As the scale of healthcare data continues to grow, it's more important than ever to generate insights and actions quickly and easily. The quote from Herbert A. Simon (Carnegie Mellon) is more true than ever today, “A wealth of information creates a poverty of attention.” So, how do we direct our attention towards the right things within our ever expanding "wealth of information"? Data visualization is the key. The Journal of AHIMA (American Health Information Management Association) published a blog "The Rise of Healthcare Data Visualization" which highlights the growing importance of data visualization and storytelling. The purpose of this post is to help you think about how to approach data visualization create a culture of analytics to transform your healthcare organization.
What is data visualization? “Data visualization is a collection of methods that use visual representations to explore, make sense of, and communicate quantitative data.” Why is data visualization important? Human brains process visual information better than text. We need to “see” the data. And the way our brains work we can draw conclusions (“understand” the data) better and more quickly when It’s visual. Think about how difficult it is to spot a trend in a table of numbers? Put the same data in a chart and the trend becomes obvious. Healthcare needs solutions that enable people to see their data, and more importantly, understand their data. It’s time to stop thinking about creating reports. We need to think about enabling healthcare professionals to answer the critical questions. It’s time to design for a culture of self-service data visualization and analytics. The important questions in healthcare, which range from population health to clinical care to supply chain are best answered in context by the people in those areas. Your team wants to make good decisions. They just need access to the right data and the tools to interact with the data. Here’s an approach to get a data visualization win in a department and simultaneously set the foundation to transform the organization
1. Create the Vision and Scope for Data Visualization
Before you start thinking about connecting your visualization tools to various data sources, consider what you want to accomplish. Begin with the end in mind. Engage the stakeholders. For whom the visualization is intended? How can you make it easy for them to access additional data? Write down a vision/scope statement that clearly identifies the target for your data visualization project. Also, start with a focused project to get a win for the organization. As an example, one of our Accountable Care Organization (ACO) clients brought together the stakeholders for a project. The intended consumers of the dashboard were physicians within the ACO. The team defined the objective of the project with a scope statement that called for development of a Physician Scorecard that combines ACO, Managed Care, and Operational Performance Metrics. The critical success factors for the project were listed as creation of a single source of data for monthly reporting (to physicians), awareness and education on the identified performance metrics for the physicians. The example above addresses the critical questions that need to be considered in advance. What is the purpose of the visualization? What are you trying to communicate with the visualization? Who is the audience? Projects often begin with the goal of developing a dashboard or report that is designed to be consumed by the target audience. This is a good place to start, but the goal should be enabling self-service analytics (more on this below).
2. Plan for Data Curation and Governance
It’s important to think about data curation and governance from the outset of your first project as a healthcare organization. The journey toward self-service analytics and data visualization in the organization often begins in a single department with a single dashboard, targeted at a specific group like the physician’s dashboard example above. The demand for analytics will grow quickly. It’s best to be prepared for this. Healthcare data sources are numerous. A single healthcare system or ACO may have EPIC, Lawson, Press-Ganey, SAP, IBM Watson, CMS and many other provider and payer data sets that need to be aggregated. This disparate data needs to be captured, cleaned, defined, and aligned. Many refer to this as data curation.In addition, it’s important to establish governance over the data to enable self-service analytics. Governance is a combination of controls on the data, roles to define access to the data, and repeatable processes the keep the data updated so that it can be trusted by the organization as the single source of truth (SSOT). In a modern data analytics environment, governance enables and empowers healthcare workers to access the right data at the right time without having to make requests of the IT department for new reports or analyses. In the modern analytics environment, IT provides the systems and structure to protect data as well as provides the permissions to empower people by their role in the organization to access the data for analytics.
3. Enable Self-Service Analytics
An environment where data is secure and managed by IT enable the organization to embark on self-service analytics and data visualization because they trust the data. At the same time, IT and the leadership of the organization can trust that the data governance model ensures that the right people have the right access to data. This is the foundation of a culture of self-service data visualization and analytics. Continuing with our Physician’s Report example, the physicians will be able to access their specific dashboard by logging into a server. What they see is tied to their role and who they are. This dashboard will provide the key performance metrics that drive shared savings for the ACO. We won’t go into the details here, but generally the metrics include productivity, quality, utilization & spending, and patient satisfaction. With tools like Tableau or Power BI, it’s easy for users to view a dashboard that’s been built for them. It’s also easy for users to explore the data in the dashboard or to create their own views of the data tailored to their needs which they can save and return to later. By enabling self-service analytics, everyone who has access to the data can explore. People can quickly and easily answer their own questions, share findings, learn from each other, and ask follow-up questions that lead to deeper insights. Because the data is on a centrally managed platform that is governed centrally by IT, each physician will only be able to see and explore data that is available to them under the security model. However, sharing analytical concepts and event data visualizations is easy and when applied by another user to their data set, will show them relevant results.
In this age of rapidly growing sources and volume of data, a data visualization strategy is critical for your healthcare organization. This three-step process will get you started.
Create the Vision and Scope for Data Visualization
Plan for Data Curation and Governance
Enable Self-Service Analytics
Read our blog about how to create a thriving community around data.