Return on investment. It’s something every business calculates—from marketing efforts to large equipment purchases to capital improvements. We want to know if our investments in the business are paying off.
Healthcare is no different, and measuring ROI has become even more important as we transform the healthcare system. With the passage of the ACA and MACRA, healthcare providers are, or will be, paid differently for their services. No longer can they rely upon the volume of services rendered to generate sustained income. Instead, they have to demonstrate the value they provide their patients.
In order to track data that will confirm both the effectiveness of treatment and the underlying costs, many health systems are investing in data analytics platforms. But is the investment in data analytics worth it?
The answer is a resounding “it depends.” In order to determine if the data analytics package you’ve purchased, or are considering, is worth the money you’ll spend on it, you have to use the information it provides to lower your costs and improve your outcomes. And you’ll have to be able to track the savings you’ve realized. These packages aren’t cheap, but you should expect a positive return on investment if you use the information they generate wisely.
So how can you generate a positive ROI? Some strategies are easily quantifiable, but others are more difficult to determine. The key will be to use the data analysis you have to make positive changes within your system.
One easily quantifiable way to generate return is through proper resource utilization. The goal is to standardize the use of certain supplies and devices at both the lowest cost and highest effectiveness possible. Your data analytics package can help you determine where you can best spend your resources.
For example, let’s assume your system’s surgeons currently use a particular implantable device sold by four different companies. The cost of the device ranges from $1,000 to $2,400, depending on the supplier. Your data can show you the cost variance for the different devices, but it can also show you which implant generates the best outcomes for patients.
Continuing the example, let’s assume that the device that costs $1,200 results in the best patient outcomes, regardless of surgeon. Armed with that information, you can make recommendations to standardize the procurement of the device from one supplier. Standardization not only lowers the cost of some of your procedures – those using more expensive devices – it will provide better outcomes for your patients, thus potentially improving your quality-based revenue.
Your ability to analyze the actual cost and effectiveness of the devices across your system allows you to make decisions like the ones in the example above. Without serious data analysis, however, you cannot examine the cost and effectiveness of the thousands of items used in your system every month. The cost savings generated as a result of this type of analysis provide an easily quantifiable, positive ROI for your data analytics system.
Data analysis may even help you decide to stop certain services. If a service is not profitable and a competitor does it better, it may be time to stop wasting resources on it. The ROI on your analytics package may increase dramatically if it can help you identify areas where you are losing serious money.
But how can you determine ROI in areas that aren’t so easily quantifiable?
Your ability to analyze data can help you improve care coordination and identify best practices for particular services or specialties. Knowing how services are used and where the challenges lie can help you control costs. You might find that directing resources to new services, such as visiting nurses, enhanced patient education or social services, may improve outcomes or reduce hospital readmissions.
Data analytics may also provide the information necessary to improve contract compliance. With more detailed analysis, you can answer the question, “Are we getting what we paid for?”
Using your data analytics package effectively can make these improvements possible. Determining the ROI for your analytics package is also possible, but it’s not always straightforward and may require more thought initially. In addition, the ROI may change over time, so it is important to consider evaluating the return at multiple dates after you implement the system.
You will have many opportunities to show the ROI for your data analytics, but it’s important 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 post implementation.
Healthcare systems may choose to perform ROI analyses internally or partner with a healthcare financial consultant. Regardless of the data analytics platform used or the method used to determine ROI, it is important to recognize and quantify the return generated from data analytics packages.
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