The Health Care Blog – Page 473 – Everything you always wanted to know about the Health Care system. But were afraid to ask.

Above the Fold

Is It Possible That All Healthcare Needs to Know We All Learned In Kindergarten?

Aug 29, 2014• 10

By JOSEPH M. SMITH, MD

US Healthcare is sick and getting sicker, and while its chaotic complexity suggests to many that it will need to fail big before it can be rebuilt, some simple rules may help to get it back on track. As this the time of year when many of us prepare to send our children on grandchildren off to school in the hopes that they will learn what they need to succeed, I thought we could revisit the lessons of Kindergarten and their application to healthcare. The following list, initially from “ALL I REALLY NEED TO KNOW I LEARNED IN KINDERGARTEN” by Robert Fulghum. has been adapted (read ‘man-handled’) for applicability to US healthcare. You’ll find the original list here: http://www.robertfulghum.com/

Share everything – In healthcare, this means share ALL the data, all the information, all the acquired wisdom. Interoperable systems are essential. Price transparency is the right side of history. Automated, coordinated, connected systems are essential. Healthcare is too much of a team sport not to share all that we know, so that we can quickly understand what works, what doesn’t, and what it’s all going to cost.

Play fair – It isn’t fair when decisions are made without a person’s input. It isn’t fair that a patient should bear the risks, the pain, the scars and the costs without having unfettered access to all the relevant information. Shared decision making is part of playing fair in a world where healthcare is meant to happen for patients and with patients, but not to patients.

Don’t hit people. – We must avoid ‘hitting’ patients with costs they can’t bear, or complications they didn’t know could happen. We should avoid ‘hitting’ clinicians with unsophisticated systems that complicate their lives and distract them from their patients. We need to stop ‘hitting’ innovators with unanticipated or needlessly complicated regulatory hurdles. And we need to work hard to have all of us avoid the ‘hit’ of a financially and logistically unsustainable healthcare system.

Put things back where you found them. Except for things like an infected appendix or a malignant growth, this continues to make great sense. And as we go about transforming healthcare, we must recognize that wholesale, sweeping changes are easier to envision than execute. While progress requires change those changes that align with / enhance / expedite existing workflows will be easiest to achieve.

Clean up your own mess – Healthcare is big enough that there are messes everywhere. We should favor local control over central planning. Patients must bear some responsibility for the consequences of their life-style choices that might be reflected in their insurance costs. Hospitals must monitor and manage their own quality metrics. Medical boards need to step up their efforts to spotlight and sanction professional inadequacy. Our federal government must do a better job of limiting inappropriate payments in healthcare. If each of us cleans up after ourselves, things get better quickly.
Continue reading…

The Power of Small

Aug 29, 2014• 10

By David C. Kibbe, MD & Vince Kuraitis

Everywhere we turn these days it seems “Big Data” is being touted as a solution for physicians and physician groups who want to participate in Accountable Care Organizations, (ACOs) and/or accountable care-like contracts with payers.

We disagree, and think the accumulated experience about what works and what doesn’t work for care management suggests that a “Small Data” approach might be good enough for many medical groups, while being more immediately implementable and a lot less costly. We’re not convinced, in other words, that the problem for ACOs is a scarcity of data or second rate analytics. Rather, the problem is that we are not taking advantage of, and using more intelligently, the data and analytics already in place, or nearly in place.

For those of you who are interested in the concept of Big Data, Steve Lohr recently wrote a good overview in his column in the New York Times, in which he said:

“Big Data is a shorthand label that typically means applying the tools of artificial intelligence, like machine learning, to vast new troves of data beyond that captured in standard databases. The new data sources include Web-browsing data trails, social network communications, sensor data and surveillance data.”

Applied to health care and ACOs, the proponents of Big Data suggest that some version of IBM’s now-famous Watson, teamed up with arrays of sensors and a very large clinical data repository containing virtually every known fact about all of the patients seen by the medical group, is a needed investment. Of course, many of these data are not currently available in structured, that is computable, format. So one of the costly requirements that Big Data may impose on us results from the need to convert large amounts of unstructured or poorly structured data to structured data. But when that is accomplished, so advocates tell us, Big Data is not only good for quality care, but is “absolutely essential” for attaining the cost efficiency needed by doctors and nurses to have a positive and money-making experience with accountable care shared-savings, gain-share, or risk contracts.

Startups Seeking Series A? Apply to Pitch at Traction at Health 2.0!

