Is Data the Cure-All?
Lessons From Health Care for Education Policymakers
Kaiser Permanente’s 8.7 million members no longer gather up reams of old paper charts and prescription records when meeting with a new doctor. Instead, each of the health-care giant’s 14,000 physicians can instantly access patients’ electronic medical records—up-to-date digital archives of a patient’s medical history, complete with medications, vaccinations, and important safety information, such as allergies and any known reactions to medicine. This allows for greater convenience, but also for information-sharing across a multiplicity of doctors, nurses, specialists, and pharmacists.
Kaiser Permanente is one of the shining examples cited in the campaign to use information technology and better data to radically reform and improve health care. Increasingly, physicians and policymakers see information technology as an essential tool in controlling medical costs and improving the quality of care.
Electronic medical records, for example, hold the promise of eliminating redundant procedures, reducing errors, and improving the coordination of care among health providers. They also allow patients to actively manage and contribute to their own health and wellness, with automatic reminders for routine screenings and other prevention-oriented activities. And when aggregated across hundreds of thousands of patients, this electronic data provides a rich resource for researchers to identify treatments more rapidly and conduct clinical trials across a wide variety of demographic groups and settings. Tens of billions of dollars in federal economic-stimulus funds are headed toward these efforts.
In education, the rhetoric around the promise of better data is equally compelling. With better data, policymakers can identify effective schools and educators, expose problems, make better decisions about the allocation of resources, and build political will for reform. At the classroom level, better data will inform instruction—enabling teachers to better understand what approaches work for specific students—and lead to better teaching and improved learning. And, as in health care, federal stimulus money—in this case $245 million—has been allocated for this purpose alone. This is on top of the billion-plus education dollars already spent building state longitudinal databases and districtwide data warehouses.
But what health reformers are learning is that using technology to transform a complex, fragmented, change-resistant, and costly system like health care—or education, for that matter—is not an easy task. More importantly, they’ve learned that electronic data systems will not improve health care, education, or any field on their own. Health reformers also understand that the nation’s investments in data systems will be for naught unless they lead to meaningful improvements in outcomes. As education accelerates its drive to utilize data, there’s much to learn from health care.
At Kaiser Permanente, for example, the move to electronic records is significant, yet change has been slow, expensive, and wrenching. BusinessWeek notes that Kaiser “has spent $4 billion and encountered disgruntled doctors, system outages, and a temporary decrease in productivity as physicians get accustomed to the new system.” And Kaiser has it easy. It’s a closed system in which members get a range of integrated services, from preventive medicine and primary care to surgery and hospitalization, all from the same provider. Since its primary focus is on individual members, and the costs are internalized, Kaiser has an incentive to build more-seamless, patient-centered information systems. In contrast, most medical providers are smaller and more fragmented, focused on a particular specialty or service.
Even among hospitals, the move to adopt electronic records is slow. In fact, a recent New England Journal of Medicine survey found that “only 1.5 percent of U.S. hospitals have a comprehensive electronic-records system (i.e. present in all clinical units), and an additional 7.6 percent have a basic system.”
Moreover, evidence from Kaiser and a number of other leading health providers shows that better technology and better data, while essential, are just the underlying infrastructure for more-substantive transformations. Health reformers have learned that unless these systems are useful for and change the work flow, incentives, and actual day-to-day practices of doctors, nurses, labs, and other parts of the system, they will not improve patient outcomes.
For example, officials at Central Pennsylvania’s Geisinger Health System, another of the shining examples in the effort to improve quality and control health-care costs, quickly realized that the capability to share data across a variety of systems and contexts was not enough to improve its quality of care. What was needed was a cultural change among its employees—specifically, a shift from isolated and task-focused work to aligned, interconnected processes.
Everybody involved with a patient needed not only to have access to that patient’s medical information, but also to have clear understanding and agreement on what each stakeholder was responsible for and what each got paid for. This was essential to tapping the potential of better data. And the design of Geisinger’s data system had to take into account and accommodate this broad change.
Health reformers have also learned that the larger goals, such as better patient outcomes, must drive the data systems—not the individual provider or institutional needs. This would certainly hold true for education as well. Systems driven by institutional needs, such as billing or compliance in health care, aren’t designed to provide information that is useful for changes in day-to-day practice. Nor can they reflect a comprehensive picture of patient (or student) needs across a variety of institutions or programs. The average Medicare patient has 14 different physicians. There’s no way to coordinate care across these providers unless data systems are centered around the individual patient. Likewise, with increasingly mobile student populations, education data must be learner-centered.
Across both health care and education, experts emphatically say that the building of systems and technologies, while expensive and sometimes difficult, is not the critical challenge. Whether these systems can enable many of the most important changes necessary for better outcomes—in both health and education—is wholly dependent on the extent to which they are developed and implemented with the larger goals in mind: using evidence to inform practice, coordinating care or instruction across multiple individuals and providers, enabling rapid and continuous learning, and producing an alignment of incentives centered on patients or students.
The most forward-thinking reformers—in health care, education, and many other fields—understand that data is most powerful when used not just to automate current systems, but to provide a critical catalyst and tool for transforming the way that systems work.
Vol. 29, Issue 27, Pages 24-25