Workforce shortages continue to plague state health agencies, and with Medicaid redeterminations well underway, the situation has now reached a tipping point. This is a time in which agencies will need to start thinking differently about how to best manage workloads. RPA is one way to help remove some of the burden from existing staff.
RPA stands for Robotic Process Automation and in the context of state health agencies facing workforce shortages, RPA can offer a practical solution for managing workload and improving operational efficiency. By automating repetitive and routine tasks, RPA can help reduce the burden on existing staff, freeing up their time to focus on more complex and high-value work.
For example, state health agencies often handle a significant amount of repetitive data entry and processing, which can be time-consuming and prone to errors. RPA can automate these tasks, allowing digital assistants to enter data accurately and consistently, reducing the likelihood of errors or discrepancies in customer records and other data by reducing the need to rekey/rework errors further enhancing overall productivity. Saving what could be thousands of hours per month on these tasks allows staff to refocus their energy and reduce backlog.
Moreover, RPA can help improve the speed and quality of customer service. By automating processes such as retrieving customer information and updating records, digital assistants can quickly and accurately process customer requests, reducing the wait time for customers and improving their overall experience.
RPA does not eliminate the need for headcount, but it can dramatically reduce the time spent on redundant tasks. If thousands of hours are freed up each month, agencies can more easily prioritize more complex tasks for their staff and high-quality customer service.
In our own consumer assistance center, GetInsured will be leveraging RPA to begin processing data matching inconsistencies (DMI). A data matching inconsistency occurs when there is a discrepancy between the information provided by an individual and the data available in the records of a government agency, for example. In the context of health insurance subsidy eligibility, it typically involves the information provided by an individual on their application for health insurance subsidies not aligning with the data available from other sources, such as tax records or employment information.
If a data matching inconsistency is identified, it can have an impact on the individual’s eligibility for health insurance subsidies. For example, if an individual underreports their income on the subsidy application compared to their income reported in tax records, it could result in an overestimation of their eligibility for subsidies. Consumers are required to submit documentation to help resolve any DMIs related to their application.
As documents are submitted, digital assistants will read them using optical character recognition (OCR) to extract data elements to process and clear the DMI. This frees up time to allow Customer Service Representatives to focus on direct customer interaction and maintain a fast speed to answer.
As the workforce shortage continues across the country, RPA can offer a valuable solution for state health agencies facing workforce shortages, helping to reduce the burden on existing staff, improve customer service, and reduce costs. By automating repetitive and routine tasks, agencies can focus on more complex and high-value tasks, improving operational efficiency and ultimately benefiting customers and taxpayers.
Learn more about how GetInsured can help your agency take advantage of RPA.
