The healthcare industry is suffering from a significant staffing shortage, and revenue cycle departments have been hit particularly hard.1 As a result, revenue cycle departments across the country are experiencing staff burnout, delayed payment cycles, and other challenges which put the financial viability of healthcare organizations at risk. Autonomous coding, a solution that leverages AI to fully automate the medical coding process, can help organizations overcome these challenges and ensure future financial stability.
Recent months have seen staffing shortages grow to unprecedented levels within revenue cycle management (RCM). In a recent survey of chief financial officers and vice presidents of revenue cycle at large health systems, 48% of respondents reported a “severe shortage” in their organization’s revenue cycle management (RCM) department.2
RCM executives cite high labor costs, increased competition for talent, and the “Great Resignation” as the main factors driving this shortage, which shows no signs of ending anytime soon.3
For healthcare organizations, this shortage is causing significant challenges within the revenue cycle. RCM departments that continue to rely on manual processes are experiencing staff burnout, delayed payment cycles, and other issues that severely impact the financial viability of healthcare organizations. To solve these challenges and ensure future stability within the revenue cycle, healthcare organizations are turning to automation technology.4
There are several different approaches when it comes to leveraging automation in RCM, each with its own set of benefits and use-cases.
On one side of the spectrum is the automation of simple, repetitive tasks with technology such as robotic process automation (RPA). RPA software mimics human behavior for rules-based tasks, enabling RCM departments to automate data entry, cost estimate generation, and other low-complexity processes.5 Leveraging technology like RPA can help alleviate staffing shortage challenges by freeing up RCM staff members and enabling them to focus on more complex processes.
On the other side of the spectrum is the automation of entire revenue cycle stages with technology such as autonomous coding. Autonomous coding solutions leverage multiple subfields of AI (machine learning, natural language processing, deep learning) to automate the medical coding stage of RCM. The goal is to meet or exceed the accuracy thresholds of human coders so that autonomously coded charts can be sent directly to payers for reimbursement.
By fully automating medical coding, autonomous coding solutions directly solve the challenges posed by staffing shortages and provide long-term stability to RCM departments.
Medical coders are now responsible for coding a larger volume of patient charts than ever before. This can lead to higher rates of staff burnout, as coders are required to significantly increase their productivity while maintaining coding quality.
By fully automating coding for a certain percentage of charts, autonomous coding solutions dramatically reduce the workload for coding staff. As a result, the technology reduces the risk of burnout and allows medical coders to focus their attention on coding the charts of patients with more complex medical conditions or those that are missing information.
Another potential consequence of medical coders having a larger chart volume than normal is coding backlogs. If coders are unable to meet the increased demand, revenue cycle departments may find themselves with thousands of charts waiting to be coded. This creates a significant bottleneck in the revenue cycle and can quickly result in delayed payment cycles.
Autonomous coding solutions can quickly resolve these backlogs, as most solutions are capable of processing hundreds, if not thousands of charts per hour. By doing so, autonomous coding solutions mitigate the risk that backlogs pose to payment cycles, and can actually accelerate payment cycles significantly.
Nym has developed its own autonomous coding solution. Powered by the Company’s innovative clinical language understanding (CLU) technology, Nym’s medical coding engine deciphers clinical language in patient charts and assigns compliant ICD-10 and CPT medical charge codes. The engine processes thousands of charts per hour with over 96% coding accuracy, all with zero human intervention.
Leveraging Nym’s engine, healthcare organizations across the US are successfully overcoming the current revenue cycle staffing shortage. Furthermore, organizations can rely on Nym’s engine to constantly process charts in the event of future staffing shortages or fluctuations in chart volume – providing the flexibility and stability that is becoming increasingly important in healthcare.
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