Self-Service: One Pillar of Business Intelligence

Dan Reber, VP of Product Strategy and Development, PrecisionBI

Earlier, we talked about the four pillars that serve as cornerstones for successful business intelligence (BI) initiatives: Self-Service, Collaborative, Enterprise and Automated. To fully appreciate how they work together, it is important to understand how each one functions and its role. We will start with Self-Service BI.

Self-Service BI helps people get the information they need, turning raw data into actionable insights. Simply put, it enables non-technical people to access and work with data — governed for the broader group.

Data is required to run a healthcare organization optimally. To perform their role, a person on the clinical or operational area of a hospital or practice will require information about any number of things – physician productivity, average time to receive reimbursement, or thousands of other metrics. They send a request to IT to get a report or modify an existing one to gain additional insight. Who wants to interrupt their train of thought for a few days while a new report is generated?

If BI is self-service, anyone in the organization, with the proper permissions, can get what they need without contacting IT and waiting for a reply. Empowering the people that need the information keeps projects moving forward – for all parties involved. Freeing up data analysts allows them to conduct more analysis instead of just creating reports.

You can also get better insights by the people that are experts in the subject matter and know how to interpret the data. This allows for more accuracy and quality of the data because the people that are creating the reports can read it in the proper context. They understand how the data should flow and what parameters to set. Department heads do not need to stop what they are doing, request a report and wait up to a few days for the information. The desired metrics can be available right then.

There are always concerns about data integrity and privacy. This is why role-based permissions and membership ensure that everyone has access to the information they need to perform their tasks without being bogged down with material outside of their responsibility, including the C-suite, financial team, and clinical staff.

There are three different levels of Self-Service BI:

  • Log-in, get it yourself and perform analysis of the data when needed via governed exposure to it.
  • Parameter driven, which allows for changes to the criteria to help narrow the focus
  • Ad hoc where reports can be created or modified as needed. Additional fields can be added, to dive deeper into why.

Let’s say an organization’s Days in AR are higher than normal. The 1st level above can tell you which payers are the problem, with level 2 and 3, you can figure out why. I like to say that dashboards tell a good story but they only get you so far. Ad hoc gives the ending to the story. And who wants to finish a story mid-way through?

Self-Service BI allows providers to see how they are performing against a governed set of metrics and understand how well they are delivering on key metrics, giving the opportunity to adjust for improvement, if necessary. This is a good indicator for both operational and clinical success.

Healthcare organizations are also able to self-report for Medicare Access and CHIP Reauthorization Act (MACRA) initiatives, including Merit-based Incentive Payment System (MIPS), CPC+ and other Alternative Payment Models (APMs).

We designed PrecisionBI for the non-technical business user. Our extensive ad hoc analysis capabilities empower healthcare organizations to take a “deep dive” into their data to determine the root causes of issues and build strategies to monitor trends and activities across your organization. The system is vendor-neutral so even as organizations shift EHR vendors, there is no need to change BI systems.

Using this approach to BI, healthcare organizations have gained great insights from their data. Below are a few examples:

  • Improved patient care through direct provider feedback on chronic care management, health maintenance, and practice management.
  • $5 million in additional revenue from lost procedure and consult charges.
  • $4.3 million in additional charges by analyzing charges vs. payments by payors.
  • $1.5 million per year in additional revenue by identifying undercoding for just 25 of the health system’s providers.
  • $1.5 million in underpayments recovered in just one year.
  • One quality metrics team saw up to a 20% improvement in measured performance by giving the right people access to clinical data.

Think of all the benefits your organization could achieve if the right people were empowered to answer their questions by diving into the whys. Now that your IT and analytics folks are free from running many of these reports, what new challenges can they address?