When someone gets in a car accident at midnight or a child has a concerning stomachache early in the morning, hospitals are always there to provide care. That’s why it’s so important that health systems mitigate downtime.
Many healthcare organizations operate 24/7, 365 days a year. They can’t afford to be down due to the potential for financial loss and, more important, the impact on patient care. To support clinical care, healthcare organizations should be able to provide “five nines”: 99.999% availability, or no more than 5 minutes and 15 seconds of downtime a year. This can be challenging to pull off in the healthcare industry, where organizations have large networks and a long list of systems to manage, including the electronic health record (EHR).
Most software companies today are creating reliable products, but healthcare organizations are still left with ensuring the reliability of their own networks and infrastructure to ensure that those software systems don’t go down. That’s where observability comes in.
EXPLORE: Maintain the health and performance of complex applications with observability.
The Importance of Observability Maturity for Healthcare
Monitoring involves assessing all of a healthcare organization’s systems and receiving alerts when something goes wrong. However, monitoring doesn’t necessarily explain what is wrong, which can result in several calls to the service desk and time spent investigating the issue. The other limitation with monitoring is that it informs IT teams only when something has happened, meaning it’s too late to prevent the issue from occurring.
Observability involves using AIOps, or artificial intelligence (AI) for IT operations, to analyze network or system data to predict a failure. This is the highest level of maturity and a key capability when it comes to mitigating downtime in healthcare. According to Amazon Web Services, the observability maturity model includes four steps:
- Stage 1 - Foundational Monitoring: Collecting Telemetry Data
- Stage 2 - Intermediate Monitoring: Telemetry Analysis and Insights
- Stage 3 - Advanced Observability: Correlation and Anomaly Detection
- Stage 4 - Proactive Observability: Automatic and Proactive Root Cause Identification
Ultimately, healthcare organizations want their networks and infrastructure to be self-healing so that systems never go down. Observability paired with redundancy can go a long way toward achieving that goal. Think of Amazon: It never goes down and consumers are always able to buy something. They are at Stage 4 of the observability maturity model. So, while they may have issues, they are able to predict them. And in case something does go wrong, they have redundancies in place so they can fail a system over, meaning that consumers never feel the impact of that issue. That’s where we need to get to in healthcare.
Observability will help healthcare organizations get there much quicker than simply relying on redundancy and hoping for five nines.
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