Online portals for medical appointments, telehealth visits, prescription refills, and patient communication are becoming more common in the United States. When new appointment slots open or during large public health efforts, these sites often get many users at the same time.
If too many people try to use the system at once, the platform may slow down or stop working. This makes it hard for patients to get care on time. It also can hurt the reputation and income of medical practices.
Healthcare managers need ways to handle busy times without lowering service quality. One common method is using queue management systems. These systems control access so the platform gets a steady flow of requests.
FIFO stands for First In First Out. It means people or data are served in the order they arrive. The first person in line is the first to be helped. This method is simple and fair. It stops people who come late from skipping ahead.
On medical websites, FIFO puts users in a virtual line and lets only a few at a time in. Each person gets a number and the system keeps everyone in order until all are served. This helps stop overloads and keeps the process clear for patients waiting.
Ritika Bhagat, a researcher on queue systems, says FIFO brings fairness and clear rules. This makes patients trust the system more and lowers delays in busy times.
Healthcare workers use FIFO differently depending on the situation. In emergency rooms, urgent cases usually get treated first, even if they came later. But for most online appointment sites, FIFO stays the fair and useful way to manage access.
Using FIFO on medical websites means adding digital queue software. Some advanced platforms use tools like Vizitor. This software tracks who is next and controls how many users enter at once to keep the system stable.
Staff need proper training to use queue systems well. When patients ask for help while waiting, workers should give clear answers. Also, explaining to patients how the queue works can reduce confusion and stress.
Cloud technology helps create queue systems that grow and shrink as needed. One example is the Virtual Waiting Room from Amazon Web Services (AWS). This cloud system holds users in a queue when traffic is high and lets them in step by step. This keeps the site working well during busy times.
Healthcare sites that get many users at once—for example, when booking COVID-19 vaccine appointments—can benefit from AWS Virtual Waiting Room:
AWS plans to retire this service in November 2025. Healthcare platforms using it will need to keep it running, switch to other options, or use AWS’s new methods with CloudFront and CloudFront Functions.
Artificial Intelligence (AI) and automation are playing bigger roles in managing patient visits online, especially when many people use the system at once. AI helps with several tasks related to queue management and office work.
AI virtual agents can handle appointment confirmations, rescheduling, and simple questions. This reduces pressure on staff during busy times and stops many calls from being dropped. Patients get quicker replies without clogging the phone or website.
AI studies past usage data to predict busy times. It can spot when flu season or vaccine drives will increase traffic. The queue system can adjust in advance to handle more users smoothly.
FIFO is standard, but AI can change the queue based on user types. For example, high-risk patients might get priority with clear rules. AI removes bias while keeping fairness.
Automation links queue systems with EHR platforms. When patients join the queue, their data can be checked and updated quickly. This speeds up check-in and reduces repeated data entry.
AI systems can send patients messages about their queue status and wait times via text, email, or apps. These updates lower anxiety and cut down on calls to the office.
Managing queues well is a solid way to handle busy times on medical service platforms in the United States. FIFO combined with cloud systems and AI automation keeps systems stable and access fair. Medical managers and IT teams who use these tools can keep services steady and reachable, even during high demand. This approach helps patients get care on time, lowers system failures, and supports medical groups in a more digital world.
The Virtual Waiting Room on AWS is a cloud-based infrastructure designed to manage and buffer large bursts of website traffic by temporarily holding users in a queue, allowing traffic to pass through only when system capacity allows.
Examples include ticket sales for concerts or sports events, major retail sales like Black Friday, new product launches, medical appointment slot releases, online exam access, and direct-to-customer services requiring account creation.
Users are assigned a queue number upon entry and retain their position until it is their turn to access the target website, guaranteeing a structured and fair queue system.
It enables control over incoming traffic during large-scale surges, preventing system overwhelm and ensuring websites remain operational and stable under high traffic loads.
It generates signed, time-limited JSON Web Tokens (JWTs) that downstream APIs use to validate users have legitimately passed through the waiting room before processing their requests.
Yes, it includes an OpenID adapter providing OpenID Connect (OIDC)-compatible APIs, allowing integration with web hosting software that supports OIDC identity providers.
AWS offers a sample waiting room website demonstrating a minimal end-to-end waiting room solution, which can be customized as needed.
The solution can be deployed automatically using an AWS CloudFormation template, with detailed implementation guides and source code available for customization and deployment.
The solution will be retired in November 2025; existing deployments will require customer maintenance and API updates. Post-retirement, the code will be archived for reference without further updates or support.
Customers can fork the archived GitHub repository to maintain their own versions, explore enterprise-supported alternatives in AWS Marketplace, or implement their own solutions following AWS’s Visitor Prioritization guidance with CloudFront and CloudFront Functions.