Month: May 2014

Will the Shinseki Resignation Turn around the VA?

May 30, 2014• 28

By MARK GRABAN

As I wrote on LinkedIn, instead of blaming “bad managers” or a “lack of integrity” at local VA sites, like Phoenix, we have to look at the system.

Dr. W. Edwards Deming always said that senior management is responsible for the system. We need to ask who designed, set in place (or tolerated) things like:

“Unrealistic” 14-day waiting time goals (says the VA Inspector General)
Bonuses and financial incentives driven by hitting these targets
A culture where people can’t ask for help (“don’t make things look bad”)
An environment that tolerates not having enough capacity to meet demand

In circumstances like that, being pressured by distant leaders to hit an unrealistic target… I would GUARANTEE that there would be some level of cheating. And, more than 40 VA sites are under investigation by the Inspector General. This is systemic. It’s too simplistic to label people as “bad” and to then fire them. “Gaming the numbers” is very predictable human behavior (and it happens in other countries’ healthcare systems too).

In his statement, Shinseki did point fingers at himself on one level:

At the end of a speech to an annual conference of the National Coalition for Homeless Veterans in Washington, Shinseki addressed a new interim report on the VA health-care system’s problems. He said he now knows that the problems are “systemic,” rather than isolated as he thought in the past.

“That breach of integrity is irresponsible,” he told the largely supportive audience. “It is indefensible and unacceptable to me.” He said he was “too trusting” of some top officials and “accepted as accurate reports that I now know to have been misleading with regard to patient wait times.”

President Reagan famously quoted an old Russian maxim, “Trust, but verify.” That’s good advice for leaders anywhere.

Toyota’s Taiichi Ohno also famously said:

“Data is of course important in manufacturing, but I place the greatest emphasis on facts.”

“Data” might include spreadsheets and reports on the web. Data are too easily gamed, faked, and fudged. People can manipulate data in many ways and leaders need to be aware of that.

“Facts” are things you can see with your own eyes. Lean leaders “go to the Gemba” (or the actual workplace) to see first hand and to talk to the people who are doing the work. A Lean VA leader would visit locations (or send people) to help verify that data is not being manipulated and that processes are being followed. You’d talk to veterans to see if they have complaints about long waits that aren’t showing up in the data.Continue reading…

Optimal Positioning Strategy and the “Quantified Relationship” in Baseball and Health Care

May 30, 2014• 2

By CHARLIE GROSS

Strategy in baseball used to be a fairly straightforward matter. A few strategy rules – a right handed pitcher was more successful against a right handed batter, lefty against lefty, no left handers at infield positions except for first base, don’t hold the runner at first with two outs and a left handed batter, and sacrifice bunt to move a runner at first with less than two outs- were taken as gospel and practiced by the community.

It was baseball’s version of the 10 commandments, written in stone and for the first century of baseball, unchangeable.

The world changed, though few knew it, in 1946 when Cleveland manager Lou Boudreau moved his shortstop to the right of second base against the legendary dead pull hitter Ted Williams of the Boston Red Sox.

However, like many innovations, it is only with the advent of large data sets that the revolution that started that July day in Cleveland impacted day to day strategy.

A players position on the field is no longer the result of the manager’s intuitive hunch, or even the result of consulting a written document of the past several encounters between a particular pitcher and a particular batter- a scatter gram of where this batter is likely to hit the ball. Instead, major league teams are increasingly relying on sophisticated, large data sets that are housed on remote servers.

These data sets run complex algorithms predicting the best solution for a particular ecosystem- elements of which include – batter, pitcher and all the defensive players and their particular gifts, skills and tendencies- and even the weather and time of day.

A Policy Model For Telehealth Technologies

May 30, 2014• 5

By JOSEPH KVEDAR, MD

The nation’s ongoing battle to strike a delicate balance between increasing access to quality health care for all Americans and reducing overall health care spending just scored one of its most substantial victories.

In late April, after several months of thoughtful and robust collaboration, the Federation of State Medical Boards (FSMB) ratified a new model national policy – the Appropriate Use of Telemedicine in the Practice of Medicine – at its annual meeting in Denver.

