husband was unemployed and she was off work on disability, but could go back if she showed an MRI — but she would have to pay herself. How might she shop for an MRI? she asked.

A woman from New Jersey called with a similar question — this time, though, there was a baby crying in the background.

A really pricey MRI.

Rising deductibles

People are paying more for health care in rising deductibles and co-insurance, but this phenomenon is not limited to Affordable Care Act plans: It is seen throughout the entire marketplace.

This was not caused by the A.C.A. The high deductibles and co-insurance are a function of the way our marketplace works. It keeps people in the dark about price charged, price paid, quality, outcomes, malfeasance and the like.

The system of third-party payers (insurance companies and government payers), plus the presence of employers buying insurance for employees, makes it even messier.

Also, the presence in this marketplace of for-profit companies is a driver of prices. For-profit companies need to maximize profits.

Here’s one way of thinking about it: Goldman Sachs is investing in health care. Goldman Sachs is here for the money. If there’s more for Goldman, there’s less for you. In this context, I hasten to add that nonprofit status does not confer saintlihood, especially not in this marketplace.

On quality metrics: The responsibility for making quality assessments clear falls on the providers or on regulators, not on the patients.

Yes, it’s hard, but it must be done. You have never lived until you’ve seen a bunch of radiologists arguing over what makes a good MRI. Imagine that for every procedure, every pill.

But if people can’t find this information because the radiologists (or other specialists or industry players or regulators) cannot agree, or make this a low priority, or decide not to publicize information, are patients responsible?

A path forward

If we want people to shop well for health care, we should ask ourselves what kind of tools they need.

If we give people good and workable tools for discerning price and quality, they will be better able to perform this work. That’s the problem we’re trying to solve here at We’re not seeking wholesale reform of the system, though that might be a laudable goal: We just don’t think that’s in the cards right now, and that’s not where we’re putting our energy.

Here are some suggestions: Make all the information public and easily usable, all the time.

On prices: Make public all Chargemaster rates, private-payer reimbursement rates, Medicare reimbursement rates, and cash rates, all the time.

On quality: Make public all performance data, outcomes, frequency of procedures, disciplinary actions, payoffs to providers and similar data, all the time. (Hats off to ProPublica, for example, for working to find this data and make it usable, as well as the Leapfrog Group, U.S. News and World Report, Consumer Reports and all the others who are working this problem.)

And listen to people. Here’s a note from our mailbox:

“I just want to say that your website is amazing “Please don‘t stop because you are helping people everyday, many of whom are struggling to make ends meet while others are just looking for a some transparency in a market where there has traditionally been very little.

“Thanks again,


Jeanne Pinder, is the founder and CEO of ClearHealthCosts.

Categories: OIG Advisory Opinions

Bringing a Complex Health care system Into Alignment

The Healthcare Blog - Thu, 11/19/2015 - 00:00

Ask the chief medical officer of a major health system about the issues that keep them up at night and he or she will talk about the need to understand outcomes in complex populations, the need to engage in new business models, novel collaborations with other stakeholders, and engaging “customers” i.e. patients in new ways, all while addressing increasing cost pressures and safety concerns.

Sit down with a franchise leader in oncology at a pharmaceutical or biotech innovator and ask the same questions, and the response will pretty much be the same.

The convergence of business imperatives is largely driven by two factors:  1) the shift to value based healthcare reimbursement from volume, and 2) our rapidly advancing understanding of the causes of disease and health that holds promise to accelerate further because of the proliferation of electronic health information coupled with continued scientific innovation.

These two factors are driving nearly all healthcare stakeholders – health systems, health plans, governments, and life science manufacturers – to struggle to answer the “hard questions” in healthcare – what works, for whom, why and at what cost? That’s the connection that aligns all segments of the health care and life sciences sectors in this emerging era of new financing, rapid knowledge expansion, increasing consumer expectations and care delivery strategies.

And the good news is that science and technology are advancing at a pace that will enable this to occur as long as policy, public sentiment and the right business models can be found to support rather than thwart the shift to value based, personalized healthcare.

