In the past few years, the fortunate among us have recognised the hazards of living with an overabundance of food (obesity, diabetes) and have started to change our diets. But most of us do not yet understand that Facebook is to the mind what sugar is to the body. Facebook feed is easy to digest. It has made it easy to consume small bites of trivial matter, tidbits that don’t really concern our lives and don’t require thinking. That’s why we experience almost no saturation. Unlike reading books and long magazine articles (which require thinking), we can swallow limitless quantities of photos and status updates, which are bright-coloured candies for the mind. Sadly, we are still far away from beginning to recognise how toxic Facebook can be.
Above the Fold
How Much Is My Colonoscopy Going to Cost? $600? $5,400?
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
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
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
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)
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?
What PHR Should I Use? It’s Complicated.
A friend called me the other day: he is moving his 93 year old father from New England to the Bay Area.
This is, of course, a relatively common scenario: aging adult moves — or is moved by family — to a new place to live.
Seamless transition to new medical providers ensues. As does optimal management of chronic health issues. Not.
Naturally, my friend is anxious to ensure that his father gets properly set up with medical care here. His dad doesn’t have dementia, but does have significant heart problems.
My friend also knows that the older a person gets, the more likely that he or she will benefit from the geriatrics approach and knowledge base. So he’s asked me to do a consultation on his father. For instance, he wants to make sure the medications are all ok for a man of his father’s age and condition.
Last but not least, my friend knows that healthcare is often flawed and imperfect. So he sees this transition as an opportunity to have his father’s health — and medical management plan — reviewed and refreshed.
This last request is not strictly speaking a geriatrics issue. This is just a smart proactive patient technique: to periodically reassess an overall medical care plan, and consider getting the input of new doctors while you do this. (Your usual doctors may or may not be able to rethink what they’ve been doing.) But of course, if you are a 93 year old patient — or the proxy for an older adult — it’s sensible to see if a geriatrician can offer you this review.
An Open Letter on Open Healthcare Data
This week a host of organizations responded to a Senate Finance Committee request for feedback on how to better use healthcare data.
The inquiry is timely, given the widespread frustration providers have with health information technology (HIT), and electronic health records (EHR) systems in particular. This frustration stems from many HIT/EHR systems are locked in proprietary systems. This hinders technology’s ability to connect and exchange information freely between disparate systems, devices and sensors along the care continuum, thus undermining the overall goal of using HIT to improve efficiencies and reduce costs.
An example illustrates the point. Because HIT systems don’t work together, most hospitals use nurses to manually double check input from disparate “smart” devices. For instance, an infusion pump reports the level of pain medication being administered to a patient, as does the EHR. But these numbers sometimes don’t match, and must be double checked by at least two nurses to confirm the right dosing. Not only is this a step back for efficiency, but it’s also another manual process that has the potential to create errors and patient safety issues.
There are also economic consequences of data fragmentation. According to the Office of the National Coordinator (ONC), U.S. providers are spending $8 billion a year due to the lack of interoperability.
To address this problem and reduce the unnecessary fragmentation of healthcare data, it’s time to require the use of open and secure applications programming interfaces (APIs).
In April, a group of America’s leading scientists, named JASON, published a report that found the current lack of interoperability among HIT data sources is a major impediment to the exchange of health information. They recommended that EHR vendors be required to develop and implement APIs that support health data architecture. The recommendation was also endorsed by the President’s Council of Advisors on Science and Technology (PCAST) in May. Requiring open APIs as a foundational standard for healthcare data would reverse the current legacy of locked systems and enable the real-time exchange of information in EHR systems to reduce costs and improve patient safety.
Is the Patient the One With the Disease?
“The patient is the one with the disease.” This medical aphorism, often quoted as rule number four from Samuel Shem’s 1978 novel, The House of God, has probably been around as long as medicine itself. Its point is that doctors need to learn to accept their own vulnerability and fallibility before they can devote themselves fully to the care of their patients. And so long as medicine was built on the relationship between two parties, patients and doctors, the rule worked reasonably well.
More recently, however, the party is being transformed into a crowd. A third player is increasingly encroaching on the doctor-patient relationship, and more and more doctors are beginning to suspect that it may be the vector of much of contemporary healthcare’s pathology. Who is the third party? Its precise identity is often difficult to pin down, but its seat in the doctor’s office and at the patient’s bedside is often occupied by a hospital, a health insurer, or a government agency.
This third party usually does not see individual patients. Instead it sees aggregates, such as rates of mortality, disease incidence, and the utilization rates of particular tests, procedures, and pharmaceuticals. It tends to be particularly interested in parameters such as efficiency, safety, cost, and revenue. Because it is largely blind to individuals, however, its risk of developing certain disorders is dramatically increased. And when it falls ill, both patients and doctors suffer.
Before patients and doctors can respond effectively to such pathologies, they must first recognize that they exist. One of the first steps in recognizing a disorder is applying a name to it, and one physician who has taken up this challenge is Adam Ratner, MD, one of the founders of the San Antonio-based non-profit, The Patient Institute. Ratner, who has been struggling to clarify the nature of these pathologies for many years, believes that healthcare is in the midst of an unrecognized epidemic.
CDC Laboratory Guidance on Ebola
For more than four decades, Ebola virus had only been diagnosed in central or eastern Africa.
Then late this past March, the first cases of Ebola began appearing in a surprising part of the continent. The Ministry of Health in Guinea notified WHO of a rapidly evolving outbreak of Ebola virus disease. The outbreak in Guinea was the first sign the virus had made the jump across the continent.
Ebola then spread quickly to Sierra Leone and Liberia, and then to Nigeria.
As the world learned of the cases, CDC began receiving questions from American hospital labs. They were looking for guidance on how to handle testing for patients who had recently returned to the U.S. from West Africa with potential Ebola symptoms.
If U.S. hospitals were to run laboratory tests on these patients, how could they be sure their staff could safely handle materials that might contain this dangerous virus? Did they need the kind of personal protective equipment they saw CDC scientists using when they were testing for Ebola?