This marks the first time the medical community has unilaterally acknowledged the impact technology has had on the practice of medicine, and the ability telemedicine — or connected health — has to facilitate and improve the delivery of health care.

Let us first put this in perspective. We all know health care is at a critical juncture. The implementation of the Affordable Care Act means millions of newly eligible Americans will seek access to an already over-burdened health care system.

The nation faces a serious shortage of primary care providers, specialty care is becoming more diversified, and access to care in rural areas is an ongoing challenge. All of these issues are on the rise.

Technology-enabled Care

Enter technology-enabled care. Real-time video encounters between patients and providers reverse the burden on patients to seek care in a hospital or doctor’s office by bringing health care directly to them, in their home. At the same time, remote monitoring, sensors, mobile health and other technologies are helping to reduce hospital readmissions, and improving adherence to care plans and clinical outcomes, as well as patient satisfaction.

Connected health tools also support preventative care efforts for chronic care patients and can empower individuals to make positive lifestyle changes to improve their overall health and wellness.

Momentum for telehealth is accelerating at an undeniable rate. As of March, twenty states and the District of Columbia have passed mandates for coverage of commercially provided telehealth services; 46 states offer some type of Medicaid reimbursement for services provided via telehealth.

A study by Deloitte predicts that this year alone, there will be 100 million eVisits globally, potentially saving over $5 billion when compared to the cost of face-to-face doctor visits. This represents a growth of 400 percent in video-based virtual visits from 2012 levels, and the greatest usage is predicted to occur in North America, where there could be up to 75 million visits in 2014. This would represent 25 percent of the addressable market.

Health Datapalooza Exclusive Interview: Dwayne Spradlin, CEO, Health Data Consortium

May 30, 2014

Interview by Matthew Holt, Co-Chairman, Health 2.0

In just two days, Health 2.0 will be attending Health Datapalooza in Washington, D.C. from June 1-3. In this exclusive interview, Dwayne Spradlin, CEO, Health Data Consortium will highlight the new sessions, panels, workshops, and speakers you can look forward to at Health Datapalooza! As an additional bonus, Spradlin gives insight on how data is driving health care innovation, and sheds light on new and on-going projects of the Health Data Consortium.

Three Reasons AstraZeneca Were Right to Reject Pfizer

May 30, 2014• 4

By BECKY BAINES

The transatlantic stand-off between the two pharmaceutical giants, Pfizer and AstraZeneca, is over; possibly for good. With Pfizer having failed to conclude a £69bn deal with the British-Swedish multinational pharmaceutical firm, almost £7bn was wiped from AstraZeneca’s share value.

AstraZeneca’s board, which decided that Pfizer’s bid was inadequate, has subsequently been criticised by major shareholders for “failing to engage”. Pfizer meanwhile, has been accused of being driven purely by the lure of lower taxes, job cuts and budget reductions. We have rounded up the reasons why we think that Astra Zeneca were right to reject the takeover bid from Pfizer.

Jobs Threatened

The proposed takeover had major implications for several sectors. From major health and pharmaceutical recruiters to manufacturers and research companies, all would have been affected by Pfizer’s huge takeover bid. Despite repeated initial assurances from Pfizer’s CEO, Ian Read, both AstraZeneca and Pfizer finally acknowledged in last week’s parliamentary select committee meeting that there would be cuts to both jobs and research.

Indeed, even before the failure of the bid, many academics, scientists and even union leaders were accusing Pfizer of being driven purely by the possibilities of a lower taxes and reductions to the research budget. Pfizer had already been described by a former boss of AstraZeneca as a “praying mantis” ready to “suck the lifeblood out of their prey”.

However, AstraZeneca’s current chairman, Leif Johansson said that the deal represented “a significant risk to shareholders.”

Samsung Throws Kitchen Sink onto the Wrist

May 29, 2014

BY MATTHEW HOLT

Yesterday phone and electronics giant Samsung rushed out its next step in health related hardware. Samsung was clearly trying to get this out the door and in the press before Apple’s forthcoming announcement of something health-related –or I assume that’s what their industrial espionage told them Apple was about to reveal (just kidding guys!). And some people (well, Techcrunch) were clearly unimpressed.

