So many topics and issues, so little time

Trying to get caught up after my Mom died. Coming this week...

The authors gave me a final pre-publication copy for review and commentary. I love it thus far.

Overview

Essential to health care reform are two elements: standards of care for managing clinical information (analogous to accounting standards for managing financial information), and electronic tools designed to implement those standards. Both elements are external to the physician’s mind. Although in large part already developed, these elements are virtually absent from health care. Without these elements, the physician continues to be relied upon as a repository of knowledge and a vehicle for information processing. The resulting disorder blocks health information technology from realizing its enormous potential, and deprives health care reform of an essential foundation...

...First, from the outset of care, relevant patient data must be chosen, and its implications determined, based on the best available medical knowledge, independent of the limited personal knowledge of the practitioners involved. Patient data must be systematically linked to medical knowledge in a combinatorial manner, before the exercise of clinical judgment, using information tools to elicit all possibilities relevant to the problem situation, while defining and documenting the information taken into account. Practitioners’ clinical judgments may add to, but must not subtract from, high standards of accuracy, completeness and objectivity for that information.

Second, in complex cases, particularly in cases of chronic disease, the organization of data in medical records must be optimized for managing multiple problems over time. This means that each medical record must begin with a complete list of carefully defined patient problems, and that other clinical information in the record must be linked to the problem or problems to which it relates.

I. Introduction: Building a new system

A culture of denial subverts the health care system from its foundation. The foundation—the basis for deciding what care each patient individually needs— is connecting patient data to medical knowledge. That foundation, and the processes of care resting upon it, are built by the fallible minds of physicians. A new, secure foundation requires two elements external to the mind: electronic information tools and standards of care for managing clinical information...

...Contrary to what the public is asked to believe, physicians are not educated to connect patient data with medical knowledge safely and effectively. Rather than building that secure foundation for decisions, physicians are educated to do the opposite—to rely on personal knowledge and judgment—in denial of the need for external standards and tools. Medical decision making thus lacks the order, transparency and power that enforcing external standards and tools would bring about...

...Without the necessary standards and tools, the matching process is fatally compromised. Physicians resort to a shortcut process of highly educated guesswork...

...Medical practice is thus trapped in a subjective realm. Unlike scientific practitioners, medical practitioners do not operate in an objective realm, where the contents of thought and knowledge exist independently of the individual mind, a realm where knowledge can be reliably transmitted and applied, where new knowledge can be rapidly translated into practice, where all knowledge can be tested against patient realities. Isolated from this objective realm, the mind be- comes a negative force, a cause of confusion and disorder. Physicians are not equipped to fulfill their immense responsibility safely and effectively. Other practitioners are not equipped to share that responsibility with physicians. Patients are not equipped to work effectively with multiple practitioners, nor to assume the ultimate burden of decision making over their own bodies and minds. Third parties are not equipped to create order out of this chaos. Practitioners and patients are not accountable for their own behaviors, while third parties are left free to manipulate disorder for their own advantage...

...Missing is a total system for enforcing high quality care by all practitioners for all patients.

...At first glance, this subject matter may seem like just a varia- tion on current policy concerns with using “health information technology” to bring “evidence-based medicine” to “patient-centered” care. Yet, current policy fails to comprehend the needed discipline in medical practice and thus fails to define precisely what is needed from health information technology. A dangerous paradox thus exists: the power of technology to access information without limits magnifies the very problem of information overload that the technology is expected to solve. Solving that problem demands a meticulous, highly organized, explicit process of initial information processing, followed by careful problem definition, planning, execution, feedback, and corrective action over time, all documented under strict medical accounting standards. When this rigor is enforced, a promising paradox occurs: clarity emerges from complexity.

...[W]ere we to close the gap between medical practice and patient needs, society then could find enormous opportunities to harvest resources now going to waste. These wasted resources include not only vast sums spent on low-value care but also a vast body of medical knowledge that all patients and practitioners could use more effectively, simple tests and observations that in combination could uncover solutions to patient problems, patients who could become better equipped and motivated to improve their own health behaviors, routine patient care that could become a fertile source of new medical knowledge, and the firsthand insights of practitioners and patients who could participate in harvesting that new knowledge for their own benefit.