Aug 28, 2014

Calling all digital health startups! If you are actively seeking Series A funding, then apply to Traction: Health 2.0’s Startup Championship. The deadline for applications is Aug 29th, so don’t miss out on this great opportunity.

Traction has plenty to offer for anyone who is interested in learning more about the digital health industry and to see some of the hottest startups of 2014. Between the startups pitches we’ll feature two panel discussions by industry leaders who explain current trends in digital health investment.

The Corporate Investor Perspective:

Joe Volpe of Merck, Noah Lewis of GE Ventures, and Jack Young of Qualcomm will share their perspectives on what criteria are most important for digital health investors. Get the scoop on the must-haves for young startups seeking funding.

Are Federal Regulations Stifling Disruptive Healthcare Technologies in the US?

Aug 28, 2014• 8

By TIM MALIYIL

In the past few years, we’ve seen headline after headline marveling at the advancements of medical technology. From wearable tech and micro sensors to 3D printing and health-oriented apps, it’s evident that technology and medicine have merged into an industry that’s pushing healthcare to a new level.

Yet many in the health tech industry are also voicing concerns about government regulators and their standards for healthcare technology. Some have even gone as far as accusing the FDA of “stifling” the creativity of healthcare tech and hindering the value these devices and apps could bring to the public.

In early 2014, legislation was introduced in an attempt to redesign the regulatory framework for certain types of technologies and lessen the FDA’s control over this growing industry. But are the FDA’s standards and actions so bad?

I’m in the tech field myself, and while I’ve heard many arguments against the FDA’s regulations, I strongly feel that it’s completely within its rights as a regulatory agency to place limits on medical technology. The FDA’s standards are put in place to protect consumers and to correct disingenuous manufacturer claims — an alarmingly frequent trend in today’s digital world.

How Much Is My Colonoscopy Going to Cost? $600? $5,400?

Aug 27, 2014• 88

By JEANNE PINDER

How much does a colonoscopy cost? Well, that depends.

If you’re uninsured, this is a big question. We’ve learned that cash or self-pay prices can range from $600 to over $5,400, so it pays to ask.

If you’re insured, you may think it doesn’t matter. Routine, preventive screening colonoscopies are to be covered free with no co-insurance or co-payment under the Affordable Care Act.

However, we’re learning that with colonoscopies, as with mammograms, people are being asked to pay sometimes. It’s not clear to us in every case that they should pay, and since we don’t know all the details of these events, we can only offer some general thoughts. We’ve also heard from Medicare enrollees without supplemental Medicare policies that they think they’re responsible for 20 percent of the charged price — so 20 percent of $600 vs. 20 percent of $5,400 is a big deal.

If you’re on a high-deductible plan and the charge to you will be, say, $3,600, you can probably ask around and find a lower rate.

A thorough view of some colonoscopy billing issues is in this article in The New York Times by Libby Rosenthal, who has been covering health costs for the paper. We’ve heard also about in-network providers using out-of-network anesthesiologists, so it pays to pay attention.

Doubling Down on ACOs and Health Information Networks

Aug 27, 2014• 11

By JAAN SIDOROV, MD

Want to achieve effective health care, reduced costs, increased quality, population health, widespread prevention and seamless health information access?

It’s easy, says this article in Population Health Management: mix one part PHO with one part HRB to create a HAPPI.

This correspondent was confused too, but that’s what’s proposed by three smart academics from Johns Hopkins, Arizona State University and UC Berkeley.

As I understand it, Population Health Organizations (PHOs) would be responsible for all medical, public health, community and social services in a defined geographic area and coordinate them with local education, housing and labor. Much of it would be paid for by a pooled risk-adjusted global or capitated payment (budget) from all insurers.

Each organization would be paired with a Health Record Bank (HRB), which would act as a huge data warehouse that not only stores all medical information, but any other publically available information on every individual enrolled in the PHO. The HRBs would be owned and operated by “trusted custodial organizations.” Data access would be ultimately controlled by each patient.

The authors believe that patient payments would be a source of additional revenue for their PHOs. Examples include buying “apps” that are tailored to their individual health needs, or selling their personal health information, especially if it means helping physicians buy an electronic health record or access cutting edge research.

Zen and the Quest For Quality

Aug 25, 2014• 21

By RICHARD GUNDERMAN, MD

Celebrating its 40 anniversary this year, Robert M. Pirsig’s Zen and the Art of Motorcycle Maintenance bears several distinctions. It is listed in the Guinness Book of World Records as the eventual bestseller that was rejected by more publishers than any other, 121. It went on to sell more than 5 million copies, making it the most popular philosophy book of the past 50 years. And it focuses on a truly extraordinary topic, which its narrator refers to as a “metaphysics of quality.”

