Umerse is an intuitive, powerful universal Electronic Medical Record Search Engine.

• An intuitive, powerful search engine for free-text documents in the electronic medical record.
• Offers multiple options for creating complex search queries yet has an interface that is easy enough to be used by those with minimal computer experience.
• Ideal for retrospective chart reviews and data abstraction and may have potential for clinical care as well.

The deployment and adoption of electronic medical records in order to improve the quality and delivery of patient care has recently been receiving growing attention. Due to the complexity and time constraints associated with documenting a clinical encounter, the majority of patient information is still stored in free-text documents as opposed to discrete coded data elements. This has created a paradox for many institutions because, while the data are in electronic format, access to specific information of interest is not readily available through automated means.

Data mining techniques have sought to address components of this problem, but the methodology usually involves experts with advanced technical skills. Additionally, humans are still often needed to review a document to ensure accurate data abstraction. Search engines have become highly popular among regular computer users and their utility for identifying appropriate medical literature has been increasingly discussed. While some attempts have been made to apply the power of search engines to the electronic medical record, the widespread adoption of such technology has not yet been realized.

Umerse was built in order to address the need for searching the medical record for research and data abstraction. Umerse is secure, maintains an audit trail. Umerse provides an easy-to-use, intuitive user interface for constructing complex search queries and scanning context-sensitive search results. Results are displayed in a manner consistent with the structure of the medical record, including separate categories for the problem summary list, patient notes, and pathology and radiology reports. It offers powerful features, such as the ability to look for potential spelling errors in the documents as well as the ability to perform batch searches across multiple patients at once