Improve DME Reimbursement Through Targeted Automation
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Improve DME Reimbursement Through Targeted Automation
Today, more than ever, Durable Medical Equipment, Prosthetics, Orthotics, and Supplies (DMEPOS), impact a significant number of patients in many specialties while also attracting a lot of scrutiny from insurance payers. Through the entire healthcare payment lifecycle — insurance verification to prior authorization to coding and claims submission — the DME provider must ensure that all insurance payer requirements are met or face the loss of reimbursement.
This requires that DME providers work closely with referring providers and the patients, as well as the insurance payers, in what can only be described as an overly complex third-party payer system unique to healthcare.
As the reimbursement landscape continues to change, impacted by an aging population and insurance programs that shift the responsibility more towards the patient, meeting the challenges will include automating billing functions to ensure accuracy and speed up payment.
5 RCM Areas to Automate
In this discussion, we want to first look at the areas where there can be a negative impact on the revenue stream if requirements aren’t met or incomplete information is submitted. In the following section, we give a process-by-process analysis of automation opportunities, third-party support, and, when feasible, artificial intelligence (AI) software with machine learning capabilities, that increase efficiency and improve the bottom line.
Critical to a strong foundation, the purpose of insurance verification is to gather and confirm precise patient eligibility information, including co-pays, co-insurance, deductibles met and remaining, and out-of-pocket maximums. While this automated process has more industry-wide acceptance with, on average, according to the 2020 CAQH Index, 84% of organizations using at least partially automated workflow, there are still efficiencies to be gained12020 CAQH Index, Closing the Gap: The Industry Continues to Improve, but Opportunities for Automation Remain. CAQH Explorations. January 2021. https://www.caqh.org/sites/default/files/explorations/index/2020-caqh-index.pdf. Accessed on February 2, 2021..
The problem, however, is that patient information is only verified and updated at the outset of new equipment rental/delivery, leaving subsequent renewals, repairs, maintenance, ongoing supplies, etc., subject to a reduced reimbursement or outright rejection.
When filing for Medicare or most commercial insurances, the list of equipment needing preauthorization is extensive and includes the full spectrum of DMEPOS. At this time, the majority of prior authorizations are prepared and submitted through a manual process that is time-consuming and subject to errors. Additionally, each piece of equipment must also be reauthorized annually.
Part of competing in today’s healthcare market means reevaluating the prior authorization process used by all DME providers and making changes that will allow for electronic data management and predictive analytics to improve the overall business.
Medical Coding and Medical Billing
Before any claims can be submitted and the billing process commenced, each piece of equipment has to be coded using the HCPCS coding system, along with all Modifiers that apply. This is for all rentals, capped rentals, maintenance and servicing, replacement and repair, and elections to purchase (for complex wheelchairs only).
As an example:
To bill for a CPAP machine on a first month capped rental that has documentation available to support medical necessity, you would code:
- HCPCS Code E0601
- RR – Rental
- KH – Initial Claim, first month rental
- KX – documentation available to support medical necessity
This machine is billed monthly and must be coded and billed monthly with changes to the modifiers as appropriate. Also, all eligible supplies need to be coded as well.
Luckily, modifiers are not required for supplies like syringes, face masks, or ostomy bags.
A/R and Denials Management
Once claims have been submitted, it is up to the insurance payer to either pay the claim or deny it for needing additional information or being incorrect. The problem is that according to the Medical Group Management Association (MGMA) at a recent healthcare business management symposium, up to 65% of denied claims go unchallenged and are left to expire thereby losing the revenue completely2Graham, Tina. You Might Be Losing Thousands of Dollars Per Month in ‘Inclean’ Claims. Medical Group Management Association, Billing & Collections, Reimbursement, Insight Article. February 1, 2014. https://www.mgma.com/resources/revenue-cycle/you-might-be-losing-thousands-of-dollars-per-month. Accessed March 12, 2021.. Often due to a lack of time and/or understanding, more than half of denied claims are never pursued.
Of the claims that are reworked and resubmitted, the MGMA estimated that the cost to the provider is approximately $25.00 per occurrence which adds up quickly with no guarantee that a resubmitted claim will be paid.
No matter how careful, it seems there is always a percentage of claims (+/-10%) left at the end of the collections process that is simply deemed uncollectible. Often this money is either written off or the patient is referred to a collections agency where the fees run over 50%.
With healthcare margins thinning, that can be the difference between a healthy organization or one that is struggling to make ends meet.
With each of these areas a potential cause for concern and many facets handled by manual and repetitive processes, let’s take a look at each one, in turn, to see how applied automation can alter the overall outcomes.
Expect Better Financial Outcomes
Unique to healthcare, third-party financial responsibility adds a layer of complexity that is often confusing and deliberately complicated. Using automation and AI technology, hospitals, outpatient facilities, doctors, and DME providers can now proactively engage insurance payers and meet them on a more level playing field.
Through automation and AI-driven software, insurance plan requirements can be updated and maintained with data accessible and actionable in real-time, creating up-to-the-minute results that positively impact a patient’s ability to acquire needed medical equipment, such as oxygen, mobility and pressure-reducing support surface devices, or CPAP machines.