For all participants, the shift towards value-based reimbursement and personalized healthcare poses challenges that will test the core of their business and operating models, as well as the technology and systems strategies to support these new models.

When Deloitte launched ConvergeHealth in 2014,we recognized that bringing different and critical elements of the healthcare ecosystem into alignment based on insights from health information had enormous transformative potential and was in fact becoming an imperative for our clients to survive and thrive in this new era of healthcare.

Our North Star goal is to help the healthcare system become a learning healthcare system, where all relevant information can help to drive higher quality, more efficient care while also enabling breakthrough insights that will lead to the next wave of medical innovation.  The ultimate objective is better outcomes, delivered in a cost-efficient manner, with valuebased, more personalized care as the end result.

Since we launched ConvergeHEALTH, the shift towards value based care has only accelerated.  Recently, the Catalyst for Payment Reform (CPR) reported that 42 percent of Medicare’s $360 billion in payments are now tied to value, the rest being made through more traditional fee-for-services. The Administration has set forth aggressive goals to significantly increase this percentage over time. The momentum from volume to value is growing.

At the same time, movement towards personalized care also is growing. The President announced a major Precision Medicine Initiative as part of this year’s State of the Union, the House of Representatives passed the 21st Century Cures Act, and the number of targeted, personalized therapies across therapeutic areas continues to grow.  The long promised era of personalized medicine appears to be close.

A powerful engine available for winning this market shift is insights derived from data analytics. Important factors that will determine how smoothly that engine can eventually operate include:

  • Major redirection in reimbursement. The push towards payments that actually reward outcomes, as noted, is gaining steam and requires new analytics approaches that allow us to understand financial and clinical outcomes in complex populations.
  • Massive advances in science and technology. Game-changing advances in genomics, proteomics, imaging and other aspects of scientific research and development are leading to an explosion of data, laying a path towards broader and more effective application of personalized medicine. Again, interpretation of massive amounts of complex data can hold the key to success.
  • The digital health wave. Electronic medical records, wearables and patient self-reported data via social media and other patient engagement technologies– are generating another tsunami of health information that could have a significant impact on health care and life sciences and fill critical gaps in our understanding of health and disease.

If data and analytics are the engine driving this shift, the vehicle for winning the market shift is new, increasingly collaborative business models.

Said another way, technology innovation is a necessary but wholly insufficient piece of supporting this shift.  Business model and operating model innovation are just as critical.  Deloitte is committed to innovating here as well, as our ongoing collaboration with pharmaceutical company Allergan and our frequent teammate in innovation and collaborator Intermountain Healthcare demonstrates. This is one of a number of joint ventures that enable us to leverage our ConvergeHEALTH analytics platform to support insights into what medical interventions work optimally in certain populations. (See Health care IT News Story – 3 heavyweights harness analytics for women’s health)

These types of next generation collaborations underscore a push toward enhanced clinical and operational excellence, value-based care to improve population health management and reliance on evidence-based medicine, and establishing excellence in research by leveraging real-world evidence and comparative analysis.

The writer and futurist William Gibson put it well: “The future is already here – it’s just not evenly distributed.”

That’s where health care and the life sciences stand. It’s our role to bring innovative yet pragmatic, workable strategies to ensure the future that is already here extends evenly to all industry stakeholders, and most importantly the patient.

Brett J. Davis is the general manager of Deloitte Health Informatics (DHI), providing advanced analytics services and products to health care providers, researchers and medical manufacturers.

Categories: OIG Advisory Opinions

When it Comes to Healthcare IT Success Stories, Don’t Count out the Little Guy

The Healthcare Blog - Wed, 11/18/2015 - 14:46

Today’s healthcare information technology headlines are littered with how large delivery networks are scaling up and successfully building and using IT infrastructure. But the real success story is hiding in the shadows of these large enterprise deployments, in the small and independent practices across the US. The recent ICD-10 transition, that had been foretold to drive small enterprise into financial despair due to their lack of IT savvy and infrastructure, has shown just the opposite. A report from a leading provider of billing software that was based on government and private payer claims analysis for the past 30 days shows a different story.

