Payers are at greater risk than ever before for provider directory errors and can benefit from automating their provider data. Starting in 2022, insurers will be responsible for an additional $20 billion in claims per year due to new standards for provider directory accuracy set by the No Surprises Act. Much of this comes from struggles with maintaining up-to-date and accurate provider directories. A 2018 Centers for Medicare and Medicaid Services study estimated that 50% of provider directory data may be inaccurate for Medicare Advantage plans.
If payer organizations don’t comply with the No Surprises Act, they could face risks and penalties. Data management compliance risks associated include providing incorrect contact information, errors due to syntax and standardization issues, delays in updating provider profiles, and human error driven by manual processes in data workflows. Unforeseen monetary losses and penalties will occur unless payers consider automating provider data now. Manual entry and the standardization of data add burden and costs to administrative tasks. They also distract other key areas of healthcare operations—including driving better member experience.
What is the potential for automating provider data in the healthcare industry?
According to the McKinsey Global Institute, nearly 30% of employee activities could be automated, representing a cost savings of over $16 trillion. For the healthcare industry, there is a potential to automate and streamline 36% of manual activities. Including automation in data management strategy can save healthcare organizations money, free up employees from tedious tasks, and provide better outcomes and a better member experience.
Payers receive most provider data updates via provider rosters, which are then checked for accuracy and transformed into a usable format by complex provider data workflows. Homegrown processes can solve some immediate problems, but they can also create errors and distract employees from more important tasks and goals for provider roster management.
3 additional benefits of automating provider data:
- Efficiency
The process to update provider directories is currently very manual across the healthcare industry. With new requirements under the No Surprises Act, payers are now required to update provider directories in less than 48 hours of receiving updates via new provider rosters.
However, data intake, reporting, and updating of reports involve many people interacting with the data throughout the process. The revision cycle with multiple stakeholders can be lengthy, and data comes in different formats that require standardization. The data update process can take not just days, but sometimes weeks or months. With automated processes, payers can uphold their service standards and have accountability for their provider data. Additionally, streamlined workflows remove human error or time on day-to-day manual tasks. Through automation, the data speaks the same language and becomes more standardized.
- Risk Mitigation
The cycle times are long to update provider data within payer directories, with middling accuracy results. These delays, whether days, weeks, or months, bring penalties and risks that payers will take on if or when the No Surprises Act deadlines aren’t met. Based on Orderly Health’s ROI analysis models, payers are encountering millions of dollars per year in out-of-network risks.
Under the new legislation, payers are responsible for out-of-network fees if they were caused by inaccurate data. By putting automated, reliable software solutions in place, payers can have more visibility into and control over provider data management. Health insurers can use automation to get data transfer results within minutes, instead of days or weeks.
- Ability to Scale
Lengthy, manual processes can become a barrier to scaling your business. This is especially true when teams add new providers, increase the size of data sets, or try to power through complex processes quickly. Improving workforce efficiency can help manage time and focus on key priorities that drive better member experiences and outcomes. Automation technologies can enable team members to focus on business insights and trends, which will amplify the long-term value of the process and ensure that it can be scaled effectively.
How much can process automation reduce operational costs?
Studies by Mckinsey show that no matter the industry, automation proves to save time, money, and effort for operations. Organizations can automate more than 69% of data processing and automate 64% of data collection activities. So, what are the operational cost savings? New digital tools, such as provider data automation software, will enable payers to reduce their operational costs by up to 30% within five years.
Should payers use external suppliers for automation?
Although healthcare is moving to become more digital, it doesn’t mean there is a streamlined and convenient in-house solution for provider data automation. Legacy technology systems often don’t have this functionality built-in. It is necessary to work with a reliable automation software partner to ensure the solution can be scaled, operations are streamlined, and additional labor costs are prevented.
The nature of provider data automation requires comprehensive and adaptable solutions. The design of the automation system should take into account the needs of key stakeholders from different departments, such as technology, operations, compliance, and executive management. Typically, software automation partners offer guidance, support, and solutions for implementing and managing change at this level.
Healthcare is making more progress toward digital innovation and change, including making processes more efficient and evaluating homegrown processes and solutions that take a lot of time. Healthcare as a sector is finding more ways to be efficient and more automated, to allow teams and organizations to focus squarely on their members and access to care. Through automating provider data, payer organizations can prime their processes for scale while reducing risk and cost to the bottom line.