For decades, healthcare providers viewed the occasional clinical denial as the cost of doing business. But with the increasing cost and frequency of denials, providers can no longer afford to shoulder the burden. Charges denied by payers have doubled to nearly 20 percent of all claims submitted, but as many as 90 percent of those were potentially avoidable. When approaching the issue of overwhelming denials, it’s understandable for healthcare organizations to initially prioritize the backlog of denials resulting from limited staff and resources. However, the prevention of future denials is equally important. Through the two-pronged approach of overturning existing denials and minimizing cause for future ones, providers can achieve fewer clinical denials, decreasing costs and protecting their reputations.
Understanding the distinction between a denial issue and its root cause is the first step for a healthcare organization that’s invested in mitigating clinical denials. For example, a payer may deny the medical necessity of a total knee replacement because the medical record sent to the payer did not include documentation of prior conservative treatments, such as physical therapy or painkillers. In this situation, the denial issue is lack of documentation, but the root cause is that the medical record was sent without complete documentation explaining prior treatment. Missing documentation, or lack of specificity within those documents, can result in denials based on observation vs. inpatient status, level of care or length of stay, among other factors.
With many denials originating from process breakdowns, such as in cases of missing or incorrect documentation or prior authorization, it is often possible to identify patterns of where issues are occurring. This is where providers can take advantage of the recent influx of artificial intelligence (AI) and automation models developed for healthcare analytics. AI can be used to quickly compare denied claims with payer coverage policies and locate repeated complications. Supplemented with an in-depth review of a practices’ existing medical records submission processes, providers can determine trends in denials that can inform updated processes.
After identifying any gaps, the next step is to address them. There are myriad possibilities for process improvement, including revised workflows to minimize the chance of missing information and AI-powered analytics and reporting dashboards. Providers with staffing challenges can also continue the use of automation, such as robotic process automation (RPA), to reduce the manual effort expended on simple tasks and free up staff and resources for jobs requiring more expertise.
Being overrun with clinical denials is no longer an inevitability for healthcare providers. With AI and automation supporting staff expertise, providers will be able to recoup valuable time and money, reducing strain on their already limited resources.
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