Quality is a hot topic in healthcare today. Hospitals and healthcare systems are abuzz with the rhetoric of QA and QI (quality assessment and quality improvement), and healthcare payers including the federal government are boldly touting new initiatives intended to replace quantity with quality as the basis for rewarding providers. Yet as Pirsig’s narrator, Phaedrus (see Plato’s dialogue of the same name), comes to realize, quality is very difficult to define.

In fact, giving an account of quality is so difficult that it drove Zen’s author mad. And this is a man whose IQ, 170, would make him one of the most intelligent people in any health system. The problem, of course, is that there is a big difference between intelligence and wisdom, and in the quest for wisdom, mere intelligence often leads us dangerously astray. Something similar is happening in healthcare today, where schemes to improve quality often precede sufficient efforts to understand it.

For example, we seek to gain greater control over healthcare outcomes through measurement, only to discover, to our chagrin, that people are massaging the data to meet their numbers. We create new programs intended to increase patient throughput, only to discover unintended perverse effects on the quality of relationships between patients and physicians. Initiatives intended to reduce error rates turn out again and again to stifle innovation.Continue reading…

Share Your Primary Care Innovations

Aug 24, 2014

By THE AMERICAN RESIDENT PROJECT

Where: Harvard Medical School
When: September 16th, 2014
What: Primary Care Innovations Pitch Off

By 2015 the U.S. will need an additional 52,000 physicians to meet the country’s needs. Primary care providers are in particularly high demand for the valuable role they play in managing chronic conditions, providing preventive care services and leading patient-centric care delivery models. The health care community is coming together to ask: What does the future of primary care look like?

What innovations are already being implemented?

The Primary Care Challenge

For two months, we will be accepting submissions as part of the effort to raise the profile of innovative ideas in primary care delivery. Any U.S. medical student, resident or physician is encouraged to submit a description of a creative program that their practice has implemented around primary care delivery. A variety of prizes will be offered to finalists and participants, including an all-expenses paid trip to Boston for five finalists to share their proposals in-person with experts and peers at our Primary Care Innovations event.

Starting this month you can check out the Primary Care Challenge website for step-by-step instructions on how to submit your program and take advantage of this great opportunity. Feel free to share your thoughts with us on Twitter and use #PCC14

The Data Response Curve (In Honor of the Dose Response Curve)

Aug 24, 2014• 10

By JORDAN SHLAIN, MD

All medical students learn about the dose response curve in pharmacology lectures. The dose-response curve informs us of how we should dose a medication in the context of its efficacy and its toxicity. Too little medicine won’t have the desired effect, and too much medicine can be toxic.

In the era of digital health, data have become the new “big pharma,” and we are facing the emergence of a data-response curve in which access to too little data is inactionable, and access to too much data can be overwhelming. Digital health devices abound today, and has enabled quantification of nearly every health and wellness metric imaginable. Sadly, in our exuberance about these new sources of data, we often conflate “more data” with “better data.”

In the era in which data have become the booming commodity of exchange in healthcare, we describe an emerging data-response curve. Large data sets can be at best clarifying or at worst self-contradictory. Too little data on the data-response curve, as with medication dosing, can be insufficient for effective action or decision-making. Too much data can be toxic to the user such as the physician, leading to poor decisions or worse, to analysis paralysis.

We live in a world of exploding data, and we need to be thoughtful. Medicine is a people business in need of data, not a data business on need of people. In reductive form, all humans make decisions based on inputs (data) from their environment and on individual analysis of the data in the form of non-linear, non-quantifiable perception. When we as doctors, policy-makers, or simply as human beings receive these inputs, one of three things happens: 1. We make a decision to do something (for example a treatment decision based on abnormal data), 2. We make a decision to do nothing (for example, normal data which we believe requires no action), or 3. We need more data in order to make an informed decision to do item #1 or item #2. More does not necessarily equal better data. More data is simply more.

Better data are actionable data wrapped in the context of the patient and the patient’s condition. Imagine each piece of objective data connected to concurrent subjective data, and surfaced in the context of a specific condition relevant to the patient. HealthLoop enables patients to generate contextual objective data married to their subjective symptoms and served to a clinician in an actionable context. High signal and low noise are the digital health equivalents of on the dose-response curve of a favorable therapeutic window.

See where some folks live on the Chart. Where do you live?