Industry-wide, hospitals are impacted by an onslaught of changing governmental regulations, insurance payer modifications, and transitioning patient expectations. Our evaluation of the revenue cycle management (RCM) process points to four areas where significant revenue is at risk when not performed efficiently: 1) medical coding, 2) medical billing, 3) A/R management, and 4) bad debt/collections.
While hospitals may opt to handle these functions in-house with a mix of automated and manual systems, we outline a far superior structure that brings artificial intelligence (AI) and machine learning capabilities through an integrated and secure HL7 technology, supported by highly-trained billing specialists, as a comprehensive solution to today’s RCM process.
Exceeding Industry-Accepted Norms for RCM
While generating healthcare revenue gets a lot of the spotlight, medical billing, and collecting that revenue can be the real workhorse. Hospitals and healthcare systems are facing real challenges and headwinds are everywhere. Changing and expanding requirements from government entities and insurance companies, new payment models, and RCM issues like rising bad debt and uncollectible amounts leave hospitals searching for a way forward.
From the macro perspective, maximizing revenue in the healthcare industry’s complex third-party payer system continues to be a challenge. With increasingly elaborate payment models and fee schedules, and escalating payer scrutiny for advanced technology used in most hospital departments, it’s never been more critical to stay current with new AI-driven advances in the revenue payment lifecycle.
To add to the complexities, according to the Healthcare Financial Management Association (HFMA), the CDC has released findings showing that 47% of commercially-insured consumers were choosing a High Deductible Health Plan (HDHP), hoping to reduce household health insurance costs by lowering premiums.1 This shift in financial responsibility from government and private insurance payers to consumers has made it imperative for hospitals to embrace new technology or risk precious margin on the accelerated growth of bad debt.
4 RCM Areas that Improve Hospital Revenue
For these purposes, let’s define the lifecycle as twofold: 1) patient access, including prior authorization and insurance verification, coupled with 2) RCM—medical coding, medical billing, A/R management, and insurance discovery. By examining RCM’s key functions, we can determine where maximum efficiency could be gained, and previously lost or delayed revenue could be captured. Let’s look at four RCM components and their inherent issues:
1. The Medical Coding Process
Since its release in October 2015 and the myriad subsequent changes and updates, the ICD-10 coding system presents a multifaceted and intricate set of issues, especially for hospitals that utilize different care venues (hospitals, outpatient centers) and complex diagnoses and procedure options.
On September 18, 2020, the final rule for the Medicare Hospital Inpatient Prospective Payment System for the fiscal year 2021 was published with a variety of DRG/MS-DRG changes that recognize advances in technology and care delivery. This, in turn, creates growing problems for insurance payers who are trying to contain costs and ensure medically sound and appropriate patient care is being delivered.
Once a patient is discharged, the first step is to determine the accurate codes and service levels. However, whether it’s due to lack of time or chart completion expectations, procedures and testing are often under coded, miscoded, documentation is missing, or level of service is misclassified. This causes severe problems that impact revenue, including denials, underpayment, and abandonment of claims.
2. The Medical Billing Process
One of the biggest pain points for hospitals can be projecting the billing process workflow and the inability to scale for the fluctuating workload quickly. From charge entry to payment posting, everything can be either overloaded or slowed to a crawl based on staffing within the billing department.
Staffing issues from unexpected changes in employment status, family leave requests, and hiring mis-queues can create bottlenecks that slow down claims processing and impact bottom line revenue. This creates further problems with ancillary responsibilities, such as resolving credit balances and managing contract performance to aid future negotiations.
3. AR Management
At a recent healthcare business management symposium,3 a study accepted industry-wide by the Medical Group Management Association (MGMA), estimates the cost to rework a claim that has been denied by insurance is $25.00 for each occurrence. And even more impactful is the fact that between 50% and 65% of denied claims go unchallenged due to lack of time and/or understanding on how to proceed with the revenue, thereby lost completely.