Closing the gap between medical practice and patient needs would transform how medicine is personally experienced by practitioners and patients alike. Practitioners could find their work to be less exhausting and more rewarding, emotionally and intellectually, than what they now undergo. The physician’s role could disaggregate into multiple roles, all freed from the impossible burdens of performance that physicians are now expected to bear. The expertise of nurses and other non-physician practitioners could deepen, and their roles could be elevated. All practitioners could follow time-honored standards of care that in the past have been honored more in the breach than the observance. All practitioners and patients could jointly use electronic information tools for matching data with medical knowledge, radically expanding their capacity to cope with complexity. All could use structured medical records, whose structure would itself bring order and transparency to the complex processes of care. Inputs by practitioners could thus be defined and subjected to constant feedback and improvement. A truly evidence-based medicine could develop, where evidence would be used to individualize care rather than standardize it. And a system of checks and balances could develop, where patients and practitioners would act on incentives for quality and economy far more effectively than before...

Buy the book (I'm not shilling it; I don't know them and I don't get anything from it). Extremely thought-provoking.

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Below, I have a complete copy of this IOM Report as well.

SUMMARY

The Institute of Medicine (IOM) report To Err Is Human estimated that 44,000-98,000 lives are lost every year due to medical errors in hospitals and led to the widespread recognition that health care is not safe enough, catalyzing a revolution to improve the quality of care.

Despite considerable effort, patient safety has not yet improved to the degree hoped for in the IOM report Crossing the Quality Chasm. One strategy the nation has turned to for safer, more effective care is the widespread use of health information technologies (health IT). The U.S. government is investing billions of dollars toward meaningful use of effective health IT so all Americans can benefit from the use of electronic health records (EHRs) by 2014. Health IT is playing an ever-larger role in the care of patients, and some components of health IT have significantly improved the quality of health care and reduced medical errors. Continuing to use paper records can place patients at unnecessary risk for harm and substantially constrain the country’s ability to reform health care. However, concerns about harm from the use of health IT have emerged.

To protect America’s health, health IT must be designed and used in ways that maximize patient safety while minimizing harm. Information technology can better help patients if it becomes more usable, more interoperable, and easier to implement and maintain. This report explains the potential benefits and risks of health IT and asks for greater transparency, accountability, and reporting. In this report, health IT includes a broad range of products, including EHRs,3 patient engagement tools (e.g., personal health records [PHRs] and secure patient portals), and health information exchanges; excluded is software for medical devices.

Clinicians expect health IT to support delivery of high-quality care in several ways, including storing comprehensive health data, providing clinical decision support, facilitating communication, and reducing medical errors. Health IT is not a single product; it encompasses a technical system of computers and soft- ware that operates in the context of a larger sociotechnical system—a collection of hardware and software working in concert within an organization that includes people, processes, and technology.

It is widely believed that health IT, when designed, implemented, and used appropriately, can be a positive enabler to transform the way care is delivered. Designed and applied inappropriately, health IT can add an additional layer of complexity to the already complex delivery of health care, which can lead to unintended adverse consequences, for example dosing errors, failing to detect fatal illnesses, and delaying treatment due to poor human–computer interactions or loss of data. In recognition of the rapid adoption of health IT, the Office of the National Coordinator for Health Information Technology (ONC) asked the IOM to establish a committee to explore how private and public actors can maximize the safety of health IT–assisted care. The committee interpreted its charge as making health IT–assisted care safer so the nation is in a better position to realize the potential benefits of health IT.

OK. Another good read. Moving along...

High on the list of breakthroughs expected to transform medicine is personalized medicine – the use of new methods of molecular analysis to better manage a patient’s disease or predisposition to disease. Personalized medicine is likely to change the way drugs are developed and medicine is prescribed.

Yet the regulatory and financial systems that will support personalized medicine are not yet in place. The mission of the PMC is to build the foundation that underpins the advancement of personalized medicine as a viable solution to the challenges of efficacy, safety and cost.

