Biggest Risks in Physician Billing in 2023
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Biggest Risks in Physician Billing in 2023

Physician billing companies know a secret – keeping on top of risks in physician billing services is one of the most effective ways to keep cash flows healthy and practices functioning at their best.

That’s why we’re going to walk you through the biggest risks to physician billing right now in 2023.

Volume and Resource Fluctuations Continue
While the worst of the pandemic-related volatility is likely behind us, physician billing will still need to adjust for unpredictability. This is because physician practices are dealing with COVID-19 challenges in addition to the waste and abuse issues that were entrenched well before the pandemic. So now physician offices are dealing with yesterday’s problems on top of longer visits, more visits for therapies and early refills, COVID-19 diagnoses, and disbursement of excess pharmacy and durable medical equipment. These things make billing volatile and complex and are why many practices are considering working with physician billing services.

And while volumes have returned to normal for many, this is only part of the story. Some payers are reporting increases in deferred care, but not quite at the rates expected, while others are seeing more than projected. Labor challenges also continue to rage on, with many practices still figuring out their approach to remote work and retention and considering physician billing companies. This is happening with both providers and payers.

These issues have contributed to an increase in payment errors and billing inaccuracies in many areas. To minimize risk, providers should be ready to address these issues both on their end and on the payer side [1].

Don’t Overestimate AI in Physician Billing Services
Medical billing has been heralded as one of the best use cases for artificial intelligence (AI) in healthcare, and for good reason. Medical billing and coding rules are constantly being changed by payers, documentation requirements are always shifting, and coders are constantly inundated with new code sets. All these issues slow down reimbursement, contributing to denials and clogging up the appeals process. AI has been hit or miss in clinical areas, but since medical billing and coding are text-centric, they could hypothetically be a perfect fit, allowing smaller teams to work on claims that are more complex than their norm.

But much of the optimism hasn’t turned into reality. Organizations who’ve stepped out early into AI have had significant growing pains, especially in terms of data quality. AI models live by the principle of “garbage in, garbage out”, so that even practices that are excited about the promise of AI are learning that they have to do significant work to assess their coding practices and making sure they’re getting highly correct information from the beginning. They also need enough data points or sets to make sure prediction models are accurate since using amounts that are too small can dilute the power an analytics technology needs for success [2].

So, while the promise of AI is on the horizon, most physician practices will need to take an honest assessment of their goals, resources, and current state of tech readiness to avoid the risk of adopting solutions before they’re ready.

Upcoding in the Age of COVID Can Cause Problems
One of the more grounded and classic risks that physician offices will face in 2023 is the problem of upcoding – a problem that, if too extensive, can trigger allegations under the False Claims Act, leading to potential audits and financial penalties.

Upcoding is simply submitting a claim with higher or more extensive medical coding than the documentation or circumstances support, usually to get higher reimbursement rates than lower codes provide. A classic example is evaluation and management (E/M) codes being billed at a higher level (such as five when documentation only supports a level two). For example, telehealth fraud was found to have increased through improper billing and upcoding during the COVID-19 pandemic. State and federal regulators had relaxed restrictions to allow increased access to telemedicine, resulting in an 11,000 percent increase in virtual appointments during the pandemic and Medicare primary care visits jumping by more than 43% in the first three months of the pandemic. But in early 2021, the Department of Justice made an announcement that it had brought in over $2.2 billion in judgments and settlements from fraud and False Claims Act cases with more than 80% of False Claims Act recoveries in FY 2020 coming from the agency resolving fraud and enforcement actions [3].

But upcoding doesn’t require direct malicious intent. A practice can be at risk of upcoding practices simply because of poor training or bringing on an employee who previously worked at a less scrupulous organization. This is why many practices work with physician billing services to level out the risk.

The Risk of Audits Continues
While connected to upcoding, it’s worth looking at audit risk on its own, even if you work with physician billing companies.

Consider that the Office of Inspector General (OIG) plans on reviewing E/M services provided by physicians in the emergency department. The agency is keeping a close eye on how physician practices are being billed in 2023. While this example is in emergent settings, physician practices should take it as a warning. It can be helpful to have someone review your claims, or you might even consider working with a physician billing company to minimize risk.

Use these points as a checklist to bump against your own processes and best practices. As you move forward, you’ll find areas for improvement, but also areas where it might be smart to start looking at physician billing companies that you can partner with to improve financial outcomes. When you’re ready to take that step, start here.

References
[1] S. Mantha, “Addressing 3 pandemic-induced payment integrity challenges,” Industry Dive, 30 January 2023. Available: https://www.healthcaredive.com/spons/addressing-3-pandemic-induced-payment-integrity-challenges/640583/.
[2] J. LaPointe, “Medical Coding is the Next Stop for Artificial Intelligence in Healthcare,” TechTarget, Inc., 3 October 2022. Available: https://revcycleintelligence.com/features/medical-coding-is-the-next-stop-for-artificial-intelligence-in-healthcare.
[3] P. Giancola and C. Stedman, “Telehealth Fraud Triggered by COVID-19 Pandemic,” JD Supra, LLC, 16 February 2021. Available: https://www.jdsupra.com/legalnews/telehealth-fraud-triggered-by-covid-19-8657616/.

