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- Data Intelligence For Claims Operations
According to the American Medical Association almost one in five (19.3%) of medical claims processed by the largest commercial health insurers is inaccurate. Imagine being one of those patients that goes in to see your doctor for a sprained wrist and a few weeks later receives a bill for a “short leg splint calf to foot.” Last time we looked your wrist is nowhere near your foot…While it might sound ridiculous to think that such a grievous mistake could happen clearly it happens far more frequently than many patients realize.
In fact, the National Health Insurer Report Card found a 2% rise in claims processing errors from 2010 to 2011, which added “an estimated $1.5 billion in unnecessary administrative costs to the health system. The group estimates that if health insurers were able to eliminate all claim processing errors, the health care system could save $17 billion a year.
The AMA calculates that doctors’ offices spend an average of 20+ hours each week dealing with claim edits. When a claim receives an edit, it is kicked back from the insurance carrier to the healthcare provider and the patient with a “reason code” for why the claim was rejected. A report from March 2011 from the Government Accountability Office (GAO) indicated that insurers are denied coverage more frequently because of claims processing and billing errors than because the care was deemed medically inappropriate. This means that your healthcare claims processing office could be at fault when patients are denied coverage! Not only are your processors costing you time and money; their processing mistakes are directly impacting the health and well-being of patients.
Eliminating claims processing and payment errors should be a critical objective for all health insurance providers. Errors are expensive, damage your brand and reputation, and can lead to regulatory sanctions. Healthcare claims processing errors come from a variety of sources (the subscriber is deemed ineligible for coverage, the medical coding doesn’t match the actual procedure, the patient needed precertification, etc.), but a substantial amount of processing errors can be traced right back to employee activity. Some processors manage their time poorly, and then need to do many claims in a short amount of time to hit their daily requirements. Other employees might skip using the applications designed to reduce errors as way to save a few minutes per claim (which comes back to bit them in the end when they have to deal with a claim edit). And sometimes claims processing employees may simply not understand the processes they are expected to follow. Medical billing and coding can be incredibly complicated and if mistakes aren’t caught and corrected right away your processors might not even realize they were doing something wrong.
In order to reduce the amount of claims processing errors and save that $17 billion, healthcare providers need to better understand the specific actions that caused the error to begin with. Was the processor doing something in particular that caused the error? Is there an issue with your system that makes the claims process more prone to errors? When a healthcare provider can identify employee work patterns that lead to claims processing errors and see the specific actions taken on claims that were processed incorrectly they can better identify process changes and coaching opportunities that will help reduce claims processing errors.