The Personalized Medicine Coalition (PMC), was launched in 2004 to educate the public and policymakers, and to promote new ways of thinking about health care. Today, PMC represents a broad spectrum of more than 200 academic, industry, patient, provider and payer communities, as we seek to advance the understanding and adoption of personalized medicine concepts and products for the benefit of patients.

What is Personalized Medicine?
As defined by the President’s Council on Advisors on Science and Technology, “Personalized Medicine” refers to the tailoring of medical treatment to the individual characteristics of each patient…to classify individuals into subpopulations that differ in their susceptibility to a particular disease or their response to a specific treatment. Preventative or therapeutic interventions can then be concentrated on those who will benefit, sparing expense and side effects for those who will not.

What they're mostly advocating here is genetic molecular biochemistry and its place in HIT for Comparative Effectiveness Research. to wit, consider this paper I got from their site:

With federal officials pursuing the goal of a personal human genome map under $1,000 in five years (White House, 2010), it is possible to envision a future where treatments are tailored to individuals’ genetic structures, prescriptions are analyzed in advance for likely effectiveness, and researchers study clinical data in real-time to learn what works. Implementation of these regimens creates a situation where treatments are better targeted, health systems save money by identifying therapies not likely to be effective for particular people, and researchers have a better understanding of comparative effectiveness (President’s Council of Advisors on Science and Technology, 2010).

Yet despite these benefits, consumer and system-wide gains remain limited by an outmoded policy regime. Federal regulations were developed years before recent advances in gene sequencing, electronic health records, and information technology. With scientific innovation running far ahead of public policy, physicians, researchers, and patients are not receiving the full advantage of latest developments. Current policies should leverage new advances in genomics and personalized medicine in order to individualize diagnosis and treatment. Similarly, policies creating incentives for the adoption of health information technology should ensure that the invested infrastructure is one that supports new-care paradigms as opposed to automating yesterday’s health care practices...

...This paper outlines the challenges of enabling personalized medicine, as well as the policy and operational changes that would facilitate connectivity, integration, reimbursement reform, and analysis of information. Our health system requires a seamless and rapid flow of digital information, including genomic, clinical outcome, and claims data. Research derived from clinical care must feed back into assessment in order to advance care quality for consumers. There currently are discrete data on diagnosis, treatment, medical claims, and health outcomes that exist in parts of the system, but it is hard to determine what works and how treatments differ across subgroups. Changes in reimbursement practices would better align incentives with effective health care practices.

Furthermore, we need privacy rules that strike the right balance between privacy and innovation. These rules should distinguish health research from clinical practice, and create mechanisms to connect data from multiple sources into databases for secondary research usage and population cohort analysis. More balanced rules would improve innovation. It is nearly impossible to evaluate treatment effectiveness without being able to aggregate data and compare results. Faster knowledge management would enable “rapid learning” models and evidence-based decision-making on the part of physicians and public health officials...

Click the title image above for the full pdf. See also

and (pdf)


I find triangulating all of this so very interesting. Much more to come on the health care QI implications of all of the foregoing.

EPIGENETICS

(Nov 19th) I was chatting with my VP for Medical Affairs Dr. Jerry Reeves tonight at a social event about my interest in and intense study now regarding the pharmacogenetic stuff. He brought up the topic of "epigenetics," which I'd read about but had not reviewed lately. Another tie-in. Just what I needed, more to read and think about.

What is Epigenetics?

Conrad Waddington (1905-1975) is often credited with coining the term epigenetics in 1942 as “the branch of biology which studies the causal interactions between genes and their products, which bring the phenotype into being”. Epigenetics appears in the literature as far back as the mid 19th century, although the conceptual origins date back to Aristotle (384-322 BC). He believed in epigenesis: the development of individual organic form from the unformed. This controversial view was the main argument against our having developed from miniscule fully-formed bodies. Even today the extent to which we are preprogrammed versus environmentally shaped awaits universal consensus. The field of epigenetics has emerged to bridge the gap between nature and nurture. In the 21st century you will most commonly find epigenetics defined as ‘the study of heritable changes in genome function that occur without a change in DNA sequence‘...

Add it to my pile.

