The U.S. healthcare industry’s claims-payment system is frustrating to providers, payers, and patients alike. Inefficiency and a systemwide tendency for error wastes precious resources, worsens miscommunication and mistrust among all stakeholders, and inhibits the ability to transition to value-based approaches that achieve better outcomes. We need to rethink our industry’s disjointed and siloed approach in order to solve a very integrated problem.
Despite billions invested in achieving efficient claims payment, more than 7% of claims are not paid correctly the first time, the second time, and sometimes even the third time.¹ The remediation process costs health plans more than $43 billion annually.² Indeed, an entire sector of the industry has evolved to examine claims retrospectively, identify inaccurate payments, and reconcile over- and under-payments. This broad “pay and chase” approach increases administrative costs for the entire industry.
Not only does this waste time and money, but it also impedes providers’ ability to manage their revenue cycle effectively, erodes their confidence in payers, and creates a barrier to closer strategic alignment. Consumers are also impacted. Like providers, they have a reasonable expectation that claims should be paid accurately and quickly the first time, and that the system should be focused on delivering good healthcare–and not rectifying payments.
Ironically, the industrywide push for automation is compounding the problem with errors rather than alleviating it. As payers work to improve their claims-payment systems by automating processes, they periodically identify gaps where manual steps are still required. To bridge these gaps and lift performance, they invest in more automation. Efficiency and costs improve in those targeted areas, but inaccurate payments continue as errors cascade through the system. This drives more frustration, more manual remediation, and (ironically) more investment in automation as payers chase problems wherever they show up next. To break this vicious cycle, payers must stop thinking about automation in a siloed or point-by-point way and start tying disparate payment systems together. The drive for accurate adjudication across the claims- payment continuum can be a game-changer.
It can optimize processes, reduce costs, align systems and stakeholders, and create the conditions for bringing accurate payment for value-based payment models to scale.
The Shift to Value Complicates Claims-Payment Accuracy
Before the introduction of value-based care, claims adjudication was relatively
straightforward. With few exceptions, providers and payers engaged in fairly standard agreements that remained consistent over time. Fee-for-service was, and remains, easier to scale.
Alternative payment models have greatly increased the complexity of payer-provider contracts and member relationships. Instead of one fee schedule applied to every provider, contracts can contain myriad nuances tailored to specific providers. The rise of narrow networks has also increased complexity, because claims have to be assigned to the right agreement to be paid correctly.
Payment-automation processes among payers have not kept pace with the plurality of payment models, contractual agreements, and provider networks. As a result, administrative staff must often step in to manually interpret and translate contract terms and conditions, and connect them directly to payment and medical policies.
The ever-increasing reliance on attachments has also generated a significant need for manual rework. According to the CAQH’s 2016 “Report of Healthcare Industry Adoption of Electronic Business Transactions and Cost Savings,”³ only 6% of claim attachments are currently submitted electronically. Many are submitted outside an automated system using a manual process, such as a fax machine.⁴
As a rule, manual interventions introduce errors and increase costs. They also reduce the likelihood of timely, predictable, accurate claim payments that adhere to the terms and conditions of a payer-provider contract. Those errors are not only detrimental to the workflow of payers and providers, they can make life miserable for patients, too. When deductibles or co-pays are charged incorrectly, patients must often waste significant time “getting in the middle” to resolve claims issues.
Open vs. Closed: The Transparency Problem
To improve the efficiency of a system reliant on manual processes, the industry has invested years and billions of dollars in automating payment adjudication in an effort to simplify and streamline payment. In truth, however, the automation solution is anything but simple, and it nearly always fails to provide transparency. For providers to be partners in improving payment accuracy, transparency in automated claims payment is essential.
Once a payer enrolls a provider and signs a specific claims-payment contract, payment is usually processed correctly for a time. But errors mount as provider data evolves, providers move in or out of network, or other conditions change. Each complication requires administrative staff to step in again to manually resolve problems and connect claims to other systems that manage contracts and payment policies.
In a health plan with many tens of thousands of providers under contract for many different services, this incremental approach is barely manageable and ultimately unsustainable. The opportunity today is to go beyond automating pockets of manual activity that exist within silos along the reimbursement continuum, and to instead take aim at the root causes of inaccurate payment.
In the claims-payment world, myriad systems are used to pay claims. And in larger health plans, multiple claim, provider, and contracting systems are used to pay claims, as well as apply benefits, medical, and payment policies needed to remit accurately. This multiplicity of data and data sources fosters differences in interpretation and differences in payment.
Explanations of payment decisions are often generic and inadequate at best. Accordingly, providers are often perplexed and frustrated whenever claims are denied, delayed, or paid incorrectly. They can’t understand the source of the problem and are powerless to do anything about it other than to engage and complain to the payer.
