In the fast-paced and unpredictable world of healthcare, system downtime is not an option. Hospitals operate 24/7, providing critical services to patients at all hours, making any downtime potentially catastrophic, both in terms of patient care and financial loss. To ensure constant availability, healthcare systems strive for "five nines" of uptime, meaning they can only afford a few minutes of downtime per year. Achieving this goal is challenging, but with technological advances, observability powered by artificial intelligence for IT operations (AIOps) is emerging as a critical solution. By predicting issues before they happen, observability helps healthcare IT teams improve reliability, optimise workflows, and ensure smooth operations.
The Role of Observability in Healthcare Uptime
Observability plays a vital role in reducing downtime in healthcare environments. Traditional monitoring systems can alert IT teams when an issue occurs, but they often fall short of identifying the root cause, which delays resolution. Monitoring is a reactive process that only informs teams after the damage is done. In contrast, observability, which leverages AIOps, proactively analyses data flows within the healthcare IT infrastructure, predicting potential issues before they escalate into critical failures. This proactive approach allows IT teams to identify anomalies and address them before they affect clinical operations.
Observability follows a maturity model with four stages: foundational monitoring, intermediate monitoring, advanced observability, and proactive observability. The ultimate goal is to achieve proactive observability, where the system not only predicts problems but also automatically identifies root causes, preventing downtime altogether. This advanced level of observability brings healthcare IT systems closer to self-healing infrastructures, where systems can automatically recover from issues without impacting patient care.
Improving Clinical Workflows with Observability
One of the most tangible benefits of observability in healthcare is its ability to enhance clinical workflows. A common challenge in hospitals involves workstations on wheels (WoWs), which clinicians use to access electronic health records (EHRs) while caring for patients. When these devices malfunction, clinicians may not always report the issue promptly, often leading to multiple devices being out of service and disrupting workflows. With observability, IT teams can automatically detect when a device has been inactive for an extended period, signalling potential problems. The system can create an automated service ticket, allowing a technician to address the issue without a clinician needing to file a report.
This level of automation ensures that IT teams can resolve problems before they affect patient care, creating a seamless experience for clinicians. For example, observability can track battery life on mobile devices used in healthcare settings, predicting when a battery will need replacement. The system can automatically generate an alert or even order a new battery, ensuring that no critical devices are out of commission during a clinical shift. This proactive maintenance avoids the risk of multiple devices failing at once, thereby improving the efficiency of clinical teams and reducing the chances of delays in patient care.
The Power of AIOps in Healthcare IT
A key component of observability is the integration of AIOps, which enhances IT teams' ability to manage complex systems. In healthcare, AIOps can scan networks, detect data bottlenecks, and predict potential failures in real time. By correlating data and determining the root cause of anomalies, AIOps enables IT teams to act swiftly to prevent system failures. This is particularly important in healthcare, where the integrity of systems is critical for everything from patient data management to the operation of life-saving medical devices.
AIOps not only helps prevent issues but also allows healthcare organisations to recover quickly when they do occur. For instance, in the event of a cyberattack or natural disaster, an IT team using AIOps can fail over to a redundant system, minimising disruption and ensuring that patient care continues uninterrupted. This level of reliability is essential in healthcare, where even brief interruptions can have serious consequences. With observability and AIOps, hospitals can achieve the goal of "five nines" uptime, making their IT infrastructures more resilient and capable of self-healing when failures do happen.
Conclusion
Healthcare organisations increasingly turn to observability and AIOps to improve system reliability and reduce downtime. Hospitals can predict and prevent IT issues by moving beyond traditional monitoring and embracing proactive solutions before they impact patient care. Observability offers IT teams the tools to automate workflows, predict failures, and ensure that critical systems remain operational, even in the face of challenges. As healthcare systems continue to evolve, integrating observability into IT operations will be key to ensuring seamless and reliable patient care around the clock.
Source: HealthTech
Image Credit: iStock
