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Where the Rx Meets the Bottom Line February 2007
Your daughter is hard of hearing. A doctor examines her and orders a computed axial tomography (CAT) scan, which would uncover any inner ear malformation contributing to her deafness. The problem is, a CAT scan was performed several weeks ago by another physician and didn't locate the problem—something the second doctor doesn't know. But what if he or she can find out that information easily? What if a computer search could turn up your child's medical history and, instead of a CAT scan, the doctor orders an MRI—which could reveal, among other things, a brain lesion? Better yet, what if the doctor could call up records comparing the effectiveness of certain treatments, match that data with your child's records, and order an MRI at the outset? Technology that will enable this could be available in just a few years—and offers the promise of making the complex and costly American healthcare system (currently 15 percent of the nation's gross domestic product) more effective and less expensive. But how can healthcare planners know what kind of new technologies will be available, how many people they will have to serve, or how much they might cost? How can those working on public health issues better understand the impact of such technologies and make sure their plans are both affordable and effective? A team from MITRE's Center for Enterprise Modernization, which works with the federal government's civil agencies, is trying to find out. Can Better Service Cost Less? The team is conducting a year-long case study of the country's large-scale public health programs. The team wants to find a way to collect realistic data on which the costs and societal impacts of measures to enhance public health can be based. The hoped-for results: a better quality of service, fewer errors, and better decision making that will slow the stratospheric increase in healthcare costs. "It's really connecting an engineering technology perspective with the economic perspective that some economists and social scientists have on how the national economy works," says Kenneth Hoffman, a MITRE senior principal information systems engineer who is leading the case study. A large part of MITRE's mission involves assessing technologies and their potential nationwide impact. But federal policies often keep new services from becoming available at the local level—sometimes for budgetary reasons, sometimes because of fear that new technologies may lead to fraud. "There's a technological revolution, and, at the same time, a severe societal climate and economic constraints on the system," he says. "How do we reconcile those? That's the challenge that we're trying to get at." Toward "Lean Healthcare" One possible answer currently gaining support in healthcare circles is "lean healthcare." The idea is that hospitals and physicians' practices are all part of an assembly line of sorts that should deliver healthcare services seamlessly. The thinking goes: By streamlining the entire process, healthcare professionals can clear away many of the clogs that slow the delivery of services, thereby improving the quality of care and acting as a brake on spiraling costs. "We would like to model these lean healthcare environments and play those into these long-term financial models and show the real value of lean healthcare," Hoffman says. Much of the push for new healthcare technology comes from the federal government. The Department of Defense and the Veterans Administration are already mandated by law to maintain electronic health records for soldiers and their families and retired beneficiaries. Moreover, President Bush has set a target date of 2012 for making electronic health records available for every American citizen. But that will not be easy. Most private providers still maintain their records on paper. With a cost of $150,000 per provider to convert to new technology, e-records are currently too expensive for many small practices. These physicians need to be convinced that advances in technology will be beneficial to their patients and the ongoing viability of their practices. That's one of the areas where MITRE comes in. The MITRE team is developing a model designed to trace a patient's path through a set of healthcare services providers offer, such as diagnostic, laboratory, and imaging tests; referrals/consultations to other providers; and in-patient treatment (to name a few). Working with researchers at the University of Maryland and Harvard, the team completed a plan to enhance the model and gather clinical data in future research efforts. In addition, the MITRE team has presented the model to others in the healthcare community. One such briefing was presented at the annual American Public Health Association Conference, held last November in Boston. Hard Data, Informed Choices The information the model will collect could help overcome some of the main obstacles to bringing advances in healthcare technology to the market. One example is the adoption of electronic health records. Without incentives for private physicians to buy the technology powering e-records, many doctors might be reluctant to start using them. The model could demonstrate some reasons for implementing a change, such as providing data that analyzes the cost and effectiveness of different kinds of services. "We're trying to build this model in a general way, but then we can define specific parameters that characterize the patient and the illness and the treatment," Hoffman says. "The reason is that we believe that will capture the benefits of using electronic health records. So, for instance, when you do a referral, you don't have to repeat all the tests. The results are captured and available in electronic form to the referred physician." The greater information sharing and reduced duplication of effort stemming from e-records should help providers see the value in switching from paper. Sorting Fact from Fraud Harder and more detailed treatment data may also help assuage concerns that electronic health capability could be too easily abused. For instance, there are limits to what insurance companies and the Centers for Medicare & Medicaid Services (CMS) will reimburse. Currently, reimbursements are based on levels of care for traditional healthcare methods like office visits or hospital stays, not for newer methods such as telemedicine (the delivery of health services over the phone or via computer). Moreover, CMS's Pay for Performance initiative means providers seeking reimbursements must submit information on the outcomes of their treatments, thus directly tying level of reimbursement to the quality of care the patient receives. These restrictions present a challenge for advocates of lean healthcare. Newer methods might help streamline the treatment process, a goal that lies at the heart of the lean care concept. But what level of performance will be needed to satisfy the CMS? And what safeguards can be put into effect against fraudulent claims for services? "Technology is evolving so quickly that it is unclear if reimbursement regulations and stipulations can keep pace with these new services," says Carolyn Padovano, MITRE's chief of clinical informatics and an expert in public health. "This particular model will be able to determine what type of service offers the highest quality care and is the most cost-effective for an insurer to reimburse on. Reliable Data Feeds the Model "To actually drive policy, you need this detailed level of information to support reimbursements for new treatments," she adds. "Because MITRE interacts with healthcare agencies, as a federally funded research and development center, our ability to advise people as to what treatments and services they should reimburse must be supported by reliable and valid data." The developers of the MITRE model concede it may not cover all the factors driving healthcare costs. But they believe it will cover the majority of them—enough to bring the healthcare community closer to a more realistic way of balancing the two ends of holding down costs and improving the quality of care. The two outcomes may seem at odds to some, but the MITRE team thinks it's possible. "We can put technologies in, begin to bounce technology opportunies against financial constraints and the economic models against policy constraints," says Hoffman. "We're working on a blend of analytical models that will help put in some sense and more reality than is currently used in some projections." —by Russell Woolard Related Information Articles and News
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