In the midst of the big data, open data and transparency revolutions, ideas around data consumption and usability are those that should be (but often are not) discussed as part of these modernizations. In health care, information usability is perhaps most critical; the fact that we’re making decisions regarding human life is in itself a reason to better use our data. Not to mention the exorbitant health care spending in the US. However, usability of data has traditionally been less advanced in health care compared to other fields. The good news? Visual analytics is changing that.
Visual analytics is an integrated approach that combines visualization, human factors and data analysis (see Visual analytics: Scope and challenges). The goal is to allow users to draw conclusions from data by representing information through human-centered, intuitive visualizations. It’s much more than what meets the eye, though. Behind the scenes, it’s the work of advanced analytics that prepare and organize massive amounts of data so that users can make sense of hundreds of thousands of variables. It’s what makes visual interaction with big data possible so that users can pose known questions to the data, and also explore the data for the unknown.
So what does that mean for health care? It’s quite transformational and can reinvent the way stakeholders of the health care system, including consumers, payers, providers, researchers, and employers, make health care decisions. More specifically, it can transform the way service delivery, public health and personal health is approached. In this first of two parts, I'll talk about service delivery...
New delivery models introduced by the US ACA, such as accountable care and patient-centered medical homes, rely heavily on data and analytics to fulfill the goal of improved, coordinated care. As a result, new users of data such as primary care physicians, specialists, hospital administrators and care managers, need to access and utilize large databases of claims, EHRs and more. Unfortunately, for the first crop of Medicare ACOs, a recent survey by NAACOS found that learning to access and process data has been a significant challenge. More specifically, ACOs have been challenged with finding suitable software, building new skill sets to analyze data, and translating data into useful information for care managers and providers.
Visual analytics addresses each of these challenges and completely changes the way ACOs can approach data. It can give these users the unique population health insights they need from data – such as performance measures, trends, costs and outcomes– across multiple sites of care. Moreover, it provides these insights in a consumable format that can improve decision-making at the patient-level. This is not only a huge advancement for provider efficiency, but a game changer in making the ACO model successful. For example, the state of New Hampshire uses SAS® Visual Analytics in conjunction with the state’s all-payer claims database (APCD) to allow ACOs to dynamically view data and critical measures on their populations’ health. Through a Web-based portal, ACOs in NH will soon be able to use visualization and interactive reports to better coordinate care, replacing monthly documents of over 800-pages!
By making visual analytics an essential component of their IT infrastructure, ACOs will gain measurable success even faster. In fact, visual analytics spans well beyond ACOs, and provides benefits across the entire health care ecosystem. Next week I'll share how visual analytics can improve public health and personal health programs in Part 2 of this series.
Schedule a demo session at SAS booth #935 at HIMSS in Orlando, or just stop by to learn more about visual analytics for health care.