



© 2023 Quality Digest. Copyright on content held by Quality Digest or by individual authors. Contact Quality Digest for reprint information.
“Quality Digest" is a trademark owned by Quality Circle Institute, Inc.
Published: 05/17/2016
The healthcare industry is in a state of constant change, and with change comes opportunity. With the passage of the Affordable Care Act (ACA) and the Medicare Access and CHIP Reauthorization Act (MACRA), healthcare providers are, or will be, paid differently for their services. No longer can they rely on the volume of services rendered to generate sustained income.
With the transition from volume-based payments to value-based payments, many health systems are investing in data analytics platforms to help expose cost savings, as well as uncover hidden revenue. But is investing in data analytics worth the cost?
With the high cost of data analytics packages, you should expect a positive return on investment (ROI). There are many ways health systems can use data analytics tools to generate a positive return. Data analytics tools can be used in a variety of situations—lowering administrative costs, supporting clinical decisions, reducing fraud and abuse, coordinating care, and improving patient wellness, for example. Healthcare systems have many options to use data analytics tools to increase the bottom line by reducing costs and increasing revenue. Some options are easily quantifiable while others are not, and therein lies the difficulty in determining ROI.
One easily quantifiable way to generate return is through resource utilization. For example, your system’s surgeons use four different companies to supply a particular implantable device. These implants range from $1,000 to $2,400. With data analytics, you are able to identify not only the implant cost variance, but also identify which implant(s) generate the best outcomes for patients. In this example, the implantable device with a cost of $1,200 results in the best patient outcomes, regardless of surgeon. These data indicate the need for supply standardization, which will not only improve cost, but also patient outcomes. The cost savings generated as a result of this analysis provides a positive ROI on the data analytics system that is easily quantifiable.
But what about areas of improvement that generate a return that isn’t so easily quantifiable? Data analytics systems may play a key role in improved care coordination as well as identification of best practices for particular services or specialties. Data analytics may also provide valuable information necessary for improved contract compliance. Each of these improvements is possible through the use of data analytics, and although quantifying the specific ROI associated with these improvements is possible, it’s not straightforward. It is also important to note that the ROI may change over time, so health systems must consider evaluating the return at multiple dates after system implementation.
These are just a few of the many opportunities for ROI in data analytics. Regardless of whether you’re considering one area or multiple areas, one key to being able to calculate ROI for a data analytics system is to establish a baseline data set at system implementation. This allows for comparison of the initial data set to data generated by the data analytics system at various future dates after implementation. Health systems may choose to perform ROI analyses in-house or partner with a healthcare financial consultant. Regardless of the data analytics platform used or the means by which organizations determine ROI for their data analytics systems, it’s important to recognize and quantify the return generated by the data analytics system.