The seemingly ancillary process of patient scheduling offers opportunities for tracking scheduling tendencies and ensuring continued care while ensuring financial health.
Today's robust analytics tools can offer artificial intelligence and machine learning technologies that can help healthcare organizations analyze patient behavior and identify the who, where and why of cancellations, reschedules and no-shows, fueling initiatives to help increase appointment completion.
During a Becker's Payer Issues Virtual Summit session sponsored by Alithya, two data analytics professionals from Alithya discussed patient scheduling issues, how AI and machine learning can move patients toward completing appointments, and solutions offered by Alithya and Oracle:
- Mark Hite, managing director, healthcare
- Brian Kelsey, product manager, analytics
Five key insights:
1. The Oracle practice within Alithya focuses on enterprise applications, application services, business strategy and data analytics. More than 225 consultants make up the Oracle practice within Alithya, a digital transformation company, and have been involved with more than 375 enterprise performance management/enterprise resource planning cloud projects.
2. Many detours can occur between the time a patient schedules and completes an appointment. "Throughout the patient workflow process, many things can happen," Mr. Hite said. The provider will call to confirm, or the patient may cancel or reschedule. Once a patient arrives, the appointment may be completed or the patient may leave before being seen. Some patients never show up. "Throughout all those processes, you'll want to capture many data points," he added.
3. Alithya's solution, which leverages Oracle technology, focuses on identifying which patients are likely to cancel their appointment so proactive measures can be taken. According to Mr. Kelsey, this solution predicts which patients, based on past activity or demographics, are at high risk of canceling. "We can then be proactive in getting them to reschedule or help them complete those appointments," he said. For example, the demo data showed that 37 percent of individuals likely to cancel lived in one area, which could prompt a community campaign. Or, if 70 percent of likely canceled appointments are not procedure-based, an organization might work to promote a telehealth option to that group.
4. Oracle technology drives the analytics behind Alithya's solution. The solution works with both on-premises and cloud-based scheduling systems, bringing the information into an autonomous, cloud-based data warehouse. "Once the data is in an interface area, we can validate and move it into a refined zone where we provide enrichment, analytical views and geo codes to incorporate location information of our patients," Mr. Kelsey said. "We can create maps that show patient-to-provider distances to see if that is contributing to cancellations." The solution can also analyze notes from appointments, and it provides robust visualization capabilities. It works out of the box, but is extensible, completely scalable and customizable to a healthcare organization's specific needs.
5. AI and machine learning technology helps healthcare organizations make better, faster decisions that can help them compete in an increasingly consumer-like marketplace. "These capabilities really help you know your patient populations and better analyze trends," Mr. Hite said. "All of healthcare is moving toward more machine learning, artificial intelligence to drive decision-making. Healthcare is in a boom of consumerism. Patients are really shopping services. By using a tool like this, you can deliver quality care as well as prevent some issues with your patient populations."
To learn more about the event, click here.