Small independent practices have few rejected claims and are getting paid quickly. The software vendor’s report, using data from over 13,000 small practices, showed that in October:

  • 99% of customers submitted at least one ICD-10 claim
  • 87% of customers received payment for at least one ICD-10 claim
  • 4 million claims submitted in October were already paid
  • 11 days was the average time to payment for ICD-10 claims
  • The payer rejection rate through one clearinghouse was 1.6%

These results are in line with announcements from large payers and clearinghouses like Humana, UnitedHealthcare, and Emdeon that reported no significant increase in denials during a panel at MGMA. However, the results do show small practices out-performing the industry average provided by CMS where total claim rejections were estimated at two percent.

The report clearly shows that small and independent practices that utilize an ICD-10 ready billing system designed for their needs to submit and process claims, have a lower denial rate thanthe average. “In preparing for the ICD-10 transition, [the right software] was of great importance for us to improve, and most importantly, have an EHR that effectively and accurately communicates data to our PM system, seamlessly bridging the gap between treatment records, scheduling, and billing requirements,” said Dr. Rebecca Pearson, an independent chiropractor in private practice.

This is a victory for the independent practice that is clearly out gunned when it comes to large scale IT resources and budgets. Practices of all sizes can learn that the right solutions for a small practice can allow them to operate much like their larger counterparts, and efficiently manage clinical charts, quality reports, and claims management.

Technology can level the playing field in many ways in healthcare and the future is bright for those practices that want to stay independent and leverage technology to ensure their success.

Tom Giannulli, MD is a clinical advisor to Kareo

Categories: OIG Advisory Opinions

“Winning” by Defeating the Triple Aim

The Healthcare Blog - Mon, 11/16/2015 - 19:34

You follow movies? That is, not just watching them but thinking about how they are built, looking at the structure? In classic movie structure there is a moment near the end of the first act. We’ve established the situation, met our hero, witnessed some good action where he or she can display amazing talents but also what may be a fatal weakness.

Then comes the moment: Some grizzled veteran or stern authority brings the hero up short. Think of Casino Royale, that scene where Daniel Craig’s Bond (after those brutal opening scenes) is back in London and is confronted by Judy Dench’s M. Or Obi Wan Kenobi challenging Luke: “You must learn the Force.” Or that moment in the classic Westerns when the tired, angry old sheriff rips off his badge and throws it on the desk, leaving the whole problem to the young upstart deputy. But before he stomps out the door he turns and says to the young upstart, “You know what your problem is, kid?”

And then he tells him what the problem is: not just the kid’s problem, but the problem at the core of the whole movie. He just lays it out, plain as day.

In healthcare, this is that moment. We are near the end of the first act of whatever you want to calloutthis vast change we are going through.

And where are we? Across America, the cry of the age is “Volume to value.” At conferences we all stand hand over heart and pledge allegiance to the Institute of Health Improvement’s Triple Aim of providing a better care experience, improving the health of populations, and reducing per capita costs of health care.

But in each market, some major players are throwing their muscle into winning against the competition by defeating the Triple Aim, by increasing their volume, raising their prices, doing more wasteful overtreatment, and taking on little or no risk for the health of populations. At least in the short term, the predatory strategies of these players are making it more difficult for the rest of us to survive and serve.

I’m not going to name names here. You know who you are. Worse for you in the long run, your customers and potential customers are coming to know who you are, and their strength in the market is increasing every year.

Nap time is over, folks. It’s time to put this discussion in the open.

First Question: Will They Succeed in Defeating the Movement?

These predatory systems are certainly making the movement from volume to value more difficult. Will they succeed in stopping it?