News in Medical Billing and Coding Services: Surprise Billing Ruled Illegal Again
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News in Medical Billing and Coding Services: Surprise Billing Ruled Illegal Again

The No Surprises Act is in the news yet again to start off 2023, promising more disruption for medical billing and coding services.

On February 6 of this year, District Judge Jeremy Kernodle issued another judgment in favor of the Texas Medical Association (TMA) – one that providers across the country will look at positively. He ruled that a revised arbitration process favors insurers and that challenges to parts of the final rule are unlawful. The president of the TMA, Gary Floyd, MD, weighed in with his opinion. “The decision will promote patients’ access to quality care when they need it most and help guard against health insurer business practices that give patients fewer choices of affordable in-network physicians and threaten the sustainability of physician practices.” [1]

The suit, which was originally filed in September, was done in conjunction with UT Health Tyler Regional Hospital and a physician and gained the support of 30 other national and state medical groups in the form of amicus briefs. Insurers have presented the idea that providers were baseless in claiming there were “early signs of a beneficial trend, where the [No Surprises Act] has furthered good faith network negotiations over reasonable rates.” The insurance trade group AHIP, stepped out in support of HHS [1].

Previously, the TMA filed a lawsuit in October of 2021 which challenged the rule with the claim that it didn’t follow direction from Congress in implementing the dispute resolution process. It was called “short-sighted” and accused the rule of driving down reimbursement rates while encouraging insurance companies to narrow networks. It was ruled against by a federal judge in February 2022.

What Is the No Surprises Act
As this piece of legislation continues to pop up in the news, providers considering the future of their medical billing and coding services will benefit from understanding it from the beginning.

The term “surprise medical bills” refers to the situation in which insured consumers receive care from an out-of-network provider like a hospital, doctor, or provider they didn’t choose, inadvertently triggering billing they didn’t authorize. This has been found to happen in around one out of five emergency room visits. On the non-emergent care side, about 9%-16% of in-network hospitalizations have been found to potentially include unexpected bills from an out-of-network provider like an anesthesiologist the patient had no hand in selecting. These bills are an issue for patients because they often result in significant financial burden through denials or out-of-network cost sharing. Consumers are also subject to “balance billing” from providers that are out-of-network that don’t have contracts to accept discounted payment rates from a health plan. The bill potentially applies to around 10 million surprise, out-of-network medical bills each year.

This most recent news addresses the arbitration process which allows for the determination of surprise bills through negotiation between providers and insurance plans and, if negotiations are not effective, the use of an independent dispute resolution (IDR) process.

But the dispute resolution process has remained a challenge, with providers issuing more submissions for appeal than was expected. Providers have made such heavy use of the IDR process that the system has become clogged and in response, the Biden administration has raised fees for engaging in the process. In December of 2022, the Treasury Department and the Department of Health and Human Services (HHS) made a significant increase in the resolution fee, increasing it to $350 from $50 per party for each disputed claim. The goal was for the fee to be a deterrent to use. These charges went into effect January 1, 2023 [2].

Patient Impact of the No Surprises Rule
Providers who care about their medical billing and coding services and work with medical coding outsourcing companies are keeping a close eye on how the bill could impact patients. This is because patient perception impacts how they choose providers and, as more patients are aware of what the practice of surprise billing can mean for them, they will predictably weigh that in their decision-making. For example, before regulation became more intense, private equity firms were taking advantage of the opportunity to bill out-of-network services from tens of thousands of physicians which they used to staff hospitals. This included the emergency department, which left patients caught in the middle.

Impact on Provider Medical Billing and Coding Services
So, what does all this mean for providers? It means a rocky future for surprise billing and arbitration, complicating billing strategies for providers across the country. Many leaders will not only have to consider the impact of their contract negotiations, but also how their approach to medical billing will intersect with future changes in the legislation. Some providers who have already considered medical coding outsourcing companies are also looking to outsource medical billing to relieve themselves of challenging decisions as the legislative environment continues to evolve. If you are in this position and want to talk more about how the No Surprises Act could impact your organization, contact us today.

References
[1] J. Emerson, “Federal judge rules against HHS — again — over surprise-billing arbitration rule,” Becker’s Healthcare, 7 February 2023 . Available: https://www.beckerspayer.com/policy-updates/federal-judge-rules-against-hhs-again-over-surprise-billing-arbitration-rule.html.
[2] L. Santhanam, “How this law reshaped medical billing, and what challenges remain for patients,” NewsHour Productions LLC, 20 January 2023. Available: https://www.pbs.org/newshour/health/how-this-law-reshaped-medical-billing-and-what-challenges-remain-for-patients.

Are You Moving Too Early on AI in Medical Coding Services?
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Are You Moving Too Early on AI in Medical Coding Services?

Artificial Intelligence (AI) solutions have been hyped up in everything from customer service to disease diagnosis – and the healthcare revenue cycle hasn’t been exempt.

