In a cardiology practice today, there are often highly technical procedures, surgeries, and advanced testing performed. However, when it comes to the business of revenue collection, many offices are still running at half speed.
The 2019 CAQH Index on Conducting Electronic Business Transactions reported that only 70% of providers are using a fully automated process for claim status inquiry. Almost unbelievably, only 13% of practices have an electronic prior authorization system in place.
With fee schedules stagnant or declining, now is the time to consider adapting to the rise in advanced automation and Artificial Intelligence (AI) in the healthcare payment lifecycle. With AI-driven solutions, cardiology practices can focus their administrative support on higher-level functions, such as the patient experience, that benefit the bottom-line and better position the practice for the value-based care criteria.
Using AI to Adapt in 2020
Successfully bringing AI into the cardiology payment lifecycle means revisiting current practices and transforming the way we do business. This is best accomplished through cloud-based technology, and bi-directional integration using a Health Level 7 (HL7) or Application Program Interface (API) linked directly to and compatible with your current EHR/EMR system.
Through machine learning capabilities and predictive analytics, tech-enabled processes save time and money, and reduce claim denials and rejected requests for reimbursement. This technology embeds all Patient Health Information (PHI) in layers of security that are Electronic Data Interchange (EDI) compliant and stores the data on the cloud using 64-bit and 256-bit encryption that guarantees 100% HIPAA compliance. Here are four ways AI can improve cardiology reimbursement:
1. Wrangling Prior Authorizations
Industry-wide, there is acknowledgement that prior authorizations (PAs) are an unreasonable burden on hospitals and providers. Whether the patient arrived without a PA from the referring provider or self-referred, PAs have long been considered problematic and time-consuming, often taking several hours to several days to complete.
By utilizing an AI-driven PA solution, a cardiology practice can streamline the entire process and facilitate a more efficient scheduling encounter that reduces cancellations and reschedules. On-time approvals are achieved using blended automation that provides a comprehensive answer to the PA dilemma so that submissions are sent in real-time with results available almost immediately.
2. Issuing the Appropriate CDSM Compliance Certificates
Whether you are performing the advanced testing or are the ordering provider, your cardiology practice will be affected by the Clinical Decision Support Mechanism (CDSM) mandate. With the growing number of Medicare patients due to an aging population, this soon-to-be mandatory component will significantly impact revenue when claims are missing the required compliance certificate.
The Centers for Medicare and Medicaid Services (CMS) have selected qualified vendors who offer substantial automation solutions to the CDSM issue. By selecting a CDSM vendor that utilizes AI, your practice can obtain CDSM consult certificates both proactively and reactively, if needed, making the billing cycle complete.
Special Note: The CMS recently updated the mandatory implementation date from January 1, 2021, to January 1, 2022, recognizing the complexity of the program required additional time for training and technological workflow challenges.
3. Optimizing the A/R Function
When you ask how AI can help cardiology, you have to look at the denials management process. A significant number of claims are rejected for a variety of reasons. According to the Medical Group Management Association (MGMA), between 50% and 65% of denied claims go unchallenged due to lack of time and/or understanding on how to proceed, and the revenue is lost completely.
Using tech-enabled and AI-driven automation, you can manage them quickly and accurately to maximize reimbursement. This also allows for operational improvement as data analytics will point to key areas needing attention to improve revenue capture.
4. Discovering Undisclosed Insurance Coverage
In 2016 and 2017, hospitals and healthcare providers lost well over $38 billion through uncompensated care. Often from undisclosed coverage or uninsured care, up to 10% may be collectible if you had access to the pertinent information instead of landing in collections. Now you can use AI-driven technology to glean the information from insurance industry clearinghouses and find coverage that exists including Medicaid and commercial insurances.
With improved automation, cardiology practices are better equipped to meet current challenges. And while someday there may be massive structural changes to the system, for the foreseeable future meeting the requirements of the insurance companies seems the expedient route to guarantee maximum reimbursement reaches the bottom-line.
Contact us to learn more about AI-driven revenue solutions to improve your bottom-line for your cardiology practice.