Transforming patient and staff engagement
Southern community-based health system on MEDITECH uses AI and automation to empower patients and eliminate work for staff
Introduction
Founded 200 years ago in 1824 in Charleston, South Carolina, MUSC is the oldest medical school in the South and the state's only comprehensive academic health system. Its journey mirrors the evolution of healthcare itself, from the rudimentary practices of its early days to the complex, technology-driven discipline it has become today. MUSC has stood the test of time, not merely surviving but thriving, by adapting to change and embracing innovation.
Today, MUSC Health, the integrated clinical arm of MUSC, serves patients through 16 hospitals, 350 telehealth sites, and nearly more than 750 care locations across all regions of South Carolina. At its core, MUSC is driven by a singular, notable purpose: to preserve and optimize human life in South Carolina and beyond. This is a commitment to excellence, compassion, and innovation, aims to heal and enhance the quality of life for every patient it serves.
How a Southern health system transformed senior engagement with automated digital outreach
The challenge
A Southern community health system with 250 beds and 2,500 employees, using the Meditech EHR, focused on its mission to strengthen the health and well-being of all people in its communities, and to be a national model for a community-based health system.
This customer aimed to modernize its pre-registration workflow as part of its transformation journey. Historically, patients with upcoming appointments for imaging, mammographies, ambulatory surgeries, X-rays, or MRIs received pre-visit calls from staff 14 days before their appointment. These calls collected demographic and insurance information, symptoms, and consent forms, and provided pre-procedure instructions.
However, this process was time-consuming, inefficient, and prone to errors, as many patients were unavailable during business hours and information had to be manually entered into patient records. When pre-registration information is incorrect for diagnostic imaging and outpatient surgical procedures, a denial is costly for the organization and patients can experience delays in care. To address this, the health system sought to digitize, automate, and personalize its pre-registration workflow while ensuring inclusivity for all patient segments.
The solution
This health system is dedicated to digitally engaging with all patients, including the senior population, bridging the technology gap through user-friendly interfaces, personalized experiences, and an ongoing ability to receive patient feedback. To do so, the organization created a digital pre-registration experience accessible to all patients. The solution provides seamless, two-way integration with its electronic health record (EHR), ensuring the accurate, real-time flow of data between pre-registration and patient records.
This health system partnered with Notable to deploy an automated digital intake experience that enables patients to complete pre-visit registration at their convenience without having to make or take a phone call. Instead, before their upcoming appointment, patients are sent a link to a personalized pre-registration experience via their preferred method of communication (email, text message). Using their mobile device, patients can enter or confirm their demographic information, upload and submit a photo of their current insurance card, complete pre-visit consent forms, and be provided with arrival and visit instructions.
“It was super easy to fill in your forms on my phone which is not always the case,” said a 55 to 64-year-old patient. “Thank you.”
All data submitted by patients through the experience is automatically written back into the EHR without staff involvement. With the time saved, staff can work on more complex tasks, like prior authorizations, without having to reschedule or otherwise impact patient care. For the organization, the time savings reduce the pressure to hire more staff, which continues to be a challenge across the industry.
A large portion of this health system’s patient population is comprised of seniors, making the Medicare Secondary Payor Questionnaire (MSPQ) a critical component of the pre-registration workflow. Comprised of six parts, the MSPQ determines if Medicare is the primary or secondary payor for a patient. The health system worked diligently to make the digital version of its MSPQ patient-friendly, focusing on the overall flow, ensuring a clean and intuitive user interface, and using language similar to what patients would encounter if they were working through it via phone with a staff member.
The Results
Through Notable’s agile deployment approach, Augusta Health quickly went live with its first service line, achieved early results, and continued to iterate with direct feedback from patients and staff members during multiple smaller implementations.
Today, four hospital-based service lines are live with the Notable experience, leading this health system to see 17,000 annualized digital intake completions by its patients. Each digital intake saves staff an estimated 7 minutes. The end-to-end automation of these workflows frees up staff capacity to focus on more complex work. On average, 60% of all encounters are registered fully digitally, and the organization sees greater than 90% patient satisfaction rate.
Rather than create a technological barrier to engagement, the automated pre-registration experience has empowered senior patients, fostering independence and enhancing healthcare delivery efficiency. To that end, patients 65-74 years old have the highest digital intake completion rate of all segments at 63.5%, and those 75-84 years old have a 56.7% completion rate.
This health system remains focused on using technology to drive efficiency and inclusivity. In partnership with Notable, the organization continues to optimize patient notifications, ensuring that duplicative outreach is reduced or eliminated. In addition, this health system plans to explore the use of a machine-learning model with set rules around payer-plan matching that will be incorporated into the automated workflow.
