What Does Your BI Do for You?
Some healthcare organizations are finding that traditional BI tools are not giving them everything they need.
For the past decade, many healthcare executives have been relying on business intelligence (BI) to measure the revenue cycle's effectiveness and efficiency. Traditionally, BI tools and the technology they use have been borrowed from the industrial sector and adapted to fit the hospital or healthcare system's needs. As healthcare's use of BI has become more sophisticated, it's becoming increasingly apparent that traditional data analytics approaches aren’t necessarily suited to healthcare. Specifically, relying on the after-the-fact reporting inherent to analysis doesn’t prevent the outliers that cost healthcare organizations time and money. Why aren’t traditional BI tools enough for healthcare? To find the answer, let’s take a quick look at the differences between data in traditional vs. healthcare industries and some limitations of BI.
The data have inherently different qualities
Healthcare data are complicated by many variables that are not found in traditional business management, processes, and products.
Comparison of business vs. medical data*
Healthcare does its best to quantify intangibles such as patient satisfaction. However, patient satisfaction metrics, like many other healthcare data points, can vary according to precisely what is being measured. For example, should patient satisfaction encompass the entire experience with a provider, or just office staff and billing? Or each department? The complicated structure of healthcare usually warrants customized definitions of data – one size does not fit all.
Blind spots in data
Analytics experts will tell you there can be blind spots in any type of data, but the blind spots in healthcare tend to aggregate deep within processes. For example, denial analytics may tell you a high percentage of denials are due to non-coverage, when in fact, many denials can be due to incorrect patient demographics triggering the non-coverage.
Another challenge: ownership of actionable analytics
A challenge to both traditional and healthcare industries is the problem of who owns the process when analytics indicate action is needed. Healthcare’s intricate structure of management sectors, actors, and the myriad of outcomes makes data ownership much more complicated than traditional industry.
The evolution of healthcare BI is Effy
Healthcare executives using BI need to improve quality, efficiency and make smarter business decisions. Effy Healthcare is the all-in-one solution for organizations that want to make the most of intelligence and act and resolve factors that lead to data blind spots, lower efficiency, and affect revenue.
In addition to traditional BI, Effy’s end-to-end platform uses real-time data and actionable analytics features to quickly isolate and automatically correct data before claims are generated, leading to more accurate data and ultimately better BI. Effy’s data discovery process identifies critical changes and issues instant notifications whenever customized thresholds are reached, fostering real-time resolutions that save time and money.
Blind spots are mitigated by an empowered revenue cycle team, that with Effy’s solution has the ability to drill down into operational processes department-by-department, person-by-person, ultimately correcting the situations that cause denials and other claims cycle challenges – creating accountability for challenges identified in BI as well as solid standard operating procedures that ensure a sustainable correction.
Perhaps most importantly, Effy Healthcare's solution reaches across your enterprise to deliver a comprehensive analysis of performance. It seamlessly integrates with all health management platforms to provide real-time analysis and corrective workflows to organize actions and automate the fixing journey, that optimize both clinical and financial operations.
Interested in learning how Effy Healthcare can truly make actionable BI work for your organization? Contact us today at email@example.com.
*Mettler, T., & Vimarlund, V. (2009). Understanding business intelligence in the context of healthcare. Retrieved from https://journals.sagepub.com/doi/pdf/10.1177/1460458209337446