ALSO, ADD IN "HIA" TO THE MIX

Health Impact Assessment

Health impact assessment (HIA) is commonly defined as “a combination of procedures, methods, and tools by which a policy, program, or project may be judged as to its potential effects on the health of a population, and the distribution of those effects within the population”...

The major steps in conducting an HIA include

• Screening (identify projects or policies for which an HIA would be useful),
• Scoping (identify which health effects to consider),
• Assessing risks and benefits (identify which people may be affected and how they may be affected),
• Developing recommendations (suggest changes to proposals to promote positive or mitigate adverse health effects),
• Reporting (present the results to decision-makers), and
• Evaluating (determine the effect of the HIA on the decision).

HIA is similar in some ways to environmental impact assessment (EIA). The National Environmental Policy Act (NEPA) requires federal agencies to consider the environmental impact of their proposed actions on social, cultural, economic, and natural resources prior to implementation. Proposed actions may include projects, programs, policies, or plans. HIA, unlike EIA can be a voluntary or a regulatory process that focuses on health outcomes such as obesity, physical inactivity, asthma, injuries, and social equity. HIA has been used within EIA processes to assess potential impacts to the human environment.

See also the World Health Organization site on HIA.

Then there's this:

Section 6301 of the PPACA (pdf), a.k.a. "ObamaCare," established the "Patient Centered Outcomes Research Institute."

"The Patient-Centered Outcomes Research Institute (PCORI) is an independent organization created to help people make informed health care decisions and improve health care delivery. PCORI will commission research that is guided by patients, caregivers and the broader health care community and will produce high integrity, evidence-based information.

PCORI is committed to transparency and a rigorous stakeholder-driven process that emphasizes patient engagement. PCORI will use a variety of forums and public comment periods to obtain public input throughout its work."

As with the case of the ACOs (Accountable Care Organizations; Section 3022 of the PPACA), I can't help but wonder about the fate of PCORI should SCOTUS strike down the Affordable Care Act in toto.

Beyond that, it will be interesting to see what extent of "transparency and a rigorous stakeholder process" ensues between all of the entities that will need to pull together. Notwithstanding that "transparency" is the feel-good term of the decade, opacity in service of turf protection (economic or otherwise institutional) will remain a risk.

e.g., let me return yet again to one of my favorites, the esteemed medical economist J.D. Kleinke:

Health Care’s ‘Prisoners’ Dilemma’
Joe Wilson’s health insurer back in Pittsburgh might have a clear financial interest in a system that would allow it to feed various streams of Joe’s clinical information to the Las Vegas hospital, to improve the quality and reduce the cost of his medical care. But doing so would be massively expensive for the insurer, not just in direct and indirect costs, but in incalculable strategic costs. If the company invested millions to create the open infrastructure required to connect its hospital, physician, pharmacy, and lab claims information systems to every hospital in Pittsburgh—let alone to every hospital in the United States—all of the other health insurers in Pittsburgh could connect to the same network for a fraction of the cost. While Joe’s insurer did the heavy lifting, its competitors would bear none of the massive up-front costs and could price their health plans well below the cost of Joe’s, for all of the years that his insurer was investing in that system.

If health care’s IT problems are a reflection of its broader economic problems, then the strategic conflicts within the health insurance and hospital industries themselves—the two most obvious beachheads for HIT development—are sufficient explanation for why we have no interoperable health care infrastructure. Notwithstanding the happy talk of their advertising, health insurers aim to attract and lock in healthy people and drive away sick ones. The less masqueraded goal of the hospital is to attract and lock in sick people and market to those who are not sick yet. Having an interoperable HIT system that allows patients to shop around, with their fully portable EMRs, for a higher-quality or lower-cost health insurer or hospital works directly against these goals.

