When and where to use RPA, business rules engines, or APIs in payer automation priorities.
No matter your payer automation priority, there is a solution to meet the need. Knowing that one technology can’t fit all, we break down the value and appropriate choice of robotic process automation (RPA), application programming interfaces (API), and business rules engines depending on the use case.
What Forces are Pushing Automation for Health Plans?
Everything from the pandemic and job losses pushing more members into Medicaid and ACA plans to competition by commercial plans, coupled with increased regulation and consumer expectations, are driving the need for more automation and greater efficiency in health plan operations.
Efficiency gains and operational process accuracy will free both budget and resources to focus on building towards growth and business objectives.
Aligning the Right Automation Solution with Two Payer Priorities – Claims Processing & Provider Credentialing
Automation solutions should be aligned to the right business problems health plans face. Advancements in automation have everyone excited about possibilities, however if an organization tries to solve too many problems with one technology, the outcome isn’t always as expected. It’s key to understanding the technology options available and which are appropriate to address each type of challenge or need.
When is robotic process automation the best choice for automating payer operations?
- RPA is best for high-volume, highly manual and repetitive processes. It is best to think of these solutions as a digital worker capable of working 24/7 without making any errors.
- Payer processes like claim audits and provider credentialing are particularly good candidates for an RPA solution:
- Claim audits: Typically involves five to six repetitive steps, including creating a sample, checking the incoming claims file for data consistency, logging into multiple systems to check for data, and compiling the results.
- This process is tremendously manual and prone to errors in most health plans.
- Regulatory checks make those errors costly.
- Mandatory provider credentialing: Also entails a high-volume and highly repetitive process, requiring confirmation across several data sources.
- SDLC Partners’ RPA solution for provider credentialing was able to reduce verification cost by more than 30% and significantly improved the accuracy of claims audit resulting in better quality. Read Case Study
When is a business rules engine the best choice for automating payer operations?
- Business rules engines are a viable option for payers to upgrade complex business processes when they are manual or processed through legacy systems that are causing inefficiencies.
- Strong candidates for building a configurable business rules engine are Medicaid and Medicare enrollment processes that involve complex state business rules when enrolling or disenrolling members.
- Think of the business rules engine as a filter in front of the payer’s legacy systems that handles all complexities of business rules and error handling
- SDLC Partners’ business rule engines have been able to modularize and effectively filter out more than 90% of errors in-state enrollments files before passing it on to the legacy systems. Read Case Study
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When is an API the best choice for automating payer operations?
- CMS has been pushing interoperability and FHIR APIs for payer and provider interfaces for few years now. They specifically mandated patient access APIs and provider directory APIs in 2020.
- While the CMS requirements and recommendations might not seem overarching, yet, health plans should proactively develop an API strategy that addresses all possible interfaces, including manual and partially-manual data exchanges.
- As you formulate your API strategy, consider these steps as you build your roadmap:
- Perform data and process assessments to identify all payer/provider interactions across all business processes
- Create a detailed data dictionary and master data inventory of all payer-provider interactions
- Complete a paper-based mapping exercise, illustrating your master data inventory and existing FHIR resources
- Identify all manual and partially-manual data transfer points across systems where APIs could streamline
Automation Traps to Avoid
- Automating a poor or ad hoc process will derail your automation success quickly. Work with process engineers to assess and streamline a more perfect process before automating.
- Deploy RPA bots after any major system upgrade. Bots may need to be reconfigured if there are changes to login or user interfaces.
- Be sure to participate in user acceptance testing and not just accept third-party results. Because the process was conducted manually, previously, those same employees should validate that the automation solution provides the right level of performance.
- Address automation security to create the right controls for bot access and data exchanges.