An insight from systems thinking about traffic might be instructive. One way to study traffic is to model it with automata: Create little software bots that mimic the motions and decisions of cars and drivers and set them loose on virtual freeways and streets. If you make them all the same, say all moving at the speed limit when they can, at a certain traffic density they always gridlock. If you make some of them different, if you introduce, for instance, a few slow-moving trucks onto your virtual freeway, the traffic actually moves better as it constantly re-arranges itself to get around them.

Similarly, such predatory systems may slow the rest of us down and be a problem for us, but over the longer term they may well spur faster changes in rival systems and in the customer base that will lead to more rapid and complete change.

Second Question: Will Their Strategy Succeed and Last for Them?

Whether they will succeed really depends on the strength of the other forces in the system — in this case, the forces pushing for lower cost at the same or higher quality.

These forces include employers, other large purchasers such as pension plans, health plans constructing narrow networks, competing healthcare providers, out-of-region and virtual competitors, new market entrants, and individual consumers pushed into narrow network plans with high deductibles and co-pays.

Note who owns the largest “lever and a place to stand” in this concatenation: employers and other large purchasers. They have the direct incentive, the market power and increasingly the information to try new strategies.

Competing structures, including, especially, multispecialty physician groups, are also important in many markets.Why? Because doctors are truly scared. That fear is driving many of them into the arms of hospitals and hospital-based integrated health networks. But the fear is driving others into building their own larger structures and creating specialized accountable care organizations and ACO-like arrangements through them. Increasingly they are seeking direct arrangements with self-funded employers, as with Boeing intheSt. Louis, Seattle and Chicago areas.

The cost crunch driving this price-sensitive behavior will increase as income inequality grows and as more boomers retire. The possibility of “entitlement reform” which unbundles Medicare into a defined-contribution program is slim, but if it happens it will only increase the cost crunch and put more of the decision-making power in the hands of the individual consumer.

The pressure will grow also as buyers become more aware that in healthcare price is truly not a marker for quality, only for market dominance. The prices in healthcare are not justifiable even in terms of the supply chain, as similar institutions in the same or similar markets often have wildly different price structures. In any market, under conditions of full transparency about quality, prices for substitutable products might vary by 50 percent or even 100 percent, not by 500 percent or 1000 percent as they commonly do in healthcare.

Payer and purchaser techniques such as reference pricing, bundled products and medical tourism are capable of picking apart a market and exposing healthcare providers to market forces based on price and quality whether or not those providers wish to be exposed.

Third Question: Does Size Matter?

CEOs of these expanding market dominators will tell you that it’s a defensive strategy: They know that the big crunch is coming, and they are bulking up to own as much of the market as possible as a reserve against that future.

They avoid alternative strategies out of fear: If they engage in risk contracts, if they market bundled products at market prices, if they take on capitated Medicaid contracts, they will be undercutting their ability to extract rentier payments for their market dominance, lower their top line income, and put the organization at greater risk.

Is this true? No. Let’s look at a few reasons why.

First. No, you don’t have to be a certain size, you don’t have to have a certain top line in order to survive. To survive you have to make sure that your top line is greater than what it costs you to bring in that top line. The metaphorical bottom line is the actual bottom line.

Second. Capital costs. Capital costs increase your cost basis more or less permanently. You have to bring in a certain level of business to lay off that bonded indebtedness every year, every month, before you can even think about turning a profit.

Some smart organizations are thinking like this: Look, the environment is changing rapidly. Some parts of what we do (say, primary care for certain populations) are with us more or less permanently, and all signs are that they are likely to grow with time rather than diminish. However we end up getting paid for that, the more efficiently and effectively we can do that, the better off we will be. So this is a good place to take on debt that we know we can service with that line of business, to build whatever is the most efficient business and physical structure for that. (Or we can build a public/private partnership that turns the transaction into someone else’s debt against a leasehold for us.)

Other lines of business, such as specific types of surgery or techniques such as proton beam therapy, have a quite different capital profile. In the changing environment, all techniques that are not truly helpful, that do not have a positive cost/benefit ratio for the customer, are likely to diminish substantially. In the new environment, if the value isn’t there, the volume won’t be there. So in the end, expending scarce capital capacity on building for them may look like you went to a lot of work to weld a ballandchain onto your own ankle.