For insurers in particular, this strategic conundrum over HIT is a redux of the broader managed care conundrum about prevention, which is essentially the prisoners’ dilemma at the heart of game theory. The prisoners’ dilemma always results in an unfortunate ending: All actors in the game would be rewarded if they cooperated and did the right thing by each other. But none will do the right thing without assurance that the other players will all follow, and so they each do exactly the wrong thing, limiting their own downside and thus creating a suboptimal outcome for all. The best way for a health insurer to use HIT to cope with the prisoners’ dilemma is to design a proprietary system that makes it easy for healthy members to sign up; difficult for sick members who need good information to find it and thus remain satisfied with their plan; and even more difficult for everyone outside the insurer’s own organization (that is, everyone looking to get paid) to navigate it. The worst way to cope with the prisoners’ dilemma is to provide an open, interoperable system that works equally well for all members and can exchange data with all other health insurers.

Yeah. More specifically, I would pose this troubling question regarding "personalized medicine." A health dx/px/rx care solution targeted specifically to me has a market potential of precisely one. That's not how Big Medicine/Big Pharma/Big Payors make their money. Now, were I Warren Buffet or Bill Gates or (the late) Steve Jobs or Paul Ryan, maybe I wouldn't care -- 'I'll have the lobster and filet mignon at market price.'

Beyond that, how indeed shall we "realign reimbursements"?

Also in this regard, I have to scoff at unregulated "free market" theorists and their beloved panacea "efficient markets hypothesis." They uniformly gloss over or grossly ignore the very real and fundamental -- if inconvenient -- corollary that the most "efficient" markets are also, by definition, the lowest margin.

Think about it. How could it be otherwise? The Sum of Self-Interested Rational Actors, All Having Transparent Access To The Same Information Upon Which to Act Upon And Express Their Value Preferences?

Right. Get serious. Gimme a break.

Twelve words, from a generation ago:

"In the gap between perception and reality, there's money to be made."

- Michael Milken

Ask Yves Smith as well. Hat tip to her for her pithy, bulls-eye debunking observation on the "efficient markets" point (I'm reading her new book "eCONNED" at the moment; been following her blog for quite some time).

HOW ABOUT A LITTLE KLEINKE CODA?

...The very idea of a public works project (at least within our own borders) sounds like an artifact from an era eclipsed by nearly three decades of hostility toward government-based solutions to domestic problems, combined with a seemingly religious belief in marketplace solutions for all of them.

As this paper makes unambiguously clear, the marketplace will not solve the HIT problem. If so, it would have solved it under the watchful eye of "managed care" or as part of the Y2K conversion or during the most recent Health Insurance Portability and Accountability Act (HIPAA) compliance scramble. There is indeed a collective business case for a national HIT system, but it is one well beyond the reach of the health care marketplace. The federal government may be unable to finance and build that system for political reasons, but it can do far more than trying to jawbone the private sector into building it on its own.

If health care’s chronic IT failure is steeped in economic reality, then the solution should be as well. The obvious entry point is reimbursement. The federal government, directly or indirectly, purchases half of U.S. health care... [Market Failure And The Creation Of A National Health Information Technology System]

Again, published in 2005. Could have been yesterday.

SBM CRASHES THE PHARMACOGENOMICS PARTY


From Science-Based Medicine: David Gorski's "Woo-omics"

A prelude to woo-omics: Genomics, proteomics, everywhere an “omics”
One of the most difficult problems in science-based medicine is how to do a better job identifying which patients will respond to which treatments. Clinical trials, by their very design, have to look at average responses in populations. In essence, a treatment is compared to either placebo or standard-of-care, a choice mainly driven by ethics and whether effective treatments exist for the condition being studied. It is then determined using statistics whether a significant difference exists between the two groups. The difficulty, as any clinician knows, is applying the results of clinical trials to individual patients. In any population, there is, after all, a range of responses to any drug or treatment, and it would be desirable to be able to predict which patients will fall at the end of the bell-shaped curve where the treatment is most effective and which will fall at the end of the curve where the treatment works poorly or not at all...

