We’ve all been living with insurance claim denials for what seems an eternity. We have come to accept that a moderate denial problem is simply the cost of doing business in our industry. But with all the changes and pressures being thrust upon medical groups, many healthcare providers are rightly concerned about their future financial performance.
With payers continuously changing their reimbursement rules, with ICD-10 adding yet another level of complexity, and with the increasing prevalence of high-deductible plans —all of which places more financial responsibility into the hands of patients and increases the potential for nonpayment—it’s imperative that provider organizations do everything they can to capture 100% of revenue owed to them by the insurance companies.
While the government finally repealed the Sustainable Growth Rate Formula (SGR) and has eliminated the annual anxiety around the annual 11th hour “doc fix” adjustments, the payment formula governed by new MACRA legislation ensures essentially flat Medicare payments for a decade to come.
What this means is that physician groups cannot rely on rate increases to grow their revenues and they must focus on operational excellence within their revenue cycle operations to drive revenue improvements.
This is where clean data comes in. As we alluded to in the title of this blog, clean data drives everything in healthcare. Your business processes, your analytics, and ultimately your revenue cycle performance. If your data’s not clean and trustworthy, there’s no way your business office can function properly and there’s no way you can be confident that you are maximizing the performance of your revenue cycle operations.
Think about it: What are the ramifications of incomplete, incorrect patient demographic or financial data? From a staff or workflow perspective, it means inefficient processes, rework due to denials, insufficient staff productivity, high business office labor costs and, possibly, low staff morale. From a financial standpoint, it means inaccurate reporting, missed revenue opportunities and slow reimbursements or flat out denials.
The bottom line is that if your data is not clean and accurate, your costs are higher and your revenue is lower—neither of which bodes well for your organization.
Ultimately clean data means confidence in your business processes, your compliance efforts, the likelihood of reimbursement success, a higher performing revenue cycle and, in many cases, improved patient experiences.
In coming blogs we’re going to take a more in-depth look at the importance of clean data and how you can reap the specific benefits it offers for your organization.
Hope you’ll come back for more.
Thanks.
