In the dictionary, the term “sleeping giant” refers to “one that has great but unrealized or newly emerging power.” It’s an apt expression for describing the growing volume of data available to hospitals and other healthcare providers. The pressure is on—from the CMS and healthcare consumers alike—to use data effectively to improve the quality of care while reducing costs.
“As patients transition from passive care recipients to active value-seeking consumers — it is healthcare’s turn to master these tools as new competitors chip away at the market.”
And providers aren’t the only ones looking to leverage data effectively. Health data represents a high-stakes game for health insurers, pharmaceutical companies and medical device manufacturers as well. In order to wake this giant—and ensure it solves problems, rather than causes them—healthcare-related organizations need to implement effective health data management practices.
Building the Case for Data-Driven Healthcare
Using data in innovative ways isn’t new to some industries. Retail and financial services businesses, for instance, have been making good use of data and digital technologies for years. But as a 2014 PwC Health Research Institute report notes, “As patients transition from passive care recipients to active value-seeking consumers, it is healthcare’s turn to master these tools as new competitors chip away at the market.”
The U.S. Department of Health and Human Services (HHS) clearly agrees, investing in the HHS IDEA (Innovation, Design, Entrepreneurship and Action) Lab to help foster innovation in healthcare. The HHS IDEA Lab acknowledges that, “The current times call for new, disruptive ideas and actions that fundamentally alter and improve the way we do business.”
Already, hospitals and health systems are leveraging health data and innovative technology to:
•Understand population health needs more clearly
•Identify variations in care to realize cost efficiencies
•Enhance the quality of patient experiences and outcomes along the care continuum
•Improve disease management and care plan compliance
•Increase patient engagement and brand loyalty
Handled correctly, data-driven decision making in healthcare also strengthens your bottom line. According to Aberdeen, notes an article in Becker’s Hospital Review, “ leaders in data analysis, reporting and management, “… increase their revenue an average 20 percent annually, more than double the followers, and have reduced operating costs by 15 percent year over year.”
The Keys to Managing Health Data
Why is health data management so important? In addition to the benefits that can be realized from health data, good data management practices are critical to keeping pace with the sheer volume of data being produced. For example, points out Healthcare IT News, the data that Kaiser Permanente manages from its EHRs alone is enough to fill 4,400 Libraries of Congress—and it grows with every passing hour. How can you get more with better health data management?
Move data from traditional silos to a unified data warehouse.
This is an ongoing challenge, given interoperability road blocks and the mix of structured and unstructured data that must be managed. You need to bring the data together to capture a 360-degree view of healthcare consumers, hospital operations and more—and that’s nearly impossible when the data remain in separate silos. Once you bring together the data, you also need to implement classification standards to ensure that you can integrate, sort and analyze various types of data from multiple sources. Even variations in terminology pose a challenge unless such variations are tagged to identify them as similar.
Define your expectations for using data.
Healthcare IT News notes that, “The key is not to seize every last bit of information, but to capture the right information.” By setting specific goals for data usage, you can identify the data needed. The focus on specific needs makes health data management easier, moving you away from information overload and towards data-driven decision making.
If you want to develop more effective patient engagement strategies, for example, you can benefit from consumer diagnostic research and psychographic segmentation.
Tap innovative data sources.
Once you define your expectations, you may find that not all of the data you need comes from your EHRs, clinical and financial systems. Consider additional sources of data that can help you make the most of your internal data. If you want to develop more effective patient engagement strategies, for example, you can benefit from consumer diagnostic research and psychographic segmentation, both of which allow you to gain deeper insights into the unique behaviors and motivations of healthcare consumers.
Psychographic insights enable one to analyze the behavioral data captured in an EHR (what consumers are doing) with a lens to interpret that data according to consumers’ motivations (why consumers are doing it). Armed with these insights—along with hospital data—you are better positioned develop innovative, data-driven patient engagement and population health programs that effectively encourage behavior change.
Are you getting as much value from your data as you’d like? If not, it may be time to revisit your health data management practices.