Health for life

Hi,

When I read the article at this link: http://www.drbenkim.com/articles-orthorexia.html#comment-10281 I just knew I had to share it. Enjoy!!

Ever been a nut about the specific things you eat? Been there. Done that. Maybe you did, too.

Read it!!  Good one!!

Love you,

Be back soon,

Marcia

What happens when a tricorders batteries go dead

Heads-up displays in cars. Apps that can remotely open garage doors. Cable TV embedded in bathroom mirrors. The techie Disease Management Care Blog lusts after all of them and understands when advances like these cross from being mere conveniences to vital necessities.  While it waits for an unenthusiastic DMCB spouse to catch up, it looks forward to the arrival of other lifestyle enhancements like internet-enabled goggles, ear hair curing nanotechnolgy and Star Trek styled tricorders, perably with lots of blinka blinka diodes.      
      
Good thing that the X-Prize Foundation agrees on the latter, though without the blinka blinka.  According to this web page, it will award $10 million to any outfit that can cram "artificial intelligence, wireless sensing, imaging diagnostics, lab-on-a-chip and molecular biology" in a single home-based "tool" that is safe, weighs no more than five pounds and has internet connectivity. Competitors for this "Qualcomm Tricorder X PRIZE" are expected to make trade-offs between audio, visual displays, imaging technology, portability, bandwidth-use, power requirements, and sensors.

The Foundation antcipates that the device will enable consumers to "incoporate health knowledge and decision-making into their daily lives." The ultimate goal is to allow end-user "direct care" for "15 diseases" that trumps "science" over the "art of medicine," bypasses the monopolistic "bottleneck" created by the traditional doctor, clinic or hospital and places diagnosis and measurement under the control of the patient.

Gosh. It wasnt too long ago that credentialled physicians totally owned the health care space. Thanks to their brute force learning, a rigorous apprenticeship and 10,000 hours worth of experiential heuristics, patient-consumers could be be highly confident of getting a correct diagnosis and treatment.

While thats still true, that space is changing: networked e-Patient communities can harness the wisdom of crowds, IBMs "Watson" can strip-mine the worlds medical knowledge to answer a single question for anyone anytime, computers are aiding the interpretation of imaging studies, non-physician clinicans can monitor as well as coach personalized self-care for thousands of consumers from afar and elite surgeons can remotely project their expertise worldwide with stereotaxic robotics.  While skeptics may doubt the short-term prognosis for this particular X-PRIZE, there can be no doubt that the concept is ultimately sound.

Big changes are in store for medical practice.

The impact will be greatest for care for persons with chronic conditions.  This not only represents another threat to the viability of primary care but undercuts a major value proposition for ACOs.

Providers and health insurers that adapt will survive; those that adopt or co-opt will thrive.
 
Depite the vision of a fully self-sufficent health care consumer, the DMCB doubts physicians will go extinct. They will  adopt and co-opt because high tech plus high touch trumps high tech with low touch.  The sum of a tricorder plus a provider will be far more than the sum of its parts. 

Even the Enterprise needed a Dr. McCoy on board.

The stats guys go to work

The Disease Management Care Blog continues to welcome blog posts from outside authors. This is another one, courtesy of Erik Tollefson, who works in the health policy field. He can be reached at erikDOTmDOTtollefsonATgmailDOTcom

As payers increasingly pursue reimbursement strategies that share risk with health care providers, risk adjustment is emerging as an important topic in health policy research.  Indeed, for providers, the ability to properly identify the underlying health risks of a specific population could mean the difference between earning savings rather than paying penalties.  As the importance of risk adjustment ascends grows, increasing attention is being given to the robustness sophistication of adjustment methodologies. That includes including the data used to estimate the risk of a covered population risk. 

In a recent study published in the British Medical Journal (BMJ), John Wennberg and co-authors explore how under-recognized “patient observation bias” can contaminate risk adjustment results.

Previous studies have identified many pitfalls of using observational data as a proxy of a population’s true disease burden. One common example is the phenomenon of “upcoding.” This practice not only adjusts diagnostic codes to maximize reimbursement, it is a well-documented source of bias that spuriously increases variation between geographical regions and complicates risk adjustment.

Wennberg and colleagues show that patient observation bias is another potential pitfall in the science of risk adjustment that has not received such attention. The phenomenon can be quantified by using numerous proxies such as frequency of visits by physicians and the intensity of diagnostic tests (both laboratory and imaging) ordered. Previous research has shown that geographical areas with higher patient observation bias independently correlate with higher rates of comorbidity after being adjusted for all the other relevant patient factors that underlie true risk.

Using a sample of Medicare claims data, the authors computed two different risk adjustment measures: 1) using standard methods; 2) adjusting for potential observation bias.  Overall, the adjusted method (using visit intensity) emerged as a more accurate predictor of the population’s underlying burden of illness. Thanks to their ability to identify a source of bias that explained a greater portion of variation in important categories such as sex, age, and race, but was the authors were able, compared to the usual risk adjustment methods, to reduce the variation levels between different geographic regions.

The importance of accurate risk adjustment is not just limited to its potential impact on increasingly high financial stakes in the health care sector. The ability of policy makers to understand why variation occurs in health care costs and utilization across geographical areas has emerged as one of the key questions that may ultimately improve delivery and cut costs in a bloated health care system. This study offers important evidence that part of the answer may indeed lay in the supply-inducing doctors self-erring patients for unnecessary diagnostic procedures that littered Atul Gawande’s account of rising health care costs in McAllen, Texas.

Another important take home lesson, however, also applies: the quality of underlying data. With continued histrionics surrounding access to ever greater amounts of health care data, it helps to remember that qualitatively understanding what one is actually measuring is still as important as the accuracy of the underlying statistical methods.