Accurate and robust claims-payment solutions are predicated on rich provider data and transparency into the system’s underlying rules and logic. When providers can view their own data, they can help ensure it is accurate and up- to-date. When they understand how a specific claim connects to the rules and conditions of their contract, and payer and regulatory policies, they can help ensure those claims are paid correctly.
This sort of collaboration helps avoid downstream appeals and is the starting point to enhance collaboration and trust between payer and provider, not to mention the starting point for more accurate payment.
Optimize the Workflow to Automate with Accuracy
Many payers have made substantial progress automating their claims payments, achieving auto-adjudication rates as high as 80%.⁵
But auto-adjudication and accurate auto-adjudication are two different things. In many cases–and especially as payers attempt to scale VBR models–rampant errors cause costs to skyrocket, diminishing efficiency gains, and eroding provider confidence and member satisfaction.
Automation can actually compound errors when provider data and contract terms and conditions aren’t current, complete, or accurate. For example, if the payment system doesn’t know the provider’s specialty or sub-specialty, then it can’t account for that information and will likely generate an incorrect payment. Worse, such errors tend to proliferate as they’re processed through isolated systems that require manual interventions, interpretations, and cross-checks.
For claims automation to achieve accurate adjudication, rich provider information must always be up-to-date and accessible, and payers must codify the terms and conditions in the contract on the front end. Most important, all healthcare technology solutions along the continuum, from contracting to payment, must be interconnected and interoperable, ideally using a contemporary service-oriented approach.
When provider data is current and complete, and claims are filtered and assigned accurately up front, the potential for errors is reduced as cleaner (ideally, clean) claims make their way through the system. When once-siloed systems are tied together in an interoperable fashion, there is less need for manual processing at each phase; the same rich provider data is available in each system; and corrections, improvements, and updates cascade autonomously across the continuum in near real-time.
The result: Once disparate systems communicate and work together as a cohesive whole, with ready access to the latest provider and payment data, payment accuracy spirals up. This translates into real savings for payers and providers, as inefficiencies, errors, reworks, and reconciliations are cut out of the system. The payer system is transformed from automated payment to accurate automated payment, regardless of the payment model or contractual complexity involved.
Accuracy Adds Value to VBR
Accurate auto-adjudication reduces costs and frustration, and leads to greater alignment among payers, providers, and patients. The ability to engage in higher-level conversations and more collaborative approaches is essential to success in a value-based reimbursement system. But payment accuracy is the missing piece in many VBR pilots and programs.
Consider the goals of a bundled payment program and the barriers that impede success. The program is designed to produce better outcomes for patients and to generate cost efficiencies for providers and payers. However, bundled-payment contracts are much more complex than fee-for-service arrangements, and providers might be participating in a number of different contracts and networks.
Moreover, most VBR programs are manual today. Claims are paid using legacy FFS (fee-for-service) processes and a true-up usually occurs a year to 18 months after the care has been provided. But providers need access to real-time information in order to manage care that is in flight. Bringing VBR programs to scale with real-time claims payment will require new levels of intelligent automation, interoperability, monitoring, and alerting.
If a payer is having trouble administering a simple FFS contract correctly, failing to pay claims accurately and in a timely fashion, it is unlikely to be capable of managing a complex bundled arrangement. Providers will be reluctant to participate or will find the benefits of participation outweighed by the frustration and costs inherent in dealing with inaccurate and delayed payments.
In a claims-payment system where the workflow is interoperable, transparency is baked in because the same provider data is shared at all points on the reimbursement continuum; contract terms and conditions are centralized and automated up front; and adjudication is efficient, timely, less costly, and accurate. This makes it possible for payers to engage with many different providers according to different terms and conditions. In effect, it allows a payer to bring value-based payment to scale.
Ultimately, accurate auto-adjudication frees payers, providers, and patients to focus on what really matters: improving patient health by delivering the best care at the lowest cost. How can the stakeholders drive better outcomes? How can they work more collaboratively to achieve those goals? How can they bend the cost curve?
Those conversations are essential to success in a value-based system. They are also a source of competitive advantage in a world where payers and providers seek to collaborate with high- performance organizations, and consumers are making more informed market-based decisions about their own health and healthcare costs.
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¹ Morse, Susan. “If only the claims were clean: Payers, providers lose big on inaccuracies, poor workflows.” Healthcare Finance News. March 22, 2016. Accessed March 30, 2017.
³ “2016 CAQH Index Report,” CAQH, January 12, 2017, accessed April 11, 2017.
⁵ Miller, Julie. “Billing process continues to improve.” Managed Healthcare Executive. February 26, 2013. Accessed May 25, 2017.