Securing the Foundation – Insurance Verification
With an automated insurance verification solution that works in concert with your existing information system, you can authenticate the patient’s available benefits, as well as discover remaining deductible amounts, equipment that is covered, and annual maximums reached.3Wilson Pecci, Alexandra. How Automating Patient Insurance Verification Reduced Denials. Healthleaders, Analysis. January 22, 2019. https://www.healthleadersmedia.com/finance/how-automating-patient-insurance-verification-reduced-denials. Accessed January 23, 2021. Done at each patient encounter, this will benefit DME organizations by improving reimbursement capture and bottom-line results with these three takeaways:
- Alleviating the administrative burden at the time of ordering equipment
- Prevent errors and reduce denials
- Allow staff to be reallocated to more patient-centric roles
Concurrently, using an integrated, automated, and comprehensive platform solution would allow patient eligibility details to also inform patient pay estimates and prior authorization requirements in advance.
DME Prior Authorizations
The single most significant area in need of modernization is utilization review and prior authorizations. The 2020 CAQH Index states that on average, only 21% of healthcare providers have fully adopted an electronic solution for managing prior authorizations which means that countless hours are being spent on hold with insurance payers trying to obtain approvals or following up on rejected requests.4Ibid., 1.
Using AI-driven software that is integrated bi-directionally, the DME provider’s billing system or medical records are accessed through cloud-based technology. As soon as a patient’s equipment order is input, anything requiring prior authorizations can be electronically identified, provider/facility detail, patient demographics, and test/diagnosis information can be collected, and an approval request submitted in real-time to the insurance payer portal.
Accessing continually updated insurance information clearinghouses storing thousands of insurance groups and plans, AI-assisted software with machine learning capabilities would electronically determine the prior authorization parameters for routing the request. Any complex or emergent prior authorization requests would be quickly handled by the human intelligence factor in the form of highly trained and certified specialists.
Here are some of the benefits that could be recognized:
Initial Processing — Guided processes are monitored for the key identifiers to initiate prior authorization approval. Matching ordered equipment with constantly updating insurance preauthorization requirements, the system stands ready to gather the required information and submit the request in real-time.
Continual Follow-Up — Once the prior authorization approval is submitted, electronic follow-up occurs 24/7 until a final resolution is obtained. If additional information is required or an appeal is necessary, the DME provider and the patient are notified immediately so that a response could be crafted and submitted as soon as possible.
Dashboard Notifications — Waiting for insurance payer responses has historically been a time-consuming affair that took hours of follow-up and burdensome administrative effort. With an interactive dashboard, today’s automation and AI-driven software gives a complete snapshot and clarity on all active prior authorization requests so that DME providers can have their questions answered immediately and follow-up can occur as necessary.
Analytics and Reporting — Bringing full transparency to future operations, timely analytics and reporting can pinpoint breakdowns in efficiency or areas needing improvement.
Coding and Billing for Efficiency
With the complexity of coding required for DME equipment, staffing issues within the billing department 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.
One solution is to consider a third-party billing partner that brings the expertise required and has the scalability to meet the workflow regardless of internal staffing issues.
DME A/R and Claims Denials
The revenue cycle concludes with the management of claim denials. By leveraging AI technology with machine learning capabilities, denials can be managed effectively, and revenue captured that may currently be abandoned entirely.
When claims are denied, they are often passed through to the patient and are a major source of “surprise” billings. Utilizing an automated AI-driven denials management solution, DME providers can significantly reduce the high number of claims that are returned or rejected, further reducing the reported “surprise” billings that rightfully upset patients.
Utilizing an automated solution with machine learning and predictive intelligence, denials would be assessed, prioritized, and next steps determined. Without delay, they could then be appealed and tracked for follow-up in real-time with certified specialists available to tackle the hard-to-collect outliers. Teaming with an innovative leader in the automated patient billing space with AI and machine learning capabilities and a scalable workforce of highly trained specialists allows your organization to focus on providing the best patient experience.
Insurance Discovery – Upfront or Post-Visit
Nobody wants it to happen, but sometimes balances have to be written off as uncollectible or charitable care. But what if there were a way to look for undisclosed insurance coverage for patients either during the initial patient access process or as a final precursor to collections? We’re talking about coverage that they don’t even know exists like secondary coverages and Medicaid.
Once the patient’s information is downloaded into a proprietary insurance discovery system, the software completes deep data mining and probabilistic analytics to glean, check, and double-check the data. Access to this information comes from a sophisticated network of clearinghouses, direct payer connections, and is supplemented through a network of public and private databases.
Collectively, this information is then used to identify undisclosed coverage and socio-demographic identifiers to correct and update claims so that they can be processed by a team of highly qualified billing experts and plans can begin to pay.
Changes in healthcare are going to continue and being prepared by utilizing the available technology to improve reimbursement as well as the patient’s experience will position your DME equipment organization for the future. By utilizing AI technology with machine learning capabilities, your DME organization will be able to streamline administrative functions freeing up your employees to educate and guide patients and improve their satisfaction and loyalty.
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