In healthcare’s complex and administratively burdensome accounts receivable process, managing the unpaid or rejected claims can be especially frustrating for billing staff. Not only does it create large blocks of unproductive time while staff members sit on hold or wait in insurance payer queues, but there are often limits on the number of claims that can be submitted or questioned during each call.
Claim status inquiries alone are estimated to take 17minutes per claim according to the 2020 CAQH Index, and takes valuable staff time away from higher-value billing functions or improving the overall patient experience.4 By automating the claims management process, a hospital can save 14 minutes per claim while also saving valuable staff time and lost opportunity redeployed to more meaningful functions.
4. Bad Debt and Collections
The most frustrating component of RCM is bad debt, and those accounts that must be reluctantly turned over to a collection agency for potential follow up once all internal avenues have been exhausted. These claims are often overdue because of uninsured patients or unpaid self-pay accounts and are written off completely or categorized as charitable care. Bad debt can total as much as 15% of total receipts in today’s hospitals, and that number is sure to grow as patients assume more and more of the financial obligations for care unless something is done to curb this trend.
Best Automated Processes for RCM
RCM inefficiencies can pose one of the most perplexing problems in hospitals today! Complex approval processes and requirements that differ by health insurance plan make claims management a challenge for even the most well-informed billing administrator. It’s not enough to rely on the status quo; groups today must be proactive in developing plans to improve operations and patient access procedures, as well as their RCM to meet the test.
With today’s focus shifting toward maximizing the patient experience and alleviating any roadblocks to collecting timely reimbursement where due, harnessing AI-driven, cloud-based technology to improve administrative workflow makes the most significant in-roads for the expense outlay. Coupled with highly trained specialists, improved automation generates more revenue for less administrative expenses in a reduced time frame.
Today, it’s imperative to accentuate the process of coding to achieve accuracy and maximize the shrinking healthcare dollar. If the ongoing education burdens a hospital- and personnel-related issues that arise with developing and maintaining a strong coding department, they may want to consider enlisting a third-party RCM partner. A trusted outside team can absorb the workflow efficiently and code thoroughly to maximize reimbursement.
To fully capturing revenue due, whether in-house or with a third-party partner, consider:
1. A paramount challenge in healthcare, specifically, hospital and healthcare systems, is staying up to date on coding with ICD-10-CM and DRG/MS-DRG codes through education and knowledge building.
2. Minimize human error and careless keying mistakes that can drastically affect reimbursement by implementing an accountability structure that rewards coding accuracy.
3. Ensure medical documentation is not only present but accurate and complete with every patient encounter. Payers request this information and will deny claims based on inaccurate, untimely receipt of documentation so be sure to include the following:
- Procedures, inpatient stays, and testing performed elaborating on medical necessity and level of care requirements,
- Physician or APP’s involvement in patient care and level of service performed,
- Tests or medical equipment ordered and corresponding results with treatment prescribed,
- Billable supplies and equipment used throughout patient treatment,
- Referrals, both incoming and outgoing, and
- Prior authorizations for all procedures and testing as required by the patient’s insurance provider.
4. Capture commonly missed tests that are billable or support treatment/diagnosis decisions.
5. Code to the highest degree of specificity and code to the diagnosis, and not necessarily the symptom.
6. Design and implement a review and audit of the documentation and coding process. Not only does this suggest areas for improvement, which directly affect the bottom line, but it also ensures compliance with government regulations and contractual insurance payer obligations.
7. Make sharing knowledge and training as it becomes available as a core foundation of organizational operations. Everyone impacted should participate in comprehensive opportunities to improve the quality of the coding and documentation program and feel a personal investment.
The most effective way to address the scalability issue that often stresses the billing function is to engage a third-party partner responsible for executing all aspects of the billing process. Utilizing a scalable, cost-effective automated solution that manages billing complexities while meeting payer criteria ensures accurate claims are submitted, paid quickly, and denials minimized.
By engaging an off-site team to provide billing support, these functions would seamlessly resolve behind the scenes:
- Charge Entry
- Payment Posting
- Credit Balance Resolution
- Contract Management
- Analytics (designed for financial management)
AR Optimization & Revenue Insights
Once a patient has been seen and a claim has been coded and billed, there are inevitably denials and rejections that prolong payment if not outright stop revenue capture. These rejected claims make up the AR and must be worked individually to ascertain the problem and then collect the necessary information before resubmission.
