Healthcare providers often struggle to keep up with the many tasks they have to accomplish to maintain patient care and day-to-day operations. Healthcare staff often struggle with patient onboarding, collecting reports and data, delegating tasks, utilizing data, and managing billing and claims. A lot of this work can be automated with RPA so essential healthcare workers can focus on caring for patients and saving lives.
Robotic Process Automation (RPA) is being adopted widely across industries for its ability to mimic human behavior to complete rule-based tasks. RPA even completes these tasks faster, more accurately, and cheaper than their human counterparts. RPA bots can process transactions, store and manipulate data, and communicate with other IT systems. RPA can be highly beneficial in a healthcare environment by taking over mundane tasks to free up staff for more valuable work.
50% of all healthcare providers in the U.S. will invest
in RPA in the next three years.
Healthcare Pain Points Solved by RPA
Managing Appointments
Scheduling appointments for new patients is particularly tedious due to collecting patient data such as personal information, insurance details, diagnosis, location, etc. Furthermore, scheduling the appointment must also be aligned with the doctors’ availability. An RPA bot can scan patient data in the appointment request using Optical Character Recognition (OCR), consolidate that data into a report, filter the report based on specified rules, and then connect with an appointment management application to find an available timeslot and book the appointment. The RPA bot can also notify the patient if there are any cancellations or appointment changes.
Unorganized Patient Data
A large amount of patient data is collected by healthcare systems including personal, diagnostic, and treatment data which is not always stored in a structured manner. This data can be useful for analysis, but is wasted because it's difficult to extract. RPA can extract, optimize, and organize these data points. By adding Artificial Intelligence to RPA those data points can be analyzed for valuable insights. These insights can be used to improve diagnosis and develop personalized treatment for patients. RPA is capable of handling new patient and disease data, allowing doctors and other staff to spend more time caring for patients.
Complex Insurance Claims
Managing insurance claims involves data input, processing, evaluation, and appeals. This takes a ton of time for healthcare administrators. Currently, most healthcare operations complete these tasks manually or with separate applications that can cause errors. This repetitive work can be automated and delegated to an RPA bot, as they excel data tasks such as data entry, data manipulation and storage, placing data in reports, and so on. RPA can speed up the process immensely while reducing manual errors. RPA can also identify compliance-related exceptions and prevent unnecessary payments from being processed.
Errors in Patient Billing
Patient billing requires gathering information from several bills and calculating the final amount. There are many line items on any given bill spanning multiple different departments include fees for diagnostic tests, doctors’ fees, medicine costs, food, and so on. Tracking and calculating these charges can be an arduous process and include inaccuracies. RPA bots can execute this process much faster and without mistakes thus making the settlement process seamless.
Regulatory Compliance
Healthcare providers must ensure compliance with frequently changing government regulations. Healthcare systems conduct regular compliance audits and reports are sent to authorized members for verification and approval. Typically, this process involves collecting multiple audit reports that need to collaborate with different staff which can be tedious. An RPA bot can automate this process by recording data and generating audit reports. Furthermore, the bot can share the reports with authorized personnel. RPA can not only simplify the auditing process but also detect non-compliance in reports.
