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As defined by the Healthcare Business Management Association (HBMA), healthcare revenue cycle management (RCM) is “the administration of financial transactions that result from the medical encounters between a patient and a provider, facility, and/or supplier.” These transactions include billing, collections, payer contracting, provider enrollment, coding, data analytics, management, and compliance. In short, healthcare revenue cycle management is the process of identifying, managing, and collecting patient service revenue.
There are myriad challenges associated with healthcare revenue cycle management. Provider burnout is prevalent throughout the healthcare industry, and employees working in all areas of healthcare are overworked and overburdened. Additionally, EMRs perpetuate an abundance of bad electronic billing data, leaving RCM teams struggling to keep up. Detailed below are the three biggest challenges facing RCM teams today.
Physicians didn’t go to medical school to become coders. They focus on providing the best possible care to their patients, not on the intricacies of coding. When charges aren’t accounted for at the physician level, medical groups lose money. Additionally, RCM teams end up spending significant time sifting through bad electronic billing data from the EMR reviewing and correcting information.
Payer requirements are constantly changing, and it can be tough for revenue cycle management teams to keep up. When updated payer requirements are missed or overlooked, denials increase. The Change Healthcare 2020 Denials Index, an analysis of 102 million hospital transactions, found that the average denials rate is up 23% since 2016, topping 11.1% of claims denied upon initial submission through the third quarter of 2020.
This combination of evolving payer requirements and bad electronic data offers a lot of opportunities for mistakes. In fact, our data indicated that up to 50% of claims have errors. When organizations have insufficient staff, these mistakes compound and can quickly add up.
Staffing shortages are plaguing the entire healthcare industry, and revenue cycle management teams have been hit hard. According to an MGMA Stat poll conducted in September 2021, 75% of medical practice leaders ranked staffing as their biggest challenge heading into 2022. According to an analysis by Revenue Cycle Intelligence, 25 percent of healthcare finance leaders noted that they would need an additional 20 or more employees to have a fully staffed revenue cycle department.
Revenue cycle integrity involves ensuring that clinical encounters are accurately translated into revenue. It includes people, processes, and platforms that work towards operational efficiency, compliance, and optimal compensation.
To achieve revenue cycle integrity, medical groups need a strategy in place to prevent revenue leakage. This strategy should have two main components:
The primary purpose of claim scrubbing is to detect and eliminate errors in billing codes, reducing the number of claims to medical insurers that are denied or rejected. While this is a simple concept, the process itself can be complex. There are many different approaches.
There’s a significant need for automation in the claim scrubbing process. Claim scrubbing by nature involves a lot of routine tasks—there will always be minor errors that need correcting time and time again. By leveraging AI to autocorrect these routine errors and streamline the entire workflow, teams can free up staff to focus on the areas where their expertise is most needed.
Automation is also an important part of reducing revenue errors and improving revenue cycle integrity. Billing and coding experts can only catch so much, and as their workloads become increasingly overloaded more opportunities for errors arise. Automation can help ensure that claims go out correctly every time, meaning revenue doesn’t fall through the cracks.
Given the above, it’s no surprise that medical groups across the country are turning to automation now more than ever. According to a survey commissioned by AKASA, the number of health systems using revenue cycle automation increased by 12 percent in 2021 over 2020. In all, 78 percent of the health systems surveyed were already using or were in the process of implementing revenue cycle automation.
As defined by the AAPC, clinical coding is the transformation of healthcare diagnoses, procedures, medical services, and equipment into universal medical alphanumeric codes. Software types commonly used in a clinical coding context include Computer Assisted Coding (CAC) and Natural Language Processing (NLP), which are technologies used to scan a provider’s clinical note and recommend codes based on what was documented.
The other approach is administrative coding. Administrative coding deals with the administrative accuracy of claims. This involves ensuring claims meet a payer’s specific requirements.
One of the most common and widely used types of administrative medical coding software is a claim scrubber. Claim scrubbers help ensure the correct ICD-10 and CPT codes are included on a claim, among other administrative payer requirements. Traditional claim scrubbers work on the back end of the billing process. This means that claim data review takes place after a claim is created in the RCM system but before going to the payer. If the claim scrubber detects an error, a task is typically created for a biller or coder to work within the RCM tasking system. The coder or biller then has to make the correction and repost it into the RCM system.
Conversely, charge scrubbers work on the front-end of the process—before the claim goes out. Since charge scrubbers review charges before they enter the RCM system, they’re a better area in which to leverage AI. If an error is identified by the AI software, it is flagged so that a coder or biller can make the corrections before a claim is created. In this model, the scrubbed charges enter the RCM system accurately and are ready to be submitted as a claim.
By automatically reviewing all claims with software instead of manually reviewing each claim individually, teams can catch more errors in less time. Not only does this decrease denials right off the bat, it also allows organizations to gather data about their common denial causes and proactively approach problem areas. Groups who proactively identify these frequently occurring errors and tackle them before claims go into the payer can drastically reduce claim denials in the long run.
According to a recent Revenue Cycle Survey from Advisory Board, health systems and hospitals wrote off 90 percent more claim denials as uncollectable compared to six years ago. For a hospital with a median of 350 beds, this increase would add up to a $3.5 million loss over the past four years.
Automation can help prevent these costly denials and can also find revenue that might otherwise slip through the cracks. For example, a provider might immunize a patient but forget to add the CPT code for administration of an immunization when entering the charge into the EMR. An AI solution can automatically detect this error and add the necessary code to the encounter, thus capturing the potential missed revenue.
Claim scrubbing automation reduces the time it takes to review claims. By automatically processing claims that are error-free and don’t need review, automation solutions significantly reduce the burden on billing and coding staff. By acting as a knowledge repository for all payer requirements, these solutions can also reduce the training period for new staff. Staff can focus on only those encounters that require modifications, and revenue cycle leaders can rest assured that everyone on their team handles billing and coding issues exactly as instructed for every encounter.
Christi Garriott, Senior Vice President of Business Intelligence and Revenue at Peak Vista, a nonprofit federally qualified health center (FQHC) in Colorado, explains the impact of the RCxRules Revenue Cycle Engine automation on her staff’s efficiency: “Now out of 3,000 tasks a day, we probably have to manually review about 100. Everything else automatically posts. Clean claims go out the first time without the need to review them.”
The natural outcome of increased staff efficiency and decreased denials is an improvement in AR days. Getting paid quickly and efficiently helps teams hit financial targets and provides the peace of mind of reliable, predictable, and surprise-free revenue generation.
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