Though RPA is the fastest-growing segment of the global enterprise software market, RPA adoption in healthcare is not widespread yet. According to market studies, Robotic Process Automation (RPA) market expected to reach $5bn by 2024 and the healthcare segment is expected to be one of the fastest-growing sectors over this forecast period and this is not a surprise since healthcare systems contain multiple rule based processes and generate a substantial amount of data. RPA can help cure healthcare inefficiencies:

What does RPA mean for the healthcare industry?

Healthcare systems contain multiple burdensome tasks that require substantial amount of resource allocation such as claim management. This leads to high costs of operations and slow processes.

Leveraging the power of automation and RPA, healthcare providers can address these issues and make healthcare systems more efficient and healthcare processes faster, improving patient satisfaction.

Why is RPA important in healthcare?

Because healthcare is one of the most inefficient industries and reducing healthcare inefficiencies will contribute to better healthcare delivery which is important for both the industry and the public.

Every industry has inefficiencies however few industries face the challenges of healthcare industry: strict regulations concerning patient data and less resources to deal with such regulations. Financial services also faces similar high levels of regulations but banks have better access to capital and have historically had higher levels of technology investment with Goldman Sachs CEO calling the company as a technology company. Therefore, the level of inefficiencies and manual processes in healthcare is higher than almost any other industry.

IT and healthcare services budgets all come from healthcare providers' earnings. With automation and fast implementation projects enabled by RPA, healthcare providers can avoid costly, long running digital transformation implementation projects and reap fast rewards, enabling them to channel more resources to healthcare delivery.

What are RPA use cases in healthcare?

Patient Scheduling

With the involvement of RPA technology, patients can schedule their appointments without an intervention from hospital employees. Along with eliminating the need of resource allocation for scheduling, this application can also improve customer relations since patients can arrange an appointment faster.

Claim Management

After a healthcare service is provided, billing takes time due to manual and repetitive tasks in claim management process. Claim management contains processes such as inputting, processing and evaluating documents and data. Along with automating time-intensive tasks, RPA-led claim management can also eliminate human errors during claim processing. According to studies, Medicare/Medicaid insurance frauds are the majority of false claims among all other insurance frauds in America.

Regulatory Compliance

RPA enables healthcare providers to track, document each process step in structured logs files so that the company can comply with external audits. Since these processes are handled by bots, RPA enhances data confidentiality as well.

Healthcare industry is reliant on paper documents and requires digital transformation. Healthcare providers are digitizing patient information so that it can be stored electronically accessed online by other doctors and the patients themselves. The process of extracting data from legacy systems and entering those into digital system can be automated by RPA bots. And then, when migration of data for another purpose such as medical research, another RPA bot can handle this migration process.

Healthcare facilities can also leverage workload automation (WLA) tools for data-related tasks, such as ETLs, FTPs, and data warehouse management. WLA tools can automate the initiation, triggering, and execution of these processes on different business platforms from a centralized point to provide an overview of data transfers and migrations, and log these actions.

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For example, Children's hospital and medical care center typically handles 350,000+ patients a year, generating a large amount of data to be processed and delivered to hundreds of employees around the hospital. The center utilized ActiveBatch job scheduler and workload automation solution to build workflows which automate 40+ file transfer processes with more than 40 vendors, and cut up 50+ hours of staff work in a year.

Industry agnostic use cases

Processes like accounts payable, expense management etc. are common across all industries and RPA can be used to automate them. For more such RPA use cases,  feel free to check our article where we explain 60+ RPA use cases.

What are the benefits of RPA in healthcare?

Top benefits of RPA in healthcare industry are:

  • Reducing costs: Price of RPA software is just a small fraction of what healthcare providers pay to employees for manual tasks. According to CAQH's study, the healthcare industry could save $13.3 billion if administrative tasks are automated in the revenue cycle .
  • Increased appointment turnout:Thanks to the automation of patient scheduling and appointment reminders send by RPA bot, patients are less likely to forget their appointments so that doctors provide care to more patients that increases productivity and efficiency.
  • Elimination of human error: In rules based processes, bots apply rules that are programmed. If programmer does not make any error while writing code, then your rules based process will be error-free.
  • Better patient experience:The RPA bots streamline front-office support and makes it easy for patient support team to manage patient queries. RPA solution in the front and the back office allows healthcare providers to offer a higher quality of customer service.
  • Better employee satisfaction:Assigning your workforce to tedious tasks may harm employee satisfaction that can lead to higher employee turnover. This leads to more recruiting and onboarding during which employees are considerably less productive.

What are example RPA case studies in healthcare?

Healthcare provider example: Max Healthcare

Problem: Max Healthcare Institute is one of the largest healthcare chains based in New Delhi, India. They deal with the process of patient transaction data on a daily basis. Some manual processes they need to streamline every day are customer detail recording, claims processing and reconciliation of data for government health schemes. The main priority was to improve the efficiency of existing processes to ensure greater accuracy and reduction in turnaround time, yet, the institue wanted to start small and scale up as and when required.

Solution: They partnered with an RPA consulting firm to identify areas where robotic automation could be implemented and where the maximum impact could be achieved. The institute adopted an RPA platform to handle following processes more efficiently:

  • Claims Processing
  • Data Reconciliation for Central Government Health Scheme (CGHS)
  • Data Reconciliation for Ex-servicemen Contributory Health Scheme (ECHS)

Results: With this solution, Max Healthcare were able to reduce turnaround time (TAT). For claims processing, the TAT was reduced by at least 50% while CGHS & ECHS have achieved time savings in the range of 65%-75%.

To learn the full story of Max Healthcare Institute's RPA journey, you can check out this article.

Major U.S. Healthcare coverage administrator automates appeal processing

Problem: The company must review cases when members submit a policy complaint or want to appeal a decision, yet, members request appeals through different channels such as email, fax, phone or a web form. Information regarding member name and complaint type was manually entered from different channels to start the appeal process. These manual steps were time consuming. Errors and delays in the appeal were costly for the company.

Solution: The company adopted an RPA solution to solve this problem. The software is able to extracts data from emails using robotics and OCR, then uses machine learning models to classify and route requests into queues.

Results:

  • Manual work is reduced by 85% across the process end-to-end, from data extraction to policy decision
  • Time stamp and other data extracted at a 99% accuracy rate, up from 62%
  • Average routing time cut from 15 minutes to 3 minutes

To learn the full story, you can check this article.

For more RPA case studies, feel free to check our RPA case studies article.

And if you still have questions about deploying RPA, don't hesitate to ask us. We would like to help:

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This article was originally written by former AIMultiple industry analyst Atakan Kantarci and reviewed by Cem Dilmegani

Cem founded the high tech industry analyst AIMultiple in 2017. AIMultiple informs ~1M businesses (as per similarWeb) including 55% of Fortune 500 every month. Throughout his career, Cem served as a tech consultant, tech buyer and tech entrepreneur. He advised enterprises on their technology decisions at McKinsey & Company and Altman Solon for more than a decade. During his secondment, he led the technology strategy and procurement of a regional telco while reporting to the CEO. He has also led commercial growth of deep tech companies that reached from 0 to 7 figure revenues within months. Cem regularly speaks at international technology conferences. He graduated from Bogazici University as a computer engineer and holds an MBA from Columbia Business School.