Tuesday, October 16, 2007

Future - The View of the Future from Aspen and San Francisco

I have doubts about new technologies’ impacts at the point of care. I’m particularly skeptical about computational advances defining and limiting what doctors can and cannot do in their offices. But I recognize new computer technologies may remake medical practice, and Health 2.0 may forecast the future.

But will rosy computer-guided scenarios empower doctors and patients in office, clinics, and hospital settings? Will computational advances pan out in the present and near future clinical world? I’m dubious.

On the hand, I’m optimistic about new imaging, new less-invasive procedures, and new genomic advances .I have listed 28 of these innovations in a paper I’m now writing, and which I shall publish in this blog.

As practicing physicians, you deserve an update and rundown of what might be. Below Brian Klepper, PhD, a widely known futurist, fresh from meetings of great minds, at a recent Aspen Health Forum and a Health 2.0 conference in San Francisco, offers his views as expressed in The Health Care Blog. on October 12, 14, and 15. Because this current blog combines three blogs from another blogger, it is longer than usual. For busy clinicians with too little time to read this sort of thing, I apologize for this length.

Healing Unbound: The Promise of Advancing Computational Power

By Brian Klepper, PhD

• Laptop-attached ultrasound units that produce startlingly clear internal images for five dollars in the field.

• Organs that re-generate inside scaffolds.

• Drugs tailored to an individual’s biology.

• Micro-images of cancerous cells lit up by bio-chemical markers.

• Decision support tools that scan the physiological values in electronic health records for patterns too complex to be detected by an unaided clinician.

The advances available from dramatic improvements in computational capabilities were a recurring theme at the Aspen Health Forum, with experts from each discipline describing where the technology was leading us.

I attended two sessions featuring Star Trek clips that predicted realities now within at least theoretical reach. (Prescient and corny, audiences nodded nostalgically.) Sessions on biotechnology, imaging, electronic health records (EHRs), and the hospital of the future highlighted the power that is being leveraged to improve care.

The deeper point is that biological mechanisms are built on incredibly complex metabolic webs. The information we depend on has also become overwhelming in scope but fragmented.

We’re only now beginning to have the computational power required to model, integrate and manage the many processes contained in each of these arenas. The power we access through digital analytics allows us to extend and broaden our reach.
A simple example was the argument, made long ago by David Eddy, a pioneering giant in the application of information technology to care, that the explosion of new knowledge has outrun the capacity of even the best human minds to appreciate and incorporate it. Tens of thousands of new articles are added to the medical literature every month, far more than any professional can evaluate and absorb. But information technology can store all that updated knowledge in formats available at moments of decisions, when we need it most.

Dr. Eddy described the promise of cognitive processing, in which software routines would scan and compare dozens or hundreds of physiologic measures within a patient’s health record for patterns a clinician could never identify.

A quick analysis might show, for instance, that when 19 of the variables present appear in combination with the values detected, there’s a 62 percent probability of a particular condition. The tool would then describe possible next steps in the care pathway.

The horizon is receding across technologies. In a session on the future of diagnostic imaging, GE Healthcare’s Medical Director Robert Honigberg thrilled the audience by showing decade-old and new ultrasound images. He then ticked off ways that, combined with broader advances in information technology, greater macro- and micro-imaging clarity would improve our abilities to effectively address issues: screening for stroke, Alzheimers and cancer; strengthening the power of primary care physicians in rural settings; virtual identification of pathologies; global disease registries; image-guided radiation treatments; and on and on.

Finding ways to help patients, clinicians and purchasers leverage the vastness of health information for their own purposes falls into the larger realm of Health 2.0. Still in its formative stages but gathering steam quickly, this sector of health informatics could create the pricing/performance transparencies and decision support that can positively improve clinical quality and finally make health care markets work, lowering cost.

But one of Health 2.0’s real appeals is its business model which, as Google has learned, leverages the utility of information to create communities and markets that have commercial value. That, in turn, makes it low cost to the end user, and therefore highly accessible.

Some developments offer more accessible (i.e., lower cost) value propositions than others. In an everyday context, those, like Health 2.0, that depend almost strictly on data analysis and reformulation into decision-support will likely be far less costly, with far greater potential for population-level impact than, say, those that involve biologics. That relationship might be reversed, though, in situations like pandemics, when the biologics are the only recourse for populations. How does one work through these dilemmas?

It is difficult to not be dazzled by these possibilities. Who wouldn’t long for progress that can replace a child’s defective heart or kidney or eye, and make a compromised life whole again?

But as with virtually all progress, developments raise profound conflicts between what we want and what we can afford. In a system being crushed by cost – while the average American family’s health care costs $14,500 in 2007, one third of households make less than $35,000 – where do we invest and how should investors be rewarded? Is there a reasonable limit to the price of even great progress?

