A normalization engine is a software tool that leverages a set of algorithms to transform diverse healthcare data into a consistent, structured, and standardized format. Normalization is critical in healthcare since clinical patient information, diagnoses, medications, procedures, and test results are expressed in different formats, through various terminologies, and with varied levels of accuracy.

High quality, standardized data is the foundation of countless initiatives. For example, reporting and analytics – and the insights they reveal – are only as effective as the data they start with. The same holds true for monitoring population health trends or identifying at-risk groups: without clean and complete data, desired health outcomes are elusive. Normalized data facilitates clinical trial design and regulatory compliance, leading to faster and more informed decision making, and the same principle applies to the development of health IT products: quality data inputs lead to more reliable and trustworthy solutions.

NLP – or natural language processing – is a subfield of artificial intelligence (AI) that allows computers to understand and process human language. In healthcare, NLP focuses on extracting meaningful insights from textual data including clinical notes, patient records, research papers, and public health data.

NLP’s ability to extract clinical and biomedical concepts from free text and automatically assign standard codes enhances documentation while reducing the burden of administrative tasks and improving billing accuracy. By converting free-text notes into structured data, NLP also makes this information easier to search, analyze, and share.

Value sets – groups of codes and corresponding terms that define clinical concepts – are used to identify specific patient populations for initiatives like quality reporting and clinical trials recruitment. A value set management tool provides a centralized solution for storing, accessing, building, updating, exporting, and/or downloading these patient groupings. Ideally, if cloud-based, these tools serve as a value set repository and editor that can be accessed by various users and departments across an organization.

Value set management tools can help minimize the burden of administrative tasks
and their associated costs by reducing the need for manual maintenance and curbing
version control issues. These solutions also promote cooperation and knowledge
exchange through shared access to accurate, current value sets that establish a common understanding of specific concepts.