The most compelling moment which I captured (poorly) in the video above was the demo of the new SIMBAND–albeit a concept rather than an available product. (In fact a couple of their partners told me that no-one outside the company has one). In the SIMBAND are a stack of new sensors which attempt to use the wrist to monitor not only heart rate, but blood pressure, temperature, EKG and do it all continuously. You can see a rather better video of the demo from Gizmodo, which I cued up to start at the right place.

They also announced a fully open platform (what at Health 2.0 we dub the Data Utility Layer) called Samsung Architecture Multimodal Interactions (SAMI) to accept and spit out all types of health related data.

This is all potentially very impressive. Samsung’s first two attempts at Smart Watches have fizzled, but they tend to keep coming back, and now are pretty much the best at Smart Phones. (You fan bois can keep your teeny iPhone screens!) But can they make the health related smartwatch work? I’ve three quick assessments/questions.

Socialized or Not, We Can Learn from the VA

May 29, 2014• 27

By ART KELLERMANN, MD

In a post on the New York Times’ Economix blog not long ago, Princeton economics professor Uwe E. Reinhardt addresses the common characterization of the British health care system as “socialized medicine.” The label is most often used pejoratively in the United States to suggest that if anything resembling Great Britain’s National Health System (NHS) were adopted in the U.S., it would invariably deliver low-quality health care and produce poor health outcomes.

Ironically, Reinhardt notes, the U.S. already has a close cousin to the NHS within our borders. It’s the national network of VA Hospitals, clinics and skilled nursing facilities operated by our Veterans Healthcare Administration, part of the Department of Veterans Affairs. By almost every measure, the VA is recognized as delivering consistently high-quality care to its patients.

Among the evidence Reinhardt cites is an “eye-opening” (his words) 2004 RAND study from in the Annals of Internal Medicine that examined the quality of VA care, comparing the medical records of VA patients with a national sample and evaluating how effectively health care is delivered to each group (see a summary of that study).

RAND’s study, led by Dr. Steven Asch, found that the VA system delivered higher-quality care than the national sample of private hospitals on all measures except acute care (on which the two samples performed comparably). In nearly every other respect, VA patients received consistently better care across the board, including screening, diagnosis, treatment, and access to follow-up.

Vendor Management Systems and the Commoditization of Physicians and Nurses

May 29, 2014• 3

By Val Jones, MD

In a policy environment where quality measures and patient satisfaction ratings are becoming the basis for reimbursement rates, one wonders how VMS software is getting traction. Perhaps desperate times call for desperate measures, and the challenge of filling employment gaps is driving interest in impersonal digital match services? Rural hospitals are desperate to recruit quality candidates, and with a severe physician shortage looming, warm bodies are becoming an acceptable solution to staffing needs.

As distasteful as the thought of computer-matching physicians to hospitals may be, the real problems of VMS systems only become apparent with experience. After discussing user experience with several hospital system employees and reading various blogs and online debates here’s what I discovered:

1. Garbage In, Garbage Out. The people who input physician data (including their certifications, medical malpractice histories, and licensing data) have no incentive to insure accuracy of information. Head hunter agencies are paid when the physicians/nurses they enter into the database are matched to a hospital.

To make sure that their providers get first dibs, they may leave out information, misrepresent availability, and in extreme cases, even falsify certification statuses. These errors are often caught during the hospital credentialing process, which results in many hours of wasted time on the part of internal credentialing personnel, and delays in filling the position. In other cases, the errors are not caught during credentialing and legal problems ensue when impaired providers are hired accidentally.

Personal Tech

May 29, 2014• 17

By ROB LAMBERTS, MD

My 87 year-old father broke his hip this past weekend. He was in Michigan for a party for his 101 year-old sister, and fell as he tried to put away her wheelchair. The good news is that he’s otherwise pretty healthy, so he should do fine.

Still, getting old sucks.

