There are few areas of science sexier than personalized medicine. The predictive potential of diving deep into our DNA has been featured everywhere from GQ and Oprah to The New York Times Magazine. Young adults hold “spit parties” to gather saliva samples for genetic analysis, while a gray-haired Alan Alda does much the same thing by expectorating and narrating during a public television special. Meanwhile, Dr. Francis S. Collins, the man who directed the sequencing of the human genome, was recently appointed director of the National Institutes of Health.
At the other extreme of the spectrum, there are few subjects more somnolent than supply-chain management. Yet those trying to incorporate personalized medicine into everyday medical care face a dilemma straight out of supply-chain school: Genetic-based diagnoses and therapies do not fit easily into what doctors were trained to do, how they do it or how they eventually get paid. Sending a sealed envelope full of saliva to a lab in California says nothing about how (or if) you integrate the results into treating cancer in Cleveland.
In response, a host of organizations have literally begun inventing the infrastructure necessary to enable doctors and hospitals to easily order genetic tests and therapies, apply the results clinically and then get reimbursed.
That’s not as easy as it might sound. Genetic data uses very different information than traditional physiological indicators such as blood pressure or tumor pathology. Sandy Aronson, who oversees information technology at the Partners HealthCare Center for Personalized Genetic Medicine, part of a health system formed by two Harvard teaching hospitals, says his clinicians must manually enter the information so that it can be used in a clinical decision database at the hospitals. Partners cannot electronically transmit or receive the results of molecular medicine testing done by outside laboratories and so can’t readily use or analyze those results.
“Without a data network, you can’t have a knowledge network,” Aronson said during a recent personalized medicine conference sponsored by Partners and the Harvard medical and business schools. “It increases our costs and leaves clinical value on the table.” In response, Partners, a Harvard teaching affiliate, is collaborating with other leading health systems to build the needed interface. Once this is done, physicians won’t just know that, say, a lung-cancer patient has a problem metabolizing a particular type of drug; they’ll be able to utilize the underlying genetic information to find the treatment most likely to be most effective.
Scientists call these molecular-level indicators of the body’s therapeutic responses “biomarkers.” In a society that relentlessly promotes personalization in everything from purses to pickup trucks, this is perhaps the ultimate personalization: individualized medical care at the molecular level.
Still, fitting this new personalized medicine model into current medical practice requires some adjustment. As an analogy, imagine the sudden advent of airlines in a country where public travel is booked only by travel agencies and only by bus and train. Although travel agents might be intrigued by the speed and convenience of travel promised by airplanes, they’d have no systems in place to write or sell tickets to fly. In fact, they wouldn’t even be sure when their customers should take the train and when an airline ticket was a better value.
Those kinds of basic “How do we get there from here?” issues are what doctors, hospitals and payers are grappling with in regard to using personalized medicine. So, for instance, San Francisco-based DNA Direct has established a national call center of genetic counselors and launched a Web-based decision tool to help patients, physicians and insurers understand which genetic tests and therapies are appropriate in what circumstances, and how to interpret the results.
El Camino Hospital in nearby Mountain View is using DNA Direct’s decision support services in an effort to integrate personalized medicine into the ordinary medical “supply chain.” Jon Friedenberg, who heads El Camino’s new Genomic Medicine Institute, cites the case of a young breast cancer patient who wanted to know whether she should be tested for the BRCA1 and BRCA2 genes that signal increased breast cancer risk. Those with the gene, concerned about cancer recurrence, are more likely to choose a mastectomy as treatment. The woman’s doctor referred her to the institute, which quickly connected her to a DNA Direct board-certified genetic counselor. The patient had the test, it came back negative and she chose to have a lumpectomy, rather than the more invasive surgery.
At the end of 2009, El Camino used DNA Direct to provide 30 different tests related to conditions that are relatively common (Crohn’s disease), rare (spinal muscular atrophy) or connected to a particular ethnic group (screening for diseases more prevalent among Ashkenazi Jews). Meanwhile, as the number of medications and tests linked to genetic indicators increases, traditional supply-chain managers are adapting their tools. Pharmacy benefits managers like Medco and CVS Caremark are altering their databases so that ordering a genetic-based test will trigger the same kind of computerized analysis — whether the test is appropriate for a particular condition, for example, or whether it is approved for reimbursement by the patient’s health plan — applied with traditional diagnostics.
CVS Caremark turned for assistance to a company called Generation Health that was established specifically to manage genetics-related tests and treatments. The Upper Saddle River, N.J., startup unabashedly focuses on classic supply-chain functions: cost-benefit analysis of different products, building a transaction platform to facilitate ordering, billing and oversight, and educating end users.
Just six weeks after announcing the partnership, CVS Caremark abruptly bought a majority share of Generation Health and made that firm’s CEO head of CVS Caremark’s entire pharmacy benefits manager operations. In doing so, CVS Caremark said it was “accelerating our commitment to personalized medicine and making genomic benefit management an integral part of our PBM offering.”
Similarly, McKesson, the giant pharmaceuticals distributor, is creating electronic guidelines that help physicians understand when to order genetic tests, unique billing codes for tests that don’t fit into the current system and an electronic database that tracks which health plans pay for what DNA testing. As a next step, McKesson plans to make the catalog of genetic tests available to consumers online. Large employers, health plans and the federal government are conducting similar reviews of their coverage policies. “We need to integrate [personalized medicine] into current processes,” says Douglas J. Moeller, medical director of claims performance at McKesson Health Solutions.
Integration doesn’t mean rubber-stamping every test or therapy touted as “personalized.” “Your technologies have to replace something or provide such an increase in health value that they’re worth the money,” Lee Newcomer, senior vice president of oncology at UnitedHealthcare, cautions. “We need to be able to have more affordable health care.”
Not every DNA test will be able to jump that hurdle. For example, many clinicians doubt whether analyzing a patient’s ability to metabolize the common anti-clotting medication warfarin (Coumadin) provides any value, since doctors must calibrate dosages based on how an individual reacts over time.
Genetic medicine today is used mostly in a diagnostic capability; that is, for finding a few specific diseases, such as cystic fibrosis, or for predicting a broader disease risk, such as the BRCA1/2 link to breast cancer. Therapeutic usages, such as selecting a particular drug or dosage based on a DNA test, are less common. Nonetheless, there are more than 200 Food and Drug Administration-approved drug package inserts that recommend a genetic test be used either to select patients or to find the right dosage of a drug. Use of biomarkers to apply those guidelines to individual patients is gradually becoming commonplace.
In a highly publicized example of biomarker analysis, the FDA in late 2009 warned doctors about using the $8 billion-a-year anti-clotting drug Plavix in concert with 11 different heartburn medications. Those medications, including the popular drug Prilosec, can block a specific enzyme in the body that is crucial to breaking down Plavix and allowing it to be effective in reducing the risk of heart attack or stroke.
Of course, building a supply-chain infrastructure does no good without a demand for what is being supplied. The Genetic Information Nondiscrimination Act is expected to make patients and doctors alike more comfortable having genetic information become a normal part of the medical record since it bans health insurers from using genetic factors to set rates or deny coverage. It also prohibits employers from using genetic factors in hiring or firing decisions.
By making personalized medicine more routine, supply-chain managers are moving the technology from research marvel to mundane diagnostic and therapeutic option. That accomplishment is not as sexy as magazine covers and talk show appearances, but it’s not an accomplishment to spit at.
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