One thing was clear. The advances that have made these miracles possible will continue to accelerate and become less expensive, making the technologies that are now available but out of reach accessible as well.

A Rage To Know: A Few Days At The Aspen Health Forum

At one of the opening sessions of the Aspen Health Forum, Peter Agre and Michael Bishop, both physician researchers and Nobel laureates, recounted their childhoods, their families, their likes and dislikes, their school experiences, and the barriers, successes and lucky breaks that led them into lives of discovery. Dr. Agre won the award for identifying the mechanisms that allow water to cross the cell membrane. Dr. Bishop won for discovering how certain defects in genes can lead to cancer.

Those of us in the audience were struck by the commonness and good humor of their stories, but also by these individuals’ profound humility and, most of all, their passion. What Neen Hunt, Director of the Lasker Foundation, the third speaker on that panel, in her description of Dr. Charles Kelman, an ophthalmologist who revolutionized the way cataract surgeries are performed (more on that in another post), called “a rage to know.”

You could hear the same dedicated, focused passion in many of the senior attendees. There was Sir Roy Calne, Professor of Surgery Emeritus at Cambridge, a pioneering giant of organ transplantation, who at the end of his presentation gave special thanks to the organ donors. An exhibition of Dr. Calne’s paintings overwhelmingly conveyed the gravity and humanity of surgery.

The tone was in Tony Fauci’s presentation as well. Dr. Fauci is Director of the National Institutes of Health’s Institute of Allergy and Infectious Diseases, the leader of the US’ Global HIV/AIDS program, and was just awarded the Lasker Foundation’s 2007 Public Service Award for his contributions as architect of two major governmental programs, one on HIV/AIDS and the other on bio-defense.
He explained why AIDS explosive growth now demands greater attention to and resources for prevention. More than 20 million have died worldwide so far, and 60 million more now have HIV/AIDS. For every patient who receives anti-retroviral therapy, six more become infected.

Dr. Fauci was joined on that panel by Mary Robinson, President of Realizing Rights: The Ethical Globalization Initiative (the Aspen Institute is an institutional partner on that effort). Ms. Robinson was Ireland’s first woman President (1990-1997), and then UN High Commissioner of Human Rights (1997-2002). Ms. Robinson's compelling, articulate voice called for helping women gain control of their own sexual and life choices, which play enormous roles in the complex of this monstrous disease.

You arrive at the Aspen Institute not knowing quite what to expect. You know it is special, an international force in bringing together thought leaders from every area of human endeavor. And it is certainly beautiful, with the mountains rising around the campus, punctuated in autumn by yellow and orange.

But the true pleasure of the Health Forum was listening to and talking with this collection of extraordinary scientists, physicians, philanthropists, economists, business leaders, venture capitalists and policy experts, who have come together for no other purpose than to share and to learn. There are 28 and 78 year olds, people at the end and beginning of their careers, but no sense of caste or clannishness.
You walk into every meeting aware that everyone has something interesting to say, that they are informed, thoughtful, deliberate and focused on translating idea to action. There is a tacit understanding that, in their rage to know and do, they are most passionate about achieving something larger than themselves.

The Aspen Institute is a critical mass of extraordinary exchange. A few days of that make it an honor and an indelible experience, with the capacity to energize and facilitate meaningful change once we have returned home and to our daily work

A Broad Vision of Health 2.0: Reformulating Data for Transparency, Decision Support & Revitalized Health Care Markets

By Brian Klepper and Jane Sarashon-Kahn

What follows is a verbal rendering of a powerpoint presentation Health2.0-1011.ppt which contains graphics necessary for full understanding of Health 2.0’s complexities. Basically the graphics show PHR, EHR, health management, and vendor management data being dumped into a data repository were the combined is analyzed by sophisticated algorithms and analytic techniques.

The term Health 2.0 refers to the concept, described by O’Reilly in September of 2005, of Web-based platforms that allow users to reformulate data for their own purposes. The Health 2.0 movement is rapidly gaining steam and traction, propelled by established and startup firms. The efforts displayed at the recent Health 2.0 meeting in San Francisco, convened by Matthew Holt and Indu Sabaiya, were both wide-ranging and narrowly focused. Even so, several end-of-day panelists noted that, at this early stage, Health 2.0’s definitions and translations into practice remain murky and fragmented.

We thought it might be useful to try to develop an image of how Health 2.0 MIGHT develop: what its working parts were, what kinds of information it would receive and generate, who its users would be and what its impacts might be. The image that has resulted is simplistic; it doesn't try to explore any of the underlying mechanisms necessary to pull this off. But it does try to convey a vision of how innovators might come together to aggregate and reformulate large data sets from disparate sources to create tremendous new utility in the marketplace for patients, clinicians and purchasers of all types.