During the whole situation around his injury, surgery, and upcoming recovery, one thing became very clear: technology can really make things much easier:

I communicated with all of my siblings about what was going on and gave my “doctor’s perspective” to them via email.
I updated friends and other family members via Facebook.
I have used social media to communicate cousins about what is going to happen after he’s discharged from the hospital and coordinate our plans.

All in all, tech has really made things much easier.

This reality is in stark contrast to the recent headline I read on Medscape: “Doctors are Talking: EHRs Destroy the Patient Encounter.” The article talks about the use of scribes (a clerical person in the exam room, not a pal of the Pharisee) to compensate for the inefficiencies of the computer in the exam room. Physician reaction is predictable: most see electronic records as an intrusion of “big brother” into the exam room.

To me, the suggestion to use a scribe (increasing overhead by one FTE) to make the system profitable is ample evidence of EMR being anti-efficient.

Despite this, I continue to beat the drum for the use of technology as a positive force for health care improvement. In fact, I think that an increased use of tech is needed to truly make care better. Why do I do so, in face of the mounting frustrations of physicians with computerized records? Am I wrong, or are they?

Neither. The problem with electronic records is not with the tech itself, it is with the purpose of the medical record. Records are not for patient care or communication, they are the goods doctors give to the payors in exchange for money. They are the end-product of patient care, the product we sell. Doctors aren’t paid to give care, they are paid to document it. Electronic records simply make it so doctors can produce more documents in less time, complying with ever-increasingly complex rules for documentation.

Will Tech Revolutionize Health Care This Time?

May 28, 2014• 66

By JOE FLOWER

After decades of bravely keeping them at bay, health care is beginning to be overwhelmed by “fast, cheap, and out of control” new technologies, from BYOD (“bring your own device”) tablets in the operating room, to apps and dongles that turn your smart phone into a Star Trek Tricorder, to 3-D printed skulls. (No, not a souvenir of the Grateful Dead, a Harley decoration or a pastry for the Mexican Dia de Los Muertos, but an actual skullcap to repair someone’s head. Take measurements from a scan, set to work in a cad-cam program, press Cmd-P and boom! There you have it: new ear-to-ear skull top, ready for implant.)

Each new category, we are told, will Revolutionize Health Care, making it orders of magnitude better and far less expensive. Yet the experience of the last three decades is that each new technology only adds complexity and expense.

So what will it be? Will some of these new technologies actually transform health care? Which ones? How can we know?

There is an answer, but it does not lie in the technologies. It lies in the economics. It lies in the reason we have so much waste in health care. We have so much waste because we get paid for it.

Yes, it’s that simple. In an insurance-supported fee-for-service system, we don’t get paid to solve problems. We get paid to do stuff that might solve a problem. The more stuff we do, and the more complex the stuff we do, the more impressive the machines we use, the more we get paid.

A Tale of a Wasteful Technology

A few presidencies back, I was at a medical conference at a resort on a hilltop near San Diego. I was invited into a trailer to see a demo of a marvellous new technology — computer-aided mammography. I had never even taken a close look at a mammogram, so I was immediately impressed with how difficult it is to pick possible tumours out of the cloudy images. The computer could show you the possibilities, easy as pie, drawing little circles around each suspicious nodule.

But, I asked, will people trust a computer to do such an important job?

Oh, the computer is just helping, I was told. All the scans will be seen by a human radiologist. The computer just makes sure the radiologist does not miss any possibilities.

I thought, Hmmm, if you have a radiologist looking at every scan anyway, why bother with the computer program? Are skilled radiologists in the habit of missing a lot of possible tumors? From the sound of it, I thought what we would get is a lot of false positives, unnecessary call-backs and biopsies, and a lot of unnecessarily worried women. After all, if the computer says something might be a tumor, now the radiologist is put in the position of proving that it isn’t.

I didn’t see any reason that this technology would catch on. I didn’t see it because the reason was not in the technology, it was in the economics.

Years later, as we are trending toward standardizing on this technology across the industry, the results of various studies have shown exactly what I suspected they would: lots of false positives, call-backs and biopsies, and not one tumor that would not have been found without the computer. Not one. At an added cost trending toward half a billion dollars per year.