Denials management is often cited as an ongoing problem in many hospitals. To optimize AR, state-of-the-art AI-driven automation is available that can utilize proprietary recovery prediction algorithms to focus efforts on which denials are collectible so that energy is spent on the recovery of revenue and increase of early cash flow.
By leveraging robotic process automation to reduce write-offs and identify the next best activity through automated algorithms based on payer guidelines and procedures, a hospital can be assured the maximum revenue is collected.
When evaluating claims management solutions, consider these software functions critical to achieving the long-term goal of permanently reducing revenue loss from denied claims:
- The ability to predict recovery, including forecasting the dollars potentially available and the timeline to achieve final collections. With machine learning algorithms, unpaid claims can be evaluated on several available parameters, such as aging, payer, and modality.
- Access to predictive and deterministic criteria prioritize follow-up strategy activities to maximize and focus human intelligence efforts where they can be most effective.
- Automated claim status checks matched with the most-likely cause, i.e., integrated insurance verification and eligibility data, DRG mismatch technology, and DOS and benefits check capabilities. Once the cause is identified, appropriate changes are made, and the claim is resubmitted.
- Auto-creation of required appeal letters, if necessary.
- Automated eFax capabilities, when required.
- The ability to perform a root cause analysis through operational analytics to find where mistakes originate upstream, including insurance verification, prior authorizations, or coding problems, so that processes can be reviewed and upgraded where necessary.
- Adaptability so that if additional areas are identified as automation candidates, integration is possible with ease.
A third-party billing system’s complexity requires diligent review and follow-up when revenue is held up and the bottom line is affected. With the technology available today that harnesses AI-driven automation, machine learning capabilities, and predictive analysis, each patient encounter can be verified, submitted, and followed up in real-time. As reported in a recent Infinx Case Study, it’s conceivable to recognize a +15% improvement in 90+ days collections from AR Optimization alone.5.
Insurance Discovery to Improve Bad Debt and Collections
One thing we know for sure—throughout the healthcare spectrum, patients frequently present for care without understanding their insurance coverage or benefits. Phrases like “annual maximums,” “remaining deductible,” and “explanation of benefits” may be overwhelming to patients that are unfamiliar with insurance terms and how they’re treated within the industry. The fact that your organization has ended up with an outstanding amount is often not from misrepresentation but simply misunderstanding.
Coupled with the growth of patient consumerism and HDHPs in recent years, we see a cascading problem that can only worsen with time. The key may be an early intervention with a cloud-based Insurance Discovery Solution.
With an AI-driven Insurance Discovery Solution, these accounts are processed through an automated coverage identifier package where patient demographics, insurance profiles, and benefits are verified, and undisclosed coverage is identified. These uncompensated accounts can then be submitted to the appropriate insurance and revenue retrieved.
One such solution may be initializing an insurance discovery process that uses AI-driven automation to scour clearinghouses and insurance databases to identify undisclosed coverage. Especially useful for Medicaid and commercial insurances, an Insurance Discovery software solution uses probabilistic analytics and machine learning to identify missing or incorrect information so that patients’ coverage can be properly billed and collected.
Anytime bottom-line results are being used as a barometer of hospital efficiency, performance and the means of getting there are critical to the evaluation. By looking at RCM practices honestly and seeking clarity on improvements that can make long-term sustainable gains, reducing the administrative burdens associated with reimbursement in a third-party payer system leads to greater recognized revenue and better patient experiences overall.
Instead of accepting ongoing operational shortfalls, each of these solutions brings increased administrative efficiencies that allow for a more smoothly run operation. Overall, this provides higher cash flows, faster recovery times, reduced aging, and improved stakeholders’ margins.
To learn more about opportunities to improve hospital RCM efficiencies using technology, leveraged by highly trained billing specialists, schedule a demo at www.infinx.com.