Laurel Borowski, MPH
Solutions Director, Streamline Health, Inc.
While some may consider clinical analytics a relatively new discipline, members of academic research centers have been focusing on it for decades. Researchers have used clinical analytics to study various aspects of public health to learn about epidemiology, trends around certain conditions, etc. One key element of clinical analytics is comparative effectiveness research (CER) or outcomes research, which provides evidence on the effectiveness, benefits, and/or potential harms of different treatment options.
As we move into the era of value-based care, we’re learning that a substantial portion of U.S healthcare spending is for services with unclear clinical effectiveness. Patterns of care across communities, specialties and practices vary widely, which makes it hard to discern the connection between the specific care being delivered and the outcome it achieved. Another obstacle is the lack of current, evidenced-based insight into what care options might be most effective for key patient populations. Providers have their own insight and experience to draw from, but what about enterprise-wide (or regional, or national) results for the most effective treatment(s) for any given condition or patient population?
The widespread implementation of EHRs is providing rich clinical data for analytics. The current challenge is to access the information in ways that providers can understand and then analyzing it in a manner that yields actionable insights to drive patient care improvements. The first step is to make information accessible and meaningful to providers on the front lines, as this would allow them to find patients and compare treatment outcomes for their own patient populations. If someone sees a lot of elderly patients with multiple comorbid conditions, each care encounter produces clinical information that could be factored into analytics that can drive CER on caring for elderly patients with these specific conditions (also known as a cohort). The insight provided could enable the provider to establish evidence-based best practices—quickly and easily— to tailor care plans accordingly. And data captured from each subsequent visit (positive or negative outcomes, improved test results, care or time lapses that may contribute to preventable issues, etc.) can help further refine the care planning, recommended therapies, interventions, etc. around this cohort.
This type of analysis is what public health researchers do all the time; we just need to empower individual providers with the tools to conduct their own CER. By compiling their own patient cohorts, providers can document treatments delivered, outcomes achieved, etc., which then creates baseline readings against which subsequent adjustments can be gauged. If substantial improvements are realized, this can then be shared with other providers to implement accordingly, and further analysis can either confirm or refute the effectiveness of the recommended adjustment. And this is the essence of healthcare reform and value-based care: getting better results, and improving patient health, more quickly and efficiently.