Applicable Industries
- Chemicals
- Healthcare & Hospitals
Applicable Functions
- Human Resources
- Product Research & Development
Use Cases
- Leasing Finance Automation
- Retail Store Automation
About The Customer
The customer is a leading healthcare organization based in North America. The organization provides integrated health services and patient care, with a focus on improving healthcare delivery efficiency. The hospital has a team of Patient Care Advocates (PCAs) responsible for ensuring patients receive reminder letters for upcoming appointments. These letters are customized for each patient’s needs and appointment type. However, the hospital was struggling with high employee turnover and the time-consuming nature of creating and printing these customized letters.
The Challenge
A leading healthcare organization in North America was facing significant challenges in managing patient communications and record management processes. The hospital's Patient Care Advocates (PCAs) were responsible for creating and sending reminder letters for upcoming appointments, a task that was both time-consuming and prone to human error. Each letter required unique customizations based on the patient, taking up to 10 minutes to create and print each one. High employee turnover further exacerbated the situation, with the number of PCAs dropping from 24 to 10 in the spring of 2022. The healthcare industry's increasing demand for medical services and a decreasing pool of workers added to the urgency of finding a solution to streamline these repetitive tasks and improve efficiency.
The Solution
The hospital partnered with Trumpet, an IT service provider, to automate the process of generating custom letters for patients. Trumpet built an automation using ElectroNeek's Subscription Model that allowed the PCAs to queue eligible patient records and pick up the letters at the printer after the automation generated the custom letters. The automation bot worked in their electronic medical records (EMR) software, monitoring a queue of patients using built-in filters. The bot identified various information elements from the patient record and stored them in memory for use within the letter. It referred to a set of configuration files made by the PCA team to generate each element of the letter that needed to be customized according to the patient’s appointment, special instructions, and doctor information. The automation combined these elements into a basic letter template stored in the EMR to create the final customized letter that was saved digitally first into the patient record and then sent to the office printer.
Operational Impact
Quantitative Benefit
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