We are posting this image on the various sites where we write – others are welcome to post it as well – as an exercise. Where is the structure wrong? What are we missing? How can this be made clearer, stronger, more faithful to our best hopes for where health information management might take us? Let us hear from you, and we'll update the image as we collectively think through the issues involved.

One caveat. Please note that we have not included back-office operational functions. While it is entirely possible that these too will ultimately be managed through Web-based processes, they are by definition the most proprietary business management tools and therefore the least susceptible to sharing.

The Electronic Health Record (EHR) is the hub of patient management within the clinical setting, and should be understood here to be not only an expansive repository of patient information (ultimately with room for gene maps, family histories and information about alternative care maps), but a complex of tools that includes clinical decision support, health plan rules, product/service pricing, and so on.

The Patient Health Record (PHR) is a lay reflection of the more robust EHR, with linkage to tools that are aimed at the consumer’s self-management, including guidance on when to seek professional expertise.
Analytics are applied to the data in the data repository to reveal patterns, to evaluate patients’ health status, and to identify the desirability of different clinical and vendor choices. For example, the:

• Relative pricing and performance within and across regions of physicians by specialty, and hospitals by services,

• Relative pricing and performance of drugs and devices within class and by vendor.

• Identification of patients with specific risks.

• Identification of more or less effective diagnostic and treatment pathways.

There are several well-accepted, widely-used analytical classification and risk adjustment tools in the market, e.g.: ETGs, CRGs and DxCGs. These algorithms permit unbiased comparisons among providers, patients and treatments and facilitate identification of patients at risk, as well continuous updating of clinical and administrative best practice.

These tools allow decision-makers of all types to evaluate professionals, organizations, products and services in the marketplace. So it is critical that all health care stakeholders find the analytical processes trustworthy, credible and open to scrutiny. This is why it is so important that the methods used to achieve transparency be transparent as well.

Now comes the first result of the analyses, Identifying Patients At Risk. These might be patients identified with chronic conditions; they could also be patients with signs or symptoms predicting genetic anomalies or acute conditions. Information about the patients identified during this process would be forwarded to their EHRs and PHRs, as well as to the Health Management tools, so they can be contacted and, possibly, receive health interventions.

By receiving a continuous flow of data, by constantly watching for best clinical and financial outcomes for specific conditions and purchasing processes, and by working “backwards” to identify the common pathways that led to those outcomes, the analytical tools could presumably identify Best Practice Guidelines. These, in turn, could be passed along to and embedded in the EHRs, Health Management and Vendor Management tools, each in formats that make sense to the tools' different users. This becomes a continuous improvement process.

The third major result of the analytics, Pricing/Performance Transparency compares the relative pricing and performance of four major health care product/service classes: Providers, Payers, Products (Drugs, Devices, Equipment and Supplies), and Interventions/Treatments.

The information produced by the Pricing/Performance Transparency functions are distributed into two ways. First, they become readily available to stakeholders of all types through Public Reports, distributed by the host or by any other public or private group, and made available through the tools to purchasers, health managers, clinicians and patients. Again, to be credible, public reporters must be scrupulous and transparent in their evaluation methodologies.

The findings of the various Pricing/Performance analytics can also flow into constantly updated Decision-Support Tools, which are adapted to the needs of purchasers, health managers, clinicians and patients.

Decision Support is also informed by input from Expert Content – e.g., current knowledge on efficacy and value from the health care literature, medical encyclopedias, and best practice guidelines.

Finally, the PHR and patient decision-making are enhanced by User-Generated Content, guidance from patients and caregivers who have dealt with the condition in question, information about health or treatments that might not be contained in the current record, individualized search results, and other relevant information.

It is not difficult to imagine that, as these various functions come together and are integrated into continuously refined applications, the impacts on the health care marketplace could be profound. The inability to see and know the results of health care processes has created an opportunistic culture that pervades every part of the continuum. The unprecedented transparency that will result from these, as well as the decision-support capabilities for patients, clinicians, health managers and purchasers, should go far in finally helping health care begin to adhere to the same rules that govern other markets. When stakeholders can make informed decisions, based on solid data, the impacts on cost and quality could be transformational.
Some key questions remain. Does this model represent what is possible and likely to occur? Can the organizations working to integrate these functionalities access the data required, and will they be capable of developing or acquiring the various processing elements incrementally? Will certain stakeholders, knowingly or tacitly, work against the ultimate objectives of this model?

We’re optimistic, but time will tell.

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