The role of load balancing in healthcare Robotic Process Automation

The role of load balancing in healthcare Robotic Process Automation

Healthcare Published on 3 mins Last updated

The concept of Robotic Process Automation (RPA) has been bandied about for a while. But here our Healthcare IT specialist at, Liam Canavan, explains why the massive backlog caused by Covid has led to a renewed interest in the topic.  

The concept

Robotic Process Automation simulates user input to drive GUI applications, freeing up clinical staff from admin tasks, reducing human error, saving money, and allowing frontline staff to spend more time with patients. All of this is essential if overstretched healthcare services are to clear the waiting list backlog created by the pandemic.

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A digital process management tool

Essentially RPA tools help organizations configure a script or 'bot', to mimic the execution of a human task e.g. analyzing data, executing a process, triggering a response, or communicating with other digital systems. This script, therefore, performs the same task a human would, on the same computer interface.

For example, in the world of RPA, bots could potentially reschedule and prioritize patient appointments, adding new details to the database and notifying patients. This would free up clinicians to 'get back out there', and do what they do best.

So far, RPA has delivered significant cost savings, with relatively low barriers to adoption. According to Gartner:

Half of U.S. healthcare providers will invest in Robotic Process Automation (RPA) in the next three years – up from 5% in 2020.

Examples of RPA application in healthcare settings

Check out the examples below for more context on how RPA is being applied in healthcare:

Benefits of RPA in healthcare

Some clear benefits of RPA implementation have therefore emerged:    

1.Increased productivity

Studies show that RPA is empowering organizations to execute business processes 5-10 times faster – resulting in increased productivity and leading to improved staff and patient satisfaction. Bots automatically perform repetitive tasks and free resource time – allowing clinicians to attend to higher-value activities.

2.More efficient data management

RPA results in the effective and efficient management of financial, regulatory and operational data. Healthcare organizations applying RPA to their central database can benefit from increased data quality, reliability, and output consistency. Besides, data transfers during automated processes are always confidential, eliminating any human errors by design.

3.Streamlined regulatory processes and compliance

RPA helps assure compliance with data-related protocols and regulations such as GDPR (General Data Protection Regulation in the UK) and HIPAA (Health Insurance Portability and Accountability Act in the US). With RPA, healthcare regulatory processes can be automated – resulting in increased process accuracy, audibility, and high levels of compliance.

4.Cost savings

Bots operate 24/7 and at a fraction of the cost of a human employee. Therefore, for repetitive tasks that are prone to errors, RPA can be a great cost-saving solution. The technology can provide significant cost savings for healthcare organizations under pressure to reinvest in the delivery of better patient care.

5.Faster decision-making

By quickly accessing, acquiring, processing, and analyzing large volumes of data, RPA enables faster and more accurate decision-making, and potentially earlier diagnosis.

6.Less errors

With a clear audit trail and logic, computers are not prone to errors in the same way as humans. Sadly, in medicine, human error is the cause of 250,000 deaths a year in the US.

The role of load balancers

Whether driven by a team of skilled clinicians or a fleet of bots, if a healthcare application experiences an outage then productivity is brought zero.

Hence RPA applications will only work if high availability is guaranteed. If the applications stop, the bots will no longer function, which could result in critical processes or data not reaching the frontline, potentially leading to compromised patient care.

Load balancers are most commonly deployed in active-passive pairs to solve this very problem. In the event of a system failure, the load balancer redirects all traffic to the redundant device, providing continuity and removing the need for scheduled downtime for maintenance. Therefore keeping critical healthcare applications and bots running 24/7.

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