Shinshu University Hospital is no stranger to Robotic Process Automation. This hospital, which is the central medical care facility for Japan’s Nagano Prefecture, has been using UiPath RPA to automate administrative tasks since 2018. The hospital’s RPA Promotion Office was established in May 2020 to expand automation to make staff more efficient and help standardize operations across departments. Thanks to RPA, the hospital saved 4,559 work hours per year by the end of 2020 and the next step was to incorporate AI.
The RPA Promotion Office team determined that AI and RPA would be a powerful combination for hospital accounting, and didn’t lose the hope for the success of these endeavors after their initial attempts at adapting AI failed. The reasons were the complexity to create a workflow that could recognize processes and correctly assign the next task, and the cost of software licensing and training.
The things went better when Yasuhiro Shiraki, who works in the RPA Promotion Office, heard about UiPath AI Center™ in February 2021. He was surprised by the low cost of AI Center and classification models such as language learning and images, which were valuable features. It was also attractive since the AI would integrate with existing UiPath RPA processes. Shiraki also was impressed by the versatility of AI Center, and the library of AI models developed by other AI Center users. The resources available were a deciding factor and made it easy to start using AI Center.
The impetus for adopting AI to power accounting was to standardize journal code entries. The Hospital Accounting Rules are complex and detailed, which makes accurate manual data entry problematic. An additional challenge is that contract workers usually complete the paperwork.
Shiraki wants to use AI to remove as much of the human factor as possible from account coding. Automating the accounting process reduces the workload for employees and eliminates much of the decision-making process. He found that AI couldn’t always make the right accounting decisions, but it’s especially effective when working in tandem with rules-based automation.
Yasuhiro Shiraki has developed a means to train the AI using external data and classification models. Once you link to the data source, you invoke machine learning and the AI becomes self-teaching. For an investment of 123 hours of AI development time, Shiraki has been able to use AI to standardize decision-making throughout accounting. Hospital executives are now discussing ways to apply the same AI models to other departments.
“We believe that the automation model we have adopted can be used by any medical institution that needs to conform to hospital accounting regulations. We also hope it will be a larger contribution to the medical industry and change the way doctors and medical professionals work.”Yasuhiro Shiraki, RPA Promotion Office, Shinshu University Hospital
AUTOMATION by NUMBERS
- 4,559 hours saved in the first two years
- 66% less cost to start compared to other AI solutions
- 123 hours to create AI for accounting