Fighting Deadly Infections in Hospitals

Overview

Hospital-acquired infections (HAIs) remain one of the greatest threats to patient safety, contributing to thousands of preventable deaths each year. Yet many hospitals lack the tools to proactively track and respond to emerging infection threats. The core problem? Inconsistent data, slow reporting, and rigid detection systems that fail to adapt to real-time infection and resistance patterns.

As a UX leader, I designed a flexible, real-time infection control and Antimicrobial Stewardship (AMS) intelligence platform that empowered clinicians to detect and manage outbreaks dynamically and proactively —instead of being constrained by inflexible, pre-built rules.

The Challenge

The Growing Threat of HAIs

• HAIs are life-threatening and costly, yet hospitals struggle to consistently perform up to expectations in this area.
• Infection control teams rely on incomplete, inconsistent, and messy data spread across multiple systems, making real-time decision-making almost impossible.
• AMS programs are a huge boon to fighting the problem, but it’s an extremely complicated field that requires dedicated, highly specialized experts that are very expensive.

Rigid, Outdated Detection Systems

• Most existing infection tracking tools used static rule sets, which meant hospitals could only react to infections after the fact, rather than prevent them in real time.
• Clinicians needed more flexibility to respond to evolving resistance patterns and outbreaks as they emerged.

The Data Normalization Problem

• Hospital systems operate on different EHRs, data formats, and reporting standards, making it nearly impossible to track infections consistently across a health system.
• Infection prevention teams needed a tool that could make sense of messy data and provide clear, reliable insights—regardless of data source or structure.

The UX Strategy

I led the UX strategy and design for a dynamic infection control and AMS platform that solved these problems by focusing on flexibility, real-time response, and data standardization.

1. A Customizable, Rule-Building System for Clinicians

• Designed an intuitive “build-your-own-rule” interface that allowed infection control teams to construct and modify detection rules in real-time using a simple, intuitive UI with a semantic, medical term-oriented structure.
• Gave hospitals the ability to proactively adjust infection tracking criteria based on live data and emerging threats.
• Allowed our in house clinicians to create their own AMS and infection response content, then publish it out to customers. Hospitals that couldn’t afford dedicated AMS teams could now rely on our expertise.

2. Real-Time Infection & Resistance Pattern Tracking

• Built a visually intuitive dashboard that provided a comprehensive, real-time view of infection outbreaks, resistance patterns, and antibiotic effectiveness.
• Designed dynamic alerts and visualization tools to help AMS teams respond proactively, preventing outbreaks before they spread.

3. Data Normalization for Cross-System Accuracy

• Built a data normalization engine that transformed messy, inconsistent hospital data into a standardized, structured format, making it usable and reliable across entire health systems.
• Enabled hospitals using different EHRs and reporting structures to track infections with a unified, consistent framework—for the first time.

The Impact

Clinician-Praised Industry Leader

• The infection management platform rose to #1 in KLAS industry rankings, as voted on by clinicians, thanks to its usability, flexibility, and clinical impact.

Real-Time, Dynamic Infection Management

• Clinicians could now build and adjust detection rules on the fly, ensuring infection tracking adapted to real-time threats, rather than relying on outdated, static criteria.

Unprecedented Market Growth & Rapid Expansion

• When CMS expanded regulations to include Antimicrobial Stewardship (AMS) reporting, our flexible, easily scalable platform enabled us to quickly pivot to meet new standards. The results paid divdends immediately, and several years later when regulation conditions stiffened.
• This led to a surge in new customers, outpacing competitors who struggled with rigid, slow-to-adapt systems.

More Accurate & Reliable Clinical Decision-Making

• The data normalization framework allowed hospitals to analyze infection trends consistently across multiple locations, improving accuracy, response times, and patient outcomes.

Key Takeaways

Empowering clinicians with flexibility is the key to better patient outcomes—allowing users to create and modify their own detection rules meant hospitals could respond to infections faster and more effectively.

Data standardization is critical in healthcare UX—by normalizing messy, inconsistent data across different hospital systems, we provided reliable, actionable insights that saved lives. This continues to be a huge problem across health systems, which came to be through acquisition, leaving a patchwork of EHR and data systems that make care consistency and extremely challenging ordeal.

Adaptability drives market success—our scalable, user-driven design allowed us to capitalize on regulatory changes and secure rapid customer growth.

Conclusion

By designing a clinician-first, flexible infection control platform, we transformed the way hospitals detect and prevent deadly infections. Instead of being trapped by outdated, slow-to-adapt tools, infection prevention teams now had a dynamic, proactive system that allowed them to fight HAIs in real time—protecting patients and improving outcomes across entire health systems.