How LOGEX safeguards healthcare data with GX

Quick facts about LOGEX

Location: Amsterdam, Netherlands 

Industry: Healthcare technology and data

Company size: 400+

Data quality team size: < 10

Background

LOGEX’s Healthcare Intelligence Suite offers a wide range of data solutions that support clinicians, regulators, and decision-makers in providing the best possible care. Their solutions include financial analytics, patient engagement, clinical registries, and dataset services.

The quality of the data, including hospital data, needs to be evaluated and ensured to provide insights on which customers can base their decisions.  
However, hospitals have other priorities than making sure their data are perfect. In fact, it is only a distant secondary priority behind providing care to patients.  But a hospital’s dataset is critical for a whole host of important post-treatment activities: regulatory compliance, monitoring treatment effectiveness, capacity planning, cost forecasting, and more.

Without purposeful attention to their data’s quality, hospitals often find that their data falls short of the standards needed to achieve these goals. Missing values, inconsistencies, and other quality issues make datasets nearly—if not completely—unusable for confident data-driven decisions.

To bridge the gap efficiently, LOGEX built a backend application that integrates with GX Core, which provides the data quality framework. With GX Core providing expert-informed data quality tests and results, LOGEX’s application allows analysts and customers to visually inspect issues in their raw data and take corrective actions like fixing errors or resubmitting data.

By ensuring that quality issues are detected and resolved before the data moves further down LOGEX’s pipeline, GX Core plays a vital role in LOGEX’s ecosystem: it lets LOGEX and its customers have confidence that their downstream insights and decisions from the Healthcare Intelligence Suite are based on reliable information.

“Addressing these data quality issues is essential before the data can proceed through LOGEX’s processing pipeline, ensuring that downstream insights and decisions are based on reliable information.” - Maria Zilli, Data Engineer

Challenges

LOGEX faced many of the data quality issues that challenge organizations today, including:

Varied and complex data: Healthcare data comes from a wide range of sources, each with its own structures, standards, and potential issues. With business spanning 10 countries, there’s an additional layer of competing standards and different local languages. LOGEX needs to be able to understand and reconcile this variety of data to maintain accuracy and consistency across all datasets.

Issue identification and resolution: Hospital data often has multiple layers of errors, including missing values and discrepancies. Before the data can be processed further, these issues need to be identified, flagged, and resolved. This level and complexity of monitoring requires robust and efficient tools.

Balancing automation and customization: Automating data quality checks is essential for any degree of scalability. But since each hospital and dataset has unique requirements, quality tests also frequently need customization.

Ensuring seamless data flow: Many data-driven decisions are time-sensitive, so even minor disruption to a data processing pipeline can have significant impacts. Resolving data quality issues quickly is critical to ensuing that pipelines flow smoothly.

Solution

The LOGEX team developed a Python backend application that uses a seamless integration with GX Core to evaluate and report on data quality.

Proactive

Using this application, data quality issues are flagged before the data enters LOGEX’s processing pipeline. The analysts and customers who submit the data can see the issues found in their data, then fix errors or resubmit the data to remediate those issues.

Adaptable

With GX Core, LOGEX was able to create simpler validation rules for its complex data with its library of prebuilt Expectations. In addition to using Expectations directly out of the box, LOGEX also adapted and extended these Expectations to meet their specific requirements.

GX Core’s flexible parameter functionality is especially valuable to LOGEX: It enables them to dynamically reference external parameters and create adaptable, context-aware checks. Context awareness is critical for LOGEX’s multinational data, which has a variety of local standards, formats, and languages.

With support from GX Core, LOGEX is able to ensure that the data entering their pipeline is accurate, consistent, and ready for analysis. With errors minimized and data quality errors resolved early in the process, LOGEX has improved over the overall reliability and impact of the insights they derive from their hospital data.

Impact

With the high-quality data—and resulting insights and analytics—simplified by GX Core, LOGEX can maintain and further develop its leading role in healthcare analytics 

Its trustworthy data ensures that healthcare providers can use the Healthcare Intelligence Suite to make complex decisions with confidence. Ultimately, this leads to better conditions for healthcare providers and better outcomes for patients.

Ready to see how GX Cloud can give you and your team confidence in your high-stakes data? Request a demo.