Optimal Quality Coding Prevents Medical Claims Denials
Medical billing denials generate significant cost for providers and hospitals that could be avoided by improving claims data management and optimizing medical coding processes. According to the American Medical Association National Health Insurer Report Card (2013), the five most common reasons for medical billing denials include missing information, duplicated claims or services, services already being adjudicated, services not being covered by payer, and the limit for filing has already expired. Optimal quality coding effectively prevents medical claims denials by reducing the potential for manual error and addressing concerns over fast approaching time limits.
How to prevent future claims denials, increase reimbursement, and maximize revenue?
In retrospect, many claims denials are preventable with more careful data management and improved quality coding. Even a single blank field on a claims form can be sufficient for immediate claim denial, with technical errors cited as being responsible for 61% of initial claims denials, as well as 42% of denial write-offs. Furthermore, “duplicates, which are claims resubmitted for a single encounter on the same date by the same provider for the same beneficiary for the same service item, are among the biggest reasons (up to 32%) for Medicare Part B claim denials” (Change Healthcare, 2016). The cost of an individual service may fall under another claim that has been previously satisfied, resulting in denial. Providers should always refer to individual patient insurance policies to confirm that services are covered prior to seeing patients to avoid denial due to services not being covered. Finally, with a limited window available to submit medical claims, the time-consuming process of correcting manual errors ultimately leads to unnecessary billing delays, with 81% of complex claim denials occurring as a result of expired filing limits.
Improved quality coding as a targeted strategy for process optimization
Multiple strategies exist to achieve optimal quality coding in an attempt to reduce costs associated with medical claims denials and maximize revenue. Effective management of patient claims data is crucial towards this goal; medical claims denials should be properly measured, categorized, and organized for efficient analysis, and the quality of data entered initially upon admission must be greatly improved. The creation of dedicated resources focused on continued statistical analysis of trends inpatient claims data can identify potential solutions and provide documentation of ongoing progress. Determination of the reason for each denial by root-cause analysis offers further valuable insight towards preventing future denials for similar reasons. Additional opportunities for improved reimbursement include the introduction of an effective denials management program, and implementation of insurance claims management software to automate portions of the claims process, used in combination with automated predictive analytics, as well as the option to outsource revenue cycle management to independent, third-party consulting services.