...[T]hese days, the search for predictors of response, prognosis, and therapies most likely to do good has moved into the realm of what we now call “omics.” The term “omics” as it is used today originally came from genomics, which is, put very simply, the study of the entire genome (i.e., all the genes in an organism). It then expanded to be used for proteomics, which, again put very simply, is the study of all the proteins expressed by a cell type, organ, or organism. Since then, the term has metastasized to many, many areas of biology, such as metabolomics, secretomics, lipidomics, and many, many others. Here’s a general schema of what I’m talking about:

The problem with all these “omics” is that they are hideously complicated, with interactions of thousands of genes, proteins, and other entities that must be made sense of in order to understand what is going on. Indeed, arguably the reason we never bothered with these sorts of analyses before is that, until the last 10-20 years quite simply they were impossible. The computing power and algorithms necessary to do them simply didn’t exist and had to be developed. Neither did the technology. Then, beginning in the late 1990s, techniques were developed to measure expression profiles that included every known gene in the human genome. Building on techniques developed for the Human Genome Project and other genomics initiatives, in the early 2000s, we had cDNA microarrays, the ability to scan thousands of single nucleotide polymorphisms (SNPs) and look for associations with diseases, and the like...

The result of the new systems biology and “omics” has been a torrential flood of data that’s far ahead of our ability to analyze it fully. As the cost of sequencing a genome has fallen from hundreds of thousands of dollars to less than $10,000 (soon to be less than $1,000), genome sequencing will soon fall to within the price range of other commonly used medical tests. (CT scans and MRIs cost around $2,000 or so, and the Oncotype DX test, for example, costs around $3,000.)

Unfortunately, even as the flood of data accelerates, successful strategies for actually using that data clinically have been elusive. Indeed, last year, around the time of the tenth anniversary of the completion of the Human Genome Project, there were a series of articles asking, basically, “Where are all the cures we were promised?” Of course, as I’ve pointed out before, the sequencing of the human genome (and now all these other genomes, as is being done in the Cancer Genome Atlas, for example) has been the easy part. The hard part is making sense of it all and relating differences in individual genomes to specific diseases and to the discovery and validation of biomarkers for response to specific therapies. Just looking at one example can demonstrate why it’s so hard to make sense of this data and to figure out how to use it to develop cures to diseases like prostate cancer. Does all of this mean that all the information we’ve gathered and connections we’ve made so far in the Human Genome Project, the Cancer Genome Atlas, and other similar projects that have tried to relate genomics data to human disease, prognosis of disease, and response to therapies useless? Of course not. It’s just that the speed with which this data will result in real cures was arguably oversold. Right now, the situation is confused and uncertain. and we are still very far from the vision of truly personalized medicine that so many see “omics” as the path towards...

Party Poopers. ;)

As always, the comments at SBM are as interesting as the articles, e.g.,

# cervantes on 21 Nov 2011 at 10:01 am

John Ioannidis has written some very important papers about data mining in genomics. People have finally gotten the message, that they should have understood from the beginning, that if you go through a whole lot of data points — in the case of these studies of the association between genetic variants and diseases, we’re talking thousands — you will find spurious correlations. The p value can only be interpreted in light of Bayes theorem. If the prior probability of an association is very small, then it is still highly unlikely, even if your p value is also small. Science is a process of learning — it builds continually on prior evidence. If something doesn’t make sense based on what we already know, it’s unlikely to be the explanation for an observation. (Bayes theorem is extremely important, and in biomedical research, we’ve gotten stuck in a Gaussian world that many of the people who do research, even some prominent investigators, fundamentally do not understand. As Ioannidis demonstrated, most published findings are false.)

Yeah, John Ioannidis, I'd forgotten about him. And, don't get me started on "p-values" or Gauss. I'll see your Gauss and raise you a Chebychev.

ON DECK

More on privacy (apropos to a great degree of the above): who owns your health information? res privatae? res litigosae? res nova? A complicated question I've dwelled on at some length in prior posts. An issue that, again, varies by state, type of data, and proposed use of the information. One that goes to the core of Comparative Effectiveness Research initiatives and breakthroughs in "Personalized Medicine."

Also, an ONC certified EHR vendor (I won't name them -- for now) has had so many bug issues they've issued a "upgrade release recall." I'm not making that up. One of my REC client clinics is on that platform. The O.M. told me today she has 87 open/unresolved support tickets. It is a mess.

