--- title: "Going Beyond Atlas: Building a Learning Health System" description: Building a Learning Health System-Overcome Atlas's limitations with an integrated platform for research, enhanced data access+driving impactful discoveries image: https://cognome.com/hubfs/AI-Generated%20Media/Images/The%20image%20depicts%20a%20modern%20healthcare%20facility%20bustling%20with%20activity.jpeg --- [Skip to content](https://cognome.com/blog/going-beyond-atlas#main-content) [![Smarter Safer Secure AI for Healthcare](https://cognome.com/hs-fs/hubfs/Smarter%20Safer%20Secure%20AI%20for%20Healthcare.png?width=2000&height=600&name=Smarter%20Safer%20Secure%20AI%20for%20Healthcare.png)](https://cognome.com/) - AI Governance Show submenu for AI Governance - [AI Sniffer™](https://cognome.com/ai-sniffer) - [ExplainerAI™](https://cognome.com/en-us/explainerai-new) - [Data Services](https://cognome.com/ai-ml-services) Show submenu for Data Services - [OMOP Transforms](https://cognome.com/ai-ml-services) - [Self-Service for Research](https://cognome.com/solutions-for-research) - [AutoChart™ - Quality and Population Health](https://cognome.com/autochart) - Insights Show submenu for Insights - [About](https://cognome.com/our-story) - [Blog](https://cognome.com/blog) - [The Learning Health System Podcast](https://cognome.com/learning-health-system-podcast) - [Published Research](https://cognome.com/peer-reviewed-research) - [Partner Login](https://partners.cognome.com/) Open main navigation Close main navigation - AI Governance Show submenu for AI Governance - [AI Sniffer™](https://cognome.com/ai-sniffer) - [ExplainerAI™](https://cognome.com/en-us/explainerai-new) - [Data Services](https://cognome.com/ai-ml-services) Show submenu for Data Services - [OMOP Transforms](https://cognome.com/ai-ml-services) - [Self-Service for Research](https://cognome.com/solutions-for-research) - [AutoChart™ - Quality and Population Health](https://cognome.com/autochart) - Insights Show submenu for Insights - [About](https://cognome.com/our-story) - [Blog](https://cognome.com/blog) - [The Learning Health System Podcast](https://cognome.com/learning-health-system-podcast) - [Published Research](https://cognome.com/peer-reviewed-research) - [Partner Login](https://partners.cognome.com/) - [Contact us](https://cognome.com/contact-us) [Contact us](https://cognome.com/contact-us) Jan 13, 2025, 5:11:23 PM # Going Beyond Atlas: Building a Learning Health System ![Picture of James Green](https://cognome.com/hs-fs/hubfs/Jame%20Green.png?width=50&name=Jame%20Green.png) [James Green](https://cognome.com/blog/author/james-green) Share: [facebook-f icon](http://www.facebook.com/share.php?u=https://cognome.com/blog/going-beyond-atlas) [linkedin-in icon](http://www.linkedin.com/shareArticle?mini=true&url=https://cognome.com/blog/going-beyond-atlas) [Twitter icon](https://twitter.com/intent/tweet?url=https://cognome.com/blog/going-beyond-atlas) [pinterest-p icon](http://pinterest.com/pin/create/link/?url=https://cognome.com/blog/going-beyond-atlas) [envelope icon](mailto:?body=https://cognome.com/blog/going-beyond-atlas) The concept of a Learning Health System (LHS) – where data seamlessly flows to improve patient care and drive research – is gaining traction. However, existing tools like Atlas, while valuable for collaborative research across institutions, often fall short of meeting the unique needs of individual health systems. Episode 3 of our Learning Health System podcast Explores the challenges of using Atlas within a single health system and highlights the innovative approach developed at Montefiore. ## Limitations of Atlas Atlas, a popular platform for observational health research, primarily focuses on: - **De-identified data:** Limiting its applicability for many internal research projects that require access to identifiable patient information. - **External collaboration:** It's designed for collaborative research across institutions, neglecting the need for integration with internal systems like EHRs, registries, and biorepositories. - **Limited compliance features:** Atlas doesn't adequately address the complexities of internal IRB reviews, data security, and compliance requirements within a healthcare system. ## Building a True Learning Health System Montefiore has addressed the limitations of Atlas by: - **Handling diverse data types:** Seamlessly integrating identified and de-identified data, clinical notes, images, and data from external sources. - **Deep system integration:** Connecting with internal systems like EHRs, registries, and biorepositories, enabling researchers to link patient data from various sources. - **Robust security and compliance:** Implementing robust security measures, audit trails, and integration with IRB systems to ensure compliance and protect patient privacy. - **User-friendly interface:** Providing a user-friendly interface that simplifies study design, data extraction, and analysis for researchers. - **Focus on patient empowerment:** Enabling patient-centered consent and allowing patients to control how their data is used in research. ## Key Differentiators - **Handling identified data:** The system effectively manages both identified and de-identified data, allowing for a wider range of research applications. - **Integration with internal systems:** Seamlessly integrating with various internal systems enhances research capabilities and enables more comprehensive analyses. - **Enhanced security and compliance:** Robust security measures and integration with IRB systems ensure responsible data usage and protect patient privacy. - **Advanced data extraction and analysis:** The system facilitates the extraction of relevant data, aligning with study designs and enabling efficient analysis. - **Patient-centered approach:** The system prioritizes patient empowerment by enabling patient-centered consent and allowing patients to control their data usage. ## Conclusion Building a true LHS requires a more comprehensive and integrated approach than what existing tools like Atlas can provide. The innovative approach developed at Montefiore demonstrates how a health system can overcome these limitations by creating a platform that is tailored to its specific needs and priorities. This approach can serve as a model for other health systems seeking to leverage data for improved patient care and impactful research. 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We... [Read more](https://cognome.com/blog/cognome-and-intel-partnership) [![](https://cognome.com/hs-fs/hubfs/Protecting%20patient%20privacy%20in%20healthcare%20with%20a%2016_9%20image%20ratio.jpeg?height=200&name=Protecting%20patient%20privacy%20in%20healthcare%20with%20a%2016_9%20image%20ratio.jpeg)](https://cognome.com/blog/fine-tuning-clincialbert) [AIModel](https://cognome.com/blog/tag/aimodel), [AI](https://cognome.com/blog/tag/ai), [LLM](https://cognome.com/blog/tag/llm), [Privacy](https://cognome.com/blog/tag/privacy), [De-Identification](https://cognome.com/blog/tag/de-identification) ## [Fine Tuning a ClinicalBERT Based Model](https://cognome.com/blog/fine-tuning-clincialbert) ![Picture of Adil Ahmed](https://cognome.com/hs-fs/hubfs/Adil.jpeg?width=50&name=Adil.jpeg) [Adil Ahmed](https://cognome.com/blog/author/adil-ahmed) Oct 30, 2024, 10:43:52 AM Enhancing PHI De-Identification for Diverse Patient Populations Protecting patient privacy is at... 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