Top RPA use cases in healthcare


According to a recent Deloitte RPA report, increased productivity and improved customer experience were the top priorities for organisations adopting Robotic Process Automation (RPA). RPA is considered by organizations, across different industries, as an exploratory first step into the world of AI. RPA makes use of virtual workers, or software robots, and mimics human users to perform business tasks. It has the ability to handle high-volume of simple and complex data at great speeds. Typical business objective of this program ranges from automating mundane administrative tasks to using bots for intelligent decision making.

With the rise of disruptive technologies, escalating costs due to legacy applications and, a paradigm shift towards patient-centric services, the healthcare sector has started to adopt RPA and now is at the forefront of making the delivery of healthcare services more efficient, effective and affordable. Healthcare has traditionally been data-driven, with a large amount of data being collected manually through forms, contrasting internal IT systems, and a myriad collection of documents and databases.

Healthcare providers and professionals seek different ways to enhance patient interaction and outcomes, save costs, improve productivity, and increase operational efficiencies. Here are the top RPA-healthcare use cases in Payer & Provider sectors:

RPA use cases in healthcare

Payer use cases

  • Claim filing: Typical claim processing is a time-consuming activity that involves repetitive tasks and gathering of vast amount of data information from different sources. With predetermined rules, RPA can extract structured and unstructured data, update systems and identify exceptions. The automated process reduces average transaction times from 12 to 2 minutes.
  • Member enrollment: The need for healthcare insurance keeps growing every year. Payers have to process a huge influx of new member enrollment requests. It is a manual process that involves a tonne of paper work, the physical movement of paperwork, and tremendous attention to detail through human eyes. RPA can automate the entire process seamlessly, and bring down the processing errors and incomplete applications; subsequently reducing the turnaround of enrollment cycle times.
  • Provider network management: Payers have to spend an equal amount of time and effort in managing the healthcare providers they collaborate with. Bad provider information could impact operational inefficiencies, like low auto-adjudication rates, wasted time and dollars in terms of tracking provider details, etc. These are typically caused due to errors or missing information, like phone numbers/incorrect address in provider records. RPA can reduce the cost of maintaining provider data and improve overall integrity.
  • Contract management: It is not just about adding a new provider or renewing the contract of an existing provider; payers process large volumes of data in both structured and unstructured formats. Search/retrieval, relationship management, and reporting are some of the areas that face challenges due to highly time consuming and error prone manual processes. With OCR (Optical Character Recognition) enabled RPA and IPA (Intelligent Process Automation), process efficiencies can be achieved in these areas.

Provider use cases

  • Revenue Cycle Management (RCM): RCM in healthcare plays a pivotal role in maintaining the long-term feasibility and profitability of healthcare providers. Revenue cycles need to be optimized by reducing the time involved between patient services delivery and payments. RPA can help reduce claim denials and claim resolution timelines, get rid of manual errors, and enable faster processing of transactions.
  • Claims processing: The processing of claims submission is automated to only a certain extent. At a basic level, automation is used to post transactions, provide general ledger information, and pay out funds to claimants. RPA can optimize these kind of transactional and rule-based work continuously and at 100% accuracy level. Hospitals can automate their health plan processing through RPA and considerably reduce the claims backlog.
  • Medical billing: The medical billing process, performed by healthcare providers, is a multi-step process that involves the use of medical codes, claim processing with payers, and recovery of out-of-pocket expenses from the patient. It requires the collaboration of both internal and external stakeholders, with the manual collection of data from each stakeholder. RPA can combine all of the sub-processes performed by each stakeholder into a seamless, centralized process. Medical billing service providers, with the help of RPA, automate the billing process for their healthcare provider customers, which will result in significant time savings.
  • Expense payment processing: The reimbursement received from insurance payers has to be accounted properly to the appropriate patient accounts in the billing system. It involves a lot of paperwork and manual cross-checking of information from different data sources and accounting systems. RPA can be used to integrate with existing applications, extract the relevant data, perform bulk payment posting and reconciliation tasks, trigger responses, send payment reminders automatically, and communicate across myriad systems.

The road ahead

Medtech startups and companies are driving Innovative ideas in healthcare and pushing the envelope as hard and as fast as they can. RPA can certainly be considered the torchbearer of this endeavour. RPA implementation takes a fair degree of investment in time and effort, however, the outcomes are beneficial for all; healthcare organizations can do away with some of the manual processes that slow down healthcare delivery, doctors/hospitals can focus on quality patient care, much quicker clinical trials and drug approvals can be facilitated, and much more.


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