Using Concept Unique Identifiers to Filter Electronic Health Records for Delirium Cases. Issue 9 (22nd September 2021)

• Record Type: Journal Article
• Authors: Oosterhouse, Kimberly J.; Young, Cynthia D.; Desai, Manushi; Birch, Steven; Price, Ron; Bobay, Kathleen L.
• Is Part Of: Computers, informatics, nursing. Volume 39:Issue 9(2021)
• Page Start: 471
• Page End: 476
• Publication Date: 2021-09-22
• Subjects: Concept unique identifiers -- Delirium -- Electronic health records -- Older adults -- Unified Medical Language System; Nursing -- Data processing -- Periodicals; 610.730285
• DOI: 10.1097/CIN.0000000000000710
• Languages: English
• ISSNs: 1538-2931

Abstract

Abstract : Delirium, an acute mental status change associated with inattention, confusion, hypervigilance, or somnolence due to a medical cause, is considered a medical emergency. Unfortunately, screening and diagnosis of delirium in acute care are often inadequate. It is estimated that 60% of delirium cases are not identified, and in claims data, they are underreported. Using information technology, we investigated whether concept unique identifiers from the Unified Language Medical System Metathesaurus could be used as a method to filter electronic health records for possible delirium cases. This article provides the reader with an overview of delirium, the Unified Language Medical System Metathesaurus, and our method for retrospectively filtering electronic health records for delirium cases from our clinical research database. Using a retrospective observational approach, we randomly selected 150 electronic health records with narrative notes containing a delirium concept unique identifier. One hundred records were used for training and 50 were used for validation and interrater reliability. Our results validate electronic health record–selected concept unique identifiers and provide insights into their use. Refinement and application of this method on a larger scale can provide an initial filter for identifying patients with delirium from the electronic health record.