Self-scheduling Medical Visits in a Multispecialty, Multisite Medical Practice: Complexity, Challenges, and...

Area of Science:

• Healthcare Administration
• Health Informatics
• Patient Experience

Background:

• Self-scheduling for medical appointments is increasingly adopted but faces implementation hurdles due to scheduling complexity.
• Mayo Clinic has been expanding its self-scheduling capabilities since 2019.
• Understanding scheduling complexity is crucial for optimizing self-scheduling systems.

Purpose of the Study:

• To quantify the complexity associated with medical visit scheduling.
• To analyze the opportunities and challenges of scheduling complexity within a self-scheduling framework.

Main Methods:

• Examined scheduled visits from January 1, 2022, to August 24, 2023.
• Counted unique visit types for both staff-scheduled and self-scheduled appointments across seven categories.
• Identified self-scheduled visit types with the highest patient uptake.

Main Results:

• Over 20.8 million completed visits included 9,555 unique visit types.
• Self-scheduled visits constituted 4.0% of total completed visits (838,592).
• Established patient, testing, and procedure visits comprised 93.5% of self-scheduled appointments, with primary care established patient visits being the most frequent (32.6%).

Conclusions:

• A high number of unique visit types presents a significant challenge for self-scheduling implementation.
• Standardizable visit types, such as guideline-based procedures (e.g., mammograms, immunizations) and established patient/laboratory visits, show high suitability and uptake for self-scheduling.
• Thousands of specific visit types still necessitate staff intervention for accurate scheduling.