You’ve likely heard about how AI is a great fit for the healthcare revenue cycle – revenue cycle is a treasure trove of data and workflows that require manual input. Many healthcare leaders have looked specifically to medical coding solutions, asking whether AI could be beneficial there.

While AI is a tempting solution, anyone considering applying AI to their medical coding services should take a step back and consider the idea that while AI might show amazing promise, it might be a bit too early to consider for the healthcare revenue cycle. This means that making a decision too soon might be difficult to reverse.

Data Quality Is a Challenge
An ancient truth of data applies even more to AI – “garbage in, garbage out”. This lesson has emerged clearly in clinical analytics, where organizations have learned that their results depend on clinicians feeding clean and comprehensive data into their EHRs. They’ve learned that if information was entered incorrectly, it flows to other people using the data, comprising data quality and record integrity [1].

This means that the same issues with inaccuracies that you might have had in the past will persist even under an AI solution. This includes inaccurate information, but also gaps in coding data you might not yet have resolved.

No matter how good your AI models are, you won’t get the results that you’re looking for if your data quality isn’t where it needs to be – no matter what quantity of data you feed into it. Any organization evaluating AI will need to answer some tough questions about their data governance policies and strategies before even considering investing in an AI solution. Skip this step at your own risk.

Trust Should Be a Priority
AI has a particular problem with trust and it’s especially acute in healthcare. Consider some recent commentary on “the black box problem” in AI and machine learning.

“There is much confusion about the black box problem of AI. Many AI algorithms are not explainable, even by the programmers who created them, as the code evolves over several virtual generations and ends up as a complex code whose working is opaque to us humans. We are unable to see the ‘rough work,’ only the final answer. Thus, especially in the critical field of healthcare, there is a big doubt whether we can trust AI.” [2]

It’s worth asking if you can find a solution you trust enough to implement in your revenue cycle.

Security Is an Issue
Healthcare as an industry has led the pack in identity theft for years now, and while many organizations have made significant progress in their cybersecurity efforts, hackers and cyber criminals still find healthcare extremely appealing. For any organization that is still struggling with security risks or that has just found their footing, AI solutions for medical coding could derail present or future progress.

AI runs on your data networks, which means it’s inherently vulnerable to security risks. Consider its differences from traditional software. Vulnerabilities in traditional software generally flow back to issues with design and source code. In AI, this extends to images, text, audio files, and whatever data that was used to train and run models. Your security team will need to be aware of an entirely new level of threat to keep your data safe from malactors [3].

You’ll Still Need People
The way some people discuss AI in the revenue cycle, you’d think it was as simple as flipping a switch and enjoying the benefits of increased efficiency and reduced long-term costs. The truth about any AI solution, though, is that while they’ve come a long way, AI still needs some level of human surveillance. While AI can reduce your need for certain positions, it will also launch you into a new phase of hiring and recruitment.

You will need an AI team to manage your projects. This team will require a range of skills and backgrounds and need to operate at high levels of collaboration for you to get the results you’re looking for. Gartner has estimated that half of IT leaders will struggle with any AI project they have beyond the conceptual level – partly because the data scientists they have are doing too much [4]. This is largely because of a talent shortage in other roles. Consider that AI itself is dealing with a labor, skills, expertise, and knowledge shortage – an issue that stands out as the number one barrier to adoption for many organizations.

Ethical Issues Still Exist
Ethics are paramount at all levels in healthcare, revenue cycle included. Unfortunately, incorporating ethics and morality into AI is still a struggle. This is especially true as the importance of social determinants of health (SDoH) continues to grow for healthcare decision makers. AI still might not be able to make considerations that are specific to certain situations.

Risk of Failure
Perhaps the greatest risk of jumping too early into AI for a medical coding solution is what happens if the solution doesn’t work out.

As things stand now, if your AI solution fails, you’re left with little recourse, either experiencing a severe interruption in your revenue cycle while you rebuild or having to quickly hire and train new human staff or possibly even scrambling to sort through medical coding companies and medical coding solutions to help you get moving again.

While we believe in the potential for AI in medical coding services, we also believe that now might be too early for most organizations to take a step. To learn what medical coding services could be a smarter choice for you as AI finds its footing, start here.

References
[1] J. Bresnick, “What are the barriers to clinical analytics, big data success?,” Health IT Analytics, 30 July 2014. Available: https://healthitanalytics.com/news/what-are-the-barriers-to-clinical-analytics-big-data-success.
[2] J. D. Akkara and A. Kuriakose, “Commentary: Is human supervision needed for artificial intelligence?,” Indian J Ophthalmol, vol. 70, no. 4, p. 1138–1139, 2022.
[3] B. Dickson, “Machine learning security vulnerabilities are a growing threat to the web, report highlights,” PortSwigger Ltd., 30 June 2021. Available: https://portswigger.net/daily-swig/machine-learning-security-vulnerabilities-are-a-growing-threat-to-the-web-report-highlights.
[4] L. Goasduff, “How to Staff Your AI Team,” Gartner, 15 December 2020. Available: https://www.gartner.com/smarterwithgartner/how-to-staff-your-ai-team.

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