2018-019 – Medical Decision Support: A Guideline Database Application

Background In order to provide all patients with the standards of care, it is crucial to be able to readily access practice guidelines which are high level evidence documents that provide guidance as to the standards of care that all patients should receive. Being able to follow basic guidelines recommendations help to lower healthcare costs, decreases the amount of unnecessary tests, decreases subspecialty consultations, improves efficiency of care, and decrease medical errors. The American Medical Association (AMA) recognizes 176 medical specialties, of which there are a growing number of published guideline documents that are consistently being updated and published. There are currently >8000 of these published guidelines. These issues make it difficult to find information immediately and answer clinical question in real-time. As in primary care or general practice clinics, there is the shortfall of in-depth understanding of a vast number of complex diseases and being able to navigate appropriateness of care and, at times, complex clinical decisions. Even though there are multiple applications and online resources available, the information is often too basic, too cumbersome to obtain, and not centralized or in a cohesive and comprehensive collection. There is a present need for a system that provides easy access to practice guidelines in a cohesive and comprehensive manner. Technology Description Researchers at The University of New Mexico are developing a new platform that will use artificial intelligence to automate transitioning of current published practice guideline documents into an organized database, that will serve as a cumulative repository of current medical knowledge quintessence. Such database may be linked and be utilized by existing and future medical decision support tools. Such medical decision support tools will provide clinicians with easy access to practice guidelines in order to ensure high levels of evidence and standard of care for a wide range of diseases. They will help providers that do not have readily available access to subspecialty care, especially those who practice in rural settings or areas of medical shortages. Gregg Banninger GBanninger@innovations.unm.edu 505-272-7908