Oh, and this is interesting:

...Nearly 250,000 doctors age 55 and over are facing the same choice—take on time-consuming obligations to document quality care and the real possibility of cuts in what the government pays them if they slip up, or just get out before penalties kick in. These older practitioners make up 32 percent of the physician workforce, according to the American Medical Association’s data from 2009, the most recent year available.

Early retirement could worsen what the Association of American Medical Colleges already predicts will be a shortage of 63,000 physicians in 2015. And that’s before an estimated 30 million more people sign on for health insurance in 2014, many of them seeking out a regular doctor for the first time.

The health care law and the 2009 economic-stimulus package transformed some now-optional programs for doctors—such as using electronic health records or tracking quality of care—into requirements for treating Medicare patients. Where the federal government now uses carrots, mostly in the form of bonus payments to participating physicians, it will start to use sticks in a few years. Doctors will face cuts in their reimbursement from Medicare if they don’t successfully use electronic medical records and report on their quality of care. In 2015, doctors will lose 1 percent of their Medicare reimbursement for not using electronic medical records, and 1.5 percent for failing to report quality data, such as whether they checked patients’ blood pressure or blood-sugar levels. Every year you miss the goals, the penalties go up.

The requirements aim to make the anachronistic U.S. health care system more efficient, and the vast majority of doctors would say they want to provide high-quality care. Providing better care will also bring down overall costs by keeping patients healthier and preventing duplicative tests. But as doctors cope with these new requirements, they also must deal with others that will change how they run their practices. For starters, they’ll have to switch to a new medical-coding system by October 2013 that balloons from 18,000 codes to nearly 140,000 to describe medical services.

Physicians also face the perennial uncertainty of Medicare reimbursement levels because Congress has repeatedly failed to agree on a permanent solution. Unless Congress acts—and lawmakers often wait until the last moment to pass the “doc fix”—physicians will absorb a nearly 30 percent cut in 2012...

Relatedly,

Primary Care Workforce Facts and Stats

...Primary care is a foundational element of the U.S. health care system and is required to meet our Nation's triple aims of improving quality, containing costs, and improving patient and family experience. Primary care is also critical to ensuring access to health care for all Americans and reducing health care disparities. Whether the focus is on the individual, a population, or the health care system, good access to primary care is associated with more timely care, better preventive care, avoiding unnecessary care, improved costs, and lower mortality.

...Primary care by some measures is the largest aspect of our health care system. In 2008, 490 million visits were made to primary care physicians—a bit more than half of all visits to physicians' offices. But primary care's share of visits has been declining.

The U.S. primary care system is struggling under increasing demands and expectations, diminishing economic margins, and increasing workforce attrition compounded by diminishing recruitment of new physicians, nurses, and physician assistants into primary care.

Approximately one-third of physicians currently practice in primary care but fewer than one-fourth of current medical school graduates are going into primary care. The Council on Graduate Medical Education is concerned that the trend, if unchecked, will progress to fewer than one-fifth of medical students specializing in primary care...

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JUST IN...

Make sure the way you use an EMR doesn't unwittingly look like fraud
Technically Speaking. By PAMELA LEWIS DOLAN, amednews staff. Posted Nov. 21, 2011.

...Apparently many vendors advise practices to shut off the audit function to help speed up the system, Dr. Gelzer said. But turning off the audit function means the physician is not HIPAA compliant, Warner warned.

These potential problems are being exacerbated, some say, by the financial incentives created under the Health Information Technology for Economic and Clinical Health Act of 2009 to encourage EMR use. To qualify for incentives, physicians must demonstrate meaningful use of EMRs that are certified by organizations approved by HHS.

Meaningful use certification is designed only to ensure that EMRs meet the individual meaningful use objectives and measures, said Karen Bell, MD, chair of the Certification Commission for Health Information Technology, one of the organizations contracted with the ONC to test and certify EMRs for meaningful use. But Dr. Gelzer is concerned that physicians may feel a false sense of security knowing that their systems were certified to meet government-mandated standards.

The Dept. of Health and Human Services Office of the Inspector General included in its 2012 Work Plan a look at the relationship between certified EMRs and fraud and abuse vulnerabilities.

"I would take this to mean that the OIG is seeing problems," Dr. Gelzer said...

Interesting.
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More to come.