ADVANCES in information technology have made it possible for predictive tools to access and manipulate Big Data, and to do so continuously—opening up opportunities to anticipate issues with unprecedented precision. No industry is unaffected. But nowhere is the potential more exciting than in health care.
Predictive analytics is fueling a transformation from a focus on the volume of procedures to the value of outcomes. For example, predictive tools can pinpoint treatments that sustain health in a more precise way than ever before.
Used to its full potential, this approach is predictive medicine—the ability to integrate and analyze known disease characteristics with a specific patient’s history and health status, and use the resulting insights to change outcomes and inform new directions for life sciences research and development.
In this new arena, the once-clear lines between companies that make drugs and medical devices, providers who diagnosis illnesses and treat patients, and payers who provide the financial support for care are blurring. Actors in this ecosystem are establishing more iterative and interactive connections with each other and with patients.
They are collaborating with (sometimes highly unlikely) partners. They’re also sharing risk.
For example, one estimate of the annual cost of medication noncompliance in the United States is a hefty $289 billion.
What if a pharmaceutical company took the lead in creating a collaborative solution, using predictive analytics to assemble and deliver a package of product and service offerings to motivate patients to stay on track? With a focus on adhering to treatment, patients, providers, risk bearers and life science companies would all benefit.
Medical device companies have begun using predictive analytics and other Big Data technologies in certain areas of their businesses. Leading pharmaceutical companies are also investing and establishing operations in advanced analytics. Life science company executives need to think about how—and how much—they will develop and integrate predictive analytics capabilities into their services.
While the most visible immediate benefit is cost reduction, the real motivation is a patient-centric business model—one that recognizes that health and care management needs to occur wherever the patient is, not just in hospitals or physician offices.
The goal is threefold: Improve clinical outcomes, enhance patient satisfaction and drive more value to the entire health-care system. ( Jeff Elton & Arda Ural )
Jeff Elton is managing director in Accenture Strategy and Global Lead of Predictive Health Intelligence. Arda Ural is senior manager in Accenture Strategy and Predictive Health Intelligence.