Third. Different revenue streams have different effects on the bottom line. Let’s look at fee-for-service, bundled products and risk contracts.

If you are getting paid for every procedure and test in a fee-for-service world, it doesn’t matter how wasteful they are, how effective or how efficient, because every expense creates its own addition to the top line, every one of them is reimbursed, and you get paid for your inefficiencies. So as a business proposition, who cares? Volume equals value, at least for you, whether or not it does for your customers.

If you offer a bundled product, the top line is no longer per test or procedure; it is per case. It still doesn’t matter whether the case itself is wasteful. Whether the patient is better off with a new knee is irrelevant financially, but suddenly the efficiency of producing the product (the “total cost of ownership”) is deeply relevant, because every extra CT scan, every mistake, every increased complexity of the operation adds to the cost against a fixed top line. If you can’t get efficient enough to get your true costs below your price (or worse, you don’t know your true costs), then every time you sell that product you are costing yourself money.

If you offer a risk-based product, now your top line is not per case but per life — per employee per month, per Medicaid beneficiary, per patient allocated to your accountable care organization. So the cost concern shifts to that level: What is the total cost of ownership of primary care, or spine-and-pain care, or diabetes care, or total life care for that life? Now it matters not only whether you are doing operations that really don’t need to be done, that are not truly medically indicated. It matters not only whether you are doing what does need to be done in the most cost-effective way possible. It matters even more whether you could have gotten to the actual goal, a healthy pain-free patient, as efficiently, effectively and quickly as possible. And the most efficient path to health for all patients (if you can do it) is to get them there before they ever need complex and expensive care: comprehensive disease management and prevention.

The Odds of Drawing to an Inside Straight

Price is implacable. You cannot game a market that is structurally exposed to price differences, information and options. Market dominators must keep up the opacity of their prices and depend on unrated backroom deals with major payers and purchasers in order to maintain their status.

In turbulent conditions, successful strategies will be those that thrive under conditions of high variance, multiple energy inputs and multiple strategic options. Successful strategies build expertise, experience and capacity for multiple revenue streams with multiple target markets.

Given the other forces in play, we cannot build any reasonable scenario in which the status quo continues. Questions on which we can build credible scenarios include: How quickly will the collapse to a more open market come to your market? And will that collapse be limited to certain revenue streams, lines of business and target markets, or will it be across the board?

Maintaining market dominance is actually a fragile strategy based on a single scenario and a monochromatic set of assumptions about the future. If your entire business structure depends on keeping your prices a high secret, and not exposed to real competition on price and quality, you are on the crumbling edge of a cliff as the seas advance.

Joe Flower is a healthcare futurist and author. He is a contributing editor with THCB.

Categories: OIG Advisory Opinions

First, we Devalued Doctors; Now, Technology Struggles to Replace Them

The Healthcare Blog - Mon, 11/16/2015 - 17:43

The key to driving behavior change, a seasoned marketing executive turned digital health investor told a panel on patient engagement that I moderated this week, is to get beyond the demographics of customers, and to understand the “why” – what are their distinct motivations and drivers?

Customers with similar demographic characteristics might be motivated in very distinct ways, he explained; sophisticated, quantitative market research can help define the different “personalities” present in a particular market.

Healthcare businesses, he emphasized, need to recognize these differences, and customize their approaches based on this nuanced understanding.

On the one hand, it occurred to me he was describing the behavioral component of precision medicine; in the same way it’s important to match an oncology drug with the right biochemical pathway, it’s also essential to customize the motivational approach to the characteristics of each individual.

On the other hand, I realized there was something that seemed a little sad about the idea of developing extensive market analytics and fancy digital engagement tools to simulate what the best doctors have done for years – deeply know their patients and suggest treatments informed by this understanding.

