At a time of unprecedented financial challenges – from payment shifts and regulatory mandates to aging populations – our nation’s hospitals are awash in data. Clearly, there is a need for analytics capabilities to make health care more efficient, cost-effective and satisfying to patients and providers alike.
In the October 2017 issue of Population Health News, I shared my ideas on how best to design population health management tools to address high-risk populations. I wanted to re-share those ideas here, where I can also expand them and hopefully encourage some discussion.
Regardless of the approach, the effectiveness of any population health management (PHM) strategy ultimately hinges on an organization's ability to manage data. The volume of available health data has become a deluge that healthcare leaders and practitioners alike find overwhelming. This data must be governed, managed and harnessed to inform clinical and business decisions in an increasingly complicated environment. How to do that, and what tools to use, remains elusive to many organizations.
In designing tools to improve the health of populations, the operative word is analytics – not just fancy reporting but analytics sufficient to allow modeling and predictive capability. Of course, basic reporting capability is assumed for an organization to remain viable. But to get to the next level, healthcare organizations must build a stronger foundation. This includes:
- Effective data management, allowing aggregation of data from all possible sources into a form that enables rapid and unfettered exploration (within the bounds of privacy regulation). This has traditionally been a challenge because data tend to be messy and come in many variations. It has been said that data management and preparation take 80 percent of the resources and time, leaving only 20 percent for getting useful insights from the data. What if we could flip that equation? Healthcare organizations that approach data management and analytics the right way are creating such efficiencies.
- Software that brings a broad range of analytical procedures within the range of business and clinical leaders. Much of the reporting and analytic software used in healthcare is developed to solve specific problems. The software includes proprietary workflows and programming exclusive to that particular business issue. The alternative is selecting a platform that allows users, from the data scientist to a non-technical business analyst, to address almost every problem with a broad arsenal of statistical tools and procedures via a simple drag-and-drop GUI. The user controls how the data are explored and visualized, from beginning to end, as opposed to a limited menu of proprietary process flows. A good analogy is a construction worker having the choice to buy a lot of very specialized, expensive tools versus a universal toolkit that had the capability to be adapted for almost any analytical need.
- The ability to share insights and put into practice data-driven solutions that effectively blend into the workflow of care delivery and engage patients in their care management. This aim hinges on a user-friendly means to generate those insights and on communicating them to colleagues in a visually appealing way to build consensus. Once consensus is built and the new processes implemented, organizations must also maintain awareness of performance and predict the future state. If the process is changed or replaced, they need some ability to predict the impact of those changes on the overall PHM program
SAS brings capabilities in each of these areas, providing a practical solution for the full cycle of population health analytics. Whether an organization wants to use SAS for a particular use case –improving immunization rates, for example – or to adopt a single analytic approach across all use cases, SAS maintains a strong value proposition and a strong track record for empowering organizations to improve health outcomes. Check out the way that SAS is making a difference in healthcare through analytics.