Using big data to benefit veterans

The Veterans Health Administration represents a vast health care entity that stretches across all 50 states, the Caribbean and the Pacific Rim. It employs 275,000 clinicians and administrative professionals who serve 8.2 million enrollees at 152 medical centers, 827 community-based outpatient clinics, 300 veteran centers (including 70 mobile centers) and 127 community living centers.

It is critical for an organization of that size to change with the times, and the times are definitely changing with respect to health care. Indeed, the volume-based care model -- which pays physicians based on how many patients they treat and how many tests, treatments and procedures they prescribe -- is on the way out.

Dr. Robert Jesse, principal deputy undersecretary for health at the Department of Veterans Affairs, has declared that volume-based care is being replaced by value-based care, in which patient outcomes, costs of treatment and quality of treatment (i.e., treatment value) determine payments and reimbursements.

Medical facilities and providers across the United States are responding to changing priorities with team-based care models and tools such as provider-, patient- and systems-facing health management platforms, telehealth and remote monitoring, and mobile applications that generate the volumes of data required to compete in this new environment.

Yet although nearly all the CIO respondents in a recent survey said they believe data analytics will play a big role in the future success of accountable care and other value-based initiatives, most reported only moderate or minimal commitment to integrating data analytics into practice.

Why is that the case? It's a question worth asking, because when it comes to big data in health care, there's no shortage of supply. Most health care organizations today, public and private alike, have little trouble capturing enough data. Instead, the big challenge facing today's health care providers -- from general practitioners to clinicians in radiology, oncology, surgery and other specialties -- remains how to leverage all the data to effectively improve workflows, patient care and financial stewardship regardless of care setting.

And although there's no single solution to managing data for enhanced outcomes in every health care setting or circumstance, there are proactive strategies and solutions federal health care organizations can implement.

Generally speaking, the most effective solutions and strategies consist of three primary characteristics:

* Begin with the end in mind. What serves as one of Stephen Covey's seven habits of highly effective people is also a useful strategy for using the power of big data to address patient challenges. Many providers in both the public and private sectors struggle to tame and make effective use of the flood of data their systems are capable of collecting. That is actually a strategic planning issue.

The solution is to first identify the problem you need to solve and the right questions to ask. You are then more effectively positioned to identify and collect the data most relevant to helping pinpoint the solutions. In radiology, for example, big data can be used to help identify the appropriateness of various imaging modalities in different clinical circumstances. Reimbursement practices for duplicate images are changing, so using data in this way is more important than ever.

* Work in real time to make the work easier. This approach reflects two guiding principles for using big data included in Jesse's presentation at the 9th Annual World Health Care Congress. The first principle is to acquire all data needed to manage patients during the actual treatment or work processes, not afterward through retrospective data collection. The second, which nearly goes without saying, is that the solution must make work easier and not impose undue burden or require rework.

Indeed, solutions are becoming widely available that enable clinicians to collect patient data in real time through the course of treatment. This is particularly true in the perioperative suites of VA medical centers, where solutions are being used to ensure that surgical safety checklists and other measures are performed for every procedure, enabling clinicians to track procedure times and other metrics and permitting post-procedure analyses to identify and correct performance issues.

* Foster interoperability. Solution interoperability is emerging as a third major characteristic of successful health care delivery in the private, public and federal sectors -- and not just as it applies to communication between or among facilities. The ability for departments within facilities -- such as radiology and cardiology, or orthopedics and accounting -- to exchange patient care and billing data is becoming increasingly important to the efficiency of organizational workflows at VA facilities.

Solutions that facilitate those capabilities are available, and the most effective ones will enable clinicians to convert much of what works with manual and paper-based practices to the electronic realm. For example, in its transition to a new electronic system for managing chemotherapy treatment, a VA facility in Michigan has been able to retain provisions for six clinician signoffs to ensure the accuracy and safety of chemotherapy treatments.

Much of health care as a whole still has far to go before it can fully realize the promise of big data to transform patient care and treatment. We remain in the early stages of figuring out what big data can and cannot do for providers and their patients. But proactive strategies like those delineated here can be used by every medical specialty, from obstetrics to geriatric medicine, and they also have the power to go a long way toward helping the VA and other federal health care agencies make significant progress toward using big data to improve patient care.