Solving Performance Issues in High-Volume Custom EHR Systems

The healthcare sector is one of those sectors that is under a significant burden and still manages to keep the world healthy.

You see, everybody knows about the WHO reports that estimate that the world will need almost 11 million healthcare workers by 2030, to support the increasing deficits. This, coupled with the rising costs of healthcare, makes the situation seem to be hanging by a thread.

Moreover, what adds to this understaffed healthcare industry is the growing administrative burden and increasing burnout rates for providers. For instance, physicians in the United States spend around 16.6% to 24% of their working hours on completing administrative tasks. And those who are not able to do it have to do it in their free time, hence the term ‘Pajama Times’.

And talking about pajama time, almost 56.5% of physicians experience burnout from their work.

However, as they say, every cloud has a silver lining; the tides in the healthcare industry are slowly shifting in favor of healthcare practices. You see, with the arrival of advanced technology and practices, understanding how customized solutions can optimize their performance while lowering the burden, many practices are looking for EHR development to solve performance issues in high-volume EHR systems.

But a custom EHR can be used for EHR performance optimization, so you might ask here, ‘How can a custom EHR improve practice performance and what if the system itself breaks down?’

Well, let’s see exactly that in this blog below and uncover the intricacies of how to improve EHR system performance that can enhance your practice performance.

So, without further ado, let’s get started!

Where Performance Breaks Down in High-Volume EHR Systems

Before getting into the intricacies of solving performance issues in custom EHR, let’s first try to understand why these software systems break down. First things first, one of the major problems comes in the form of lag or slow systems, especially in high-volume environments. This latency is caused by large and rapidly growing patient databases coupled with multiple logins at the same time, and just by coincidence, it happens to be the peak clinical hours of your practice.

I mean, let me explain, everything that could go wrong at the point of care can go wrong on a normal day. And this chain of events can be initiated by a simple software malfunction or a slowdown.

So, at the peak time, you are seeing that one patient has lab orders pending, the other is concerned about billing, one is requesting a refill, and you are struck with a frozen screen. One of the common reasons for this is the architecture of these software systems. Due to its monolithic nature, its systems are tightly compiled, where the room for flexibility is minimal.

In such cases, it is natural for the software to freeze when the volume increases with load on its features and functionalities.

And since healthcare practices were unable to rely on these systems, they started to shift to custom EHR software for performance.

Furthermore, performance challenges are something that can be fixed in updates of maintenance. Some challenges can even disrupt your development process and knowing about them can be a good start for futureproofing your system. On that note, read the blog – Common Challenges in Custom EHR Development and How to Overcome Them.

Architectural Foundations for Healthcare Software Scalability

EHR system optimization with custom healthcare software systems is much easier. You see, modern-day healthcare software systems are built on modular architecture. In simple words, every component of the software is built independently of others and then brought together to work in perfect synergy.

In such cases, when the volume increases on one particular component of the software, the other one remains unaffected.

This architectural approach is also called a microservices-based approach, and it is one of the best ways to deal with high-volume situations. You see, it not only isolates failures and improves resilience, which makes your software robust and capable of handling extreme pressure.

And given the ever-increasing volume of data, the cloud-native infrastructure of the custom EHR gives it the necessary elasticity or flexibility that helps in scaling and handling high-volume data pressures.

However, something where most of the projects go wrong is database partitioning and sharding strategies. You see, databases have a huge role to play in resilience and EHR system performance. With the right strategy in place, this can improve the performance of your system by a huge margin.

Practical Techniques to Improve EHR System Performance

Most of the performance issues in custom EHR are byproducts of physical restrictions. In such cases, you need to trick the system into working more efficiently. For instance, in high-volume EHR systems, the user interface is always in focus, and blocking it during a task can create chances of system freezing, generating frustrations, and disrupting workflows.

However, by breaking this real-time request cycle, most of the triggers can be improved. To explain, while the report is being generated in the background, the physician would be alerted with a notification and continue his work. And once the report is successfully generated, they will be notified again.

In this way, the waiting factor is removed from the screen. These techniques can be extremely useful for population health and quality reporting, PACS imaging syncs, and claims batch processing.

But this is just one of the tricks, here are some strategies that you can implement:

The AI Advantage in EHR Performance Optimization

Ever since the introduction of Artificial Intelligence, it has always used for solving performance issues in high-volume EHR systems. You see, to understand the advantage of AI, you have to implement it. And this is exactly what many healthcare practices are doing with custom EHR software development.

Let’s have a look at some of the examples that can be used to improve performance in high-volume EHR systems.

The very first thing that sticks in our mind is predictive performance analytics. You see, by understanding the daily usage and other intricacies of the internal system network, your system itself can anticipate peak system load and adjust itself in that manner.

Furthermore, when you have an AI system in your EHR, you should use it for detecting anomalies. These anomalies can enhance your system immensely by helping you identify early signs of things that affect the performance of your system.

And if you’re able to make this even smarter, your AI can even intelligently allocate the resources to real-time system behavior. There are certain things that you indeed need to address in this, but if done correctly, it can make your system faster, smarter, and better.

The way AI helps in EHR system optimization is by being embedded in the workflows of the system. You see, when the core of workflow—that is, documentation—is assisted by AI, it creates minimal friction and puts less strain on the system. This way, the process of entire care deliveries gets faster without influencing the clinical decision-making. In short, with AI, you can create a win-win situation easily.

Testing, Monitoring & Continuous Performance Improvement

Performance improvement is not a quick-fix problem; it is a process where you have to continuously test, monitor the progress, and make changes till the systems are running. Especially in EHR software development. You see, until your system is not like the way you want it, test it and make it even better.

Here are some aspects that can help you in this process:

• Load & Stress Testing: While many vendors test for load, they forget stress. But the software should be tested for both. Test how the EHR system performs under peak times and how it performs when stretched beyond its limit. It gives you a better idea about the sustainability of your system.

• Identifying System Breaking Point: With AI, this identification process can become much easier. However, you should keep an eye on the system functions regularly. It gives you insights about when your EHR system slows down or fails. This gives you enough time to fix the issues before escalating during patient care.

• Performance Monitoring Reports: It is natural for any system to increase in features and data. As more patients, users, and features are added to your EHR, it should be monitored to ensure that, despite this, the system remains fast, reliable, and user-friendly over time.

• Set Benchmarking Metrics: Since you will be tracking everything, set some benchmarks for almost every aspect of your system. It is one of the best ways to ensure that the system is always fast, reliable, and clinician-friendly at all times, and there is always something to look forward to.

Frequently Asked Questions