Robotic process automation has become an influential tool company
can use to generate operational efficiencies quickly. However, it can also be
used as a first step to better data quality, laying the foundation for
artificial intelligence and machine learning systems.
This cannot happen soon enough for hospitals grappling with
the burden of changing revenue and cost dynamics in an industry that depends on
processing large volumes of sensitive personal data. In fact, at an average of
$408 per record, the cost of healthcare data breaches is at least double that
of other industry sectors (see Figure 1). The high price of a breach is
primarily due to high notification costs and heavy penalties in the United
States for mishandling health information. Better management and automation
would help reduce the risks considerably.
The healthcare industry faces the highest per capita cost of data breaches
The healthcare sector, in general, is far behind others in adopting
digital technologies. According to our recent Digital Radar report, the
healthcare industry scored an average of 41.25 out of 100 on our Digital
Maturity Index. This score compares to an average of 70+ for technology
companies.
Healthcare is an industry that is not seen as a natural
candidate for automation. This is a human-centered service where the personal
touch significantly impacts patient experience and outcomes. However, there is
still considerable potential for automation, given the extent to which data
drives decisions and the underlying systems. According to McKinsey, 36% of
healthcare activities could be automated, and most automation opportunities are
related to data collection and processing2.
Automation helps reduce current data-related inefficiencies
by improving data quality and consistency and enabling standardized data
structures that can create a unified view of performance across a hospital.
Hospitals that have implemented RPA have seen significant
benefits. A Kentucky-based multi-unit medical center upgraded to an integrated
medical records and practice management system, saving more than 2,000 hours of
manual effort. The RPA system took less than 24 hours to perform an error-free
transfer of more than 64,000 records from old systems to a new system3.
In Europe, a general care hospital with 70,000 emergency
department visits and 300,000 outpatient visits per year faced several
challenges that were labor intensive, depended on paper records for medical
records and financial documents, and had inventory management issues. The
hospital used RPA to eliminate paper records and store data digitally. In the
process, he reduced unnecessary functions, integrated operational silos, and
simplified the supply chain. Billing and claims handling costs were reduced
from $4 to $1 per claim4.
Where to apply RPA
Robotic process automation is the technology that automates
high-volume, repeatable business processes by mimicking the human interactions
that performed the procedures initially.
RPA is best used for mundane and repetitive tasks such as
logging into web applications, filling out forms, and extracting data from
disparate internal systems (see Figure 2). RPA bots are programmed to follow
"if-this-then-that" rules and therefore work well in already
well-understood processes and where data formats are structured and
standardized. However, bots can further structure data through their results
and can be an essential tool for creating a standardized data architecture.