3 Critical RPA Mistakes to Avoid for Successful Automation in HealthCare

A recent article by InformationWeek’s Jessica Davis proclaimed,

RPA is the fastest growing category of software today, driven by enterprise digital transformation efforts.”

Davis went on to cite a Gartner report which found Robotic Process Automation (RPA) has year-over-year growth of 63%, which it attributes to “an expensive patchwork quilt of applications and systems” that companies are struggling to manage.

RPA (Robotic Process Automation) is an innovative technology that transforms process automation across multiple industries, from finance and retail to healthcare. In the healthcare industry, providers leverage software robots or bots to automate repetitive, time-consuming, and rule-based tasks, thereby freeing up clinicians for more valuable work: improving patient experience and outcomes.

In our blog, we have extensively covered the advantages that RPA offers to organizations, along with the typical hurdles they encounter while assessing opportunities for its implementation. To avoid these obstacles, it is crucial to clear up common RPA misconceptions, a topic I recently discussed with the Enterprisers Project’s Kevin Casey.

RPA-the-eggplant-way-ebook-cover (Check out our latest eBook on how to make RPA safer and more efficient.)


Top 3 RPA Myths (And How to Avoid Them)

#1 RPA improves business processes.

Essentially, RPA is all about automating processes, improving efficiency, reducing operational costs, and enhancing customer satisfaction.

As Casey put it,

If those processes need to be improved, though, you have to do that work.”

It’s a subtle distinction because RPA can ultimately drive some process improvements if—and this is critical if—it’s the right process for RPA to begin with.

While RPA has the potential to drive process improvements, it's essential to recognize that not all processes are suitable for automation. One way to get ahead of this issue is by ensuring that the processes you wish to automate are clearly defined.

By doing so, you can optimize RPA's potential and ensure that it's applied to the most appropriate processes that require automation. Defining the right processes for RPA implementation can lead to improved operational efficiency, reduced costs, and enhanced accuracy. As a result, it's essential to have a well-defined strategy in place to ensure that RPA drives meaningful results for your organization.

Here is a demo showing how RPA simplifies patient appointment booking:

HubSpot Video

#2 RPA notices aberrations.

RPA is great for taking on highly rules-based and predictable processes, simultaneously freeing healthcare workers to focus on more strategic tasks. If something about the process is unusual or suspicious, however, “RPA is typically not going to raise its eyebrows,” Casey writes.

Incorporating anomaly detection into RPA enables healthcare organizations to identify issues that would otherwise go unnoticed. However, modeling anomaly detection into RPA is not a straightforward task and requires careful consideration.

To ensure successful implementation, companies must identify repeatable processes that don't typically result in a significant amount of questions or variation when performed by human workers. As a result, healthcare IT leaders need to take a strategic approach to automation and identify processes that can benefit the most from anomaly detection capabilities to achieve maximum benefits.

#3 RPA deals well with change.

While RPA is a valuable tool for automating repetitive and rule-based tasks, it does have its limitations. One of the primary challenges of RPA is that it needs to be re-tuned to handle changes in a process, which can be challenging in organizations with numerous dependent systems. The first iteration of RPA is not adaptive, which means it lacks the cognitive ability to learn like humans. To ensure that RPA delivers the desired outcomes, healthcare organizations must be aware of its capabilities and lay the right foundation for RPA from the outset.

However, RPA is rapidly evolving to address the unique challenges in healthcare. More organizations are augmenting RPA bots with AI and machine learning technologies. And we expect to see even more opportunities for the technology to drive business value.

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