Top 5 Healthcare Challenges Solved by Observability Tools

Healthcare IT systems are the lifeblood of any modern healthcare organization. From electronic health records (EHRs) to intricate pharmacy systems that dispense life-saving drugs, every system plays a critical role in delivering timely and effective patient care. But when these systems falter, the human cost can be significant.

This is where observability comes into play, showcasing its value. But what makes it indispensable for healthcare organizations? And what challenges does it solve? This blog will uncover the top challenges healthcare IT leaders face and how observability can help streamline operations, reduce downtime and improve patient outcomes.

Observability is the maturation of traditional monitoring practices. Monitoring typically focuses on identifying when something goes wrong, such as a server being down. Traditional monitoring requires teams to watch and respond to incidents, but over time, teams develop alert fatigue, making it challenging to discern emergencies until something critical goes down.

Observability, on the other hand, takes things a step further by providing visibility into the "why."

It collects and correlates telemetry data — such as logs, metrics and traces — from across systems to reveal the root cause of issues in real time. This holistic insight helps organizations be proactive, rather than reactive, in managing their IT ecosystems.

Healthcare systems are expected to operate at five nines — or 99.999% — of uptime, meaning they can experience downtime for just under five minutes per year. And yet, legacy systems, siloed teams and growing complexities make this a steep hill to climb.

Observability helps healthcare IT teams achieve greater reliability through faster issue identification, reduced incident resolution times, and the ability to predict and prevent future failures. Through context correlation, when configured correctly, observability removes the need for teams to explain whether something is or isn’t their issue to fix, and it alerts the teams that need to begin solving the incident.

Let's examine the top five challenges observability addresses in healthcare IT.

Few industries demand as much uptime as healthcare. Getting to the five nine uptime with traditional monitoring is near impossible. A failure in a critical system — like EHRs or a picture archiving and communication system (PACS) — can delay treatment or even stall care altogether. The stakes are high, as even a few minutes of downtime can disrupt patient treatment plans or delay surgeries.

How Observability Helps: 

Observability allows healthcare organizations to centralize data collection and analysis, providing a single source of truth. Rather than juggling dozens of monitoring tools, healthcare IT leaders can consolidate operations and establish uniform observability standards.

Correlated data insights can pinpoint the exact components causing an issue. If the problem stems from external connectivity, observability can direct the network team to resolve it, saving other departments from scrambling unnecessarily.

This ability to localize and address issues dramatically reduces downtime and improves system reliability.

Most healthcare IT environments are highly siloed. Separate teams manage myriad areas, such as networks, applications, databases and servers. This sometimes leads to a "not my problem" mentality during incidents, making resolving issues slow and cumbersome, and creating unnecessary internal friction.

How Observability Helps: 

Observability breaks down silos by aggregating data from disparate systems into a unified dashboard. Everyone has access to the same information, eliminating the guesswork about who is responsible.

By providing context to alerts (e.g., "This issue originates from the database server"), teams can collaborate more effectively instead of wasting time proving innocence.

The result? Streamlined workflows and faster resolution during incidents.

Healthcare organizations frequently grow through mergers and acquisitions. While beneficial for scalability, this practice creates complex IT environments with duplicate tools and fragmented systems. Managing and integrating these tools becomes a monumental task.

How Observability Helps: 

Observability platforms centralize data collection and analysis, offering a single source of truth. Rather than juggling dozens of monitoring tools, healthcare IT leaders can consolidate operations and establish uniform observability standards.

This simplifies governance, eliminates redundant tools and provides better oversight over sprawling IT environments. With observability, mergers can become more seamless, ensuring business continuity and minimizing disruptions to patient care.

Revenue cycles and operational stability are important, but in healthcare, the biggest concern is always patient safety. If a key system like a pharmacy management tool goes down, patients may not get their medications on time.

How Observability Helps: 

Observability ensures seamless access to critical systems by enabling predictive alerts. For example, if CPU usage in a drug-dispensing system is climbing at an abnormal rate, observability tools can flag this before it leads to downtime.

Automated remediation processes can fix issues instantly or alert the right personnel for rapid intervention, ensuring minimal impact on services.

This proactive approach protects patients while maintaining operational efficiency.

While large healthcare systems often have the resources to deploy fully self-aware, automated observability solutions, smaller healthcare organizations face budget constraints and legacy systems. However, they still require IT visibility to maintain stability and patient care.

How Observability Helps: 

Observability can be scaled to accommodate businesses of varying sizes, making it accessible for small hospitals. Affordable, modular observability solutions can meet the requirements of many organizations.

For smaller IT teams, observability simplifies processes by aggregating telemetry data in one tool rather than requiring knowledge of multiple complex systems.

Some advanced observability platforms even go beyond current issues, offering predictive monitoring. By analyzing historical data trends, they can anticipate problems before they arise.

For example, increasing CPU or disk usage over several weeks might signal an impending system crash. Artificial intelligence-powered tools can flag this as a risk, providing IT teams with time to prevent the issue — potentially avoiding outages altogether.

From ensuring the reliability of life-critical systems to reducing friction between teams, observability has the potential to revolutionize healthcare IT. By offering proactive insights, streamlining tools and breaking down silos, observability equips healthcare organizations to operate with efficiency, precision and agility — even in the most complex environments.

With patient care and safety on the line, investing in observability is no longer optional — it’s essential.