Instead, it seems, we’ve slashed the time physicians get to spend with patients, protocolized and algorithmitized almost every moment of this brief encounter, and insisted the balance of time is used for point-and-click data entry and perhaps a rushed dictation.  We’ve industrialized the physician-doctor encounter – the process and the paperwork — but eviscerated the human relationship; it’s value, unable to translate easily to an excel spreadsheet, was discounted and dismissed.

As I look at the extensive analytic efforts to categorize patients, and the many digital health platforms designed to motivate behavior, it’s hard not to ask whether we’re painfully trying — at scale but without heart — to re-create something we might have been better off not destroying in the first place.

David Shaywitz is based in Mountain View, California. He is Chief Medical Officer at DNAnexus, a Mountain View based company and holds an adjunct appointment, Visiting Scientist, in the Department of Biomedical Informatics at Harvard Medical School.

Categories: OIG Advisory Opinions

Why Doctors Still Don’t Text or E-mail their Patients

The Healthcare Blog - Sun, 11/15/2015 - 16:45

According to the Nielsen survey earlier this month by the Council of Accountable Physician Practices and the Bipartisan Policy Center, the majority of medical providers in the United States still do not use emails or text messages to communicate with their patients, despite the fact that such communication channels are in very high demand from the patients.

The survey results are appalling. After all, when you receive text message reminders about your upcoming credit card bill or ask your airline a question about your flight reservation via email, why can’t you communicate with your doctor in the same convenient way? Why are we still using the technology of the 20th century to communicate with our doctors in the 21stcentury?

The answer has three sides to it: Economics, technology management and regulations.

Physicians, like you and me, have to make a living. In the current fee-for-service payment system, doctors are only paid for the services for which they can submit a claim to the insurance companies. As you may have guessed already, doctors are not always reimbursed for the time and energy that they spend on emails and text messages. If they can answer your question during an office (which pays more than online consultations) why would they answer it in an email?

Information technology has revolutionized all industries but healthcare. Everyone, except doctor and hospitals, had to either jump on the IT bandwagon or go out of business. The lack of economic incentives in the fee-for-service payment model prevented physicians to seriously consider implementing such technologies in their practices. Even larger medical providers rarely have a well-defined digital strategy. As a result, while other industries now have learned how to adopt, use and manage information technology, healthcare sector lacks the required business expertise for successful implementation of information technology.

While there are hundreds of products and thousands of experts for customer relationship management in virtually every other industry, the healthcare sector seems to lack the required technical and business expertise for patient relationship management. Even if medical providers want to better communicate with their patients, they neither have the tools nor the expertise, at least as compared with other industries. If these technologies are not correctly implemented and integrated with the workflow of medical providers, they will become a problem rather than a solution. Imagine a doctor who is constantly distracted by the flow of emails and text messages form his patients.

Finally, the misunderstanding of laws and regulations which are intended to protect patient privacy in healthcare further inhibits medical providers to fully embrace IT. The Health Insurance Portability and Accountability Act commonly known as HIPAA is a good example of such acts. I believe HIPAA is a fairly well-designed act and does pretty well in protecting patients’ privacy, but as David Harlow points out, there’s a lot of confusion about HIPAA on the part of medical providers and tremendous resistance to open communication even when authorized and demanded by patients.

These factors have created a situation in which medical providers do not have the incentive to better communicate with their patients, and even if they want to do so, they rarely know how and are often concerned about the possible legal consequences of their actions. Given these barriers, the fact that even a small percentage of medical providers are using these communication technologies is surprising to me.

Despite the lackluster survey results, I believe that medical providers will use modern communication tools in the near future. As value based payments replace the fee-for-service models, providers will have much larger incentives to communicate with their patients. This demand from the side of medical providers will drive the IT sector to develop the required tools and very soon the healthcare industry will learn how to successfully integrate these technologies into their daily routine. The generation of young and digitally native doctors will help expedite this process.

Niam Yaraghi is a fellow at the Brookings Institution. This post first appeared in the Brookings Tech Talk Blog.

Categories: OIG Advisory Opinions