title: Automatic delirium prediction system in a Korean surgical intensive care unit.
abstract: BACKGROUND
  In Korea, regular screening for delirium is not considered essential. In addition, delirium is often associated with vague concepts, making it harder to identify high-risk patients and impeding decision-making.
  
  
  OBJECTIVE
  To assess the impact of the Automatic PREdiction of DELirium in Intensive Care Units (APREDEL-ICU) system on nursing-sensitive and patient outcomes for surgical ICU patients and to evaluate nurse satisfaction with the system and its usability.
  
  
  METHODS
  A pre-post research design was adopted. Our study included 724 patients admitted before the implementation of the APREDEL-ICU (January to December 2010) and 1111 patients admitted after the system was installed (May 2011 to April 2012). The APREDEL-ICU uses a pop-up window message to inform the nursing staff of patients at risk for delirium, allowing evidence-based nursing interventions to be applied to the identified patients. A total of 42 nurses were surveyed to determine the system's usability and their level of satisfaction with it.
  
  
  RESULTS
  After the implementation of APREDEL-ICU, high-risk patients, determined using a prediction algorithm, showed a slight decrease in the incidence of delirium, but the changes were not significant. However, significant decreases in the number and duration of analgesic/narcotic therapies were observed after the implementation of the system. Nurse self-evaluation results showed an improvement in all categories of knowledge regarding delirium care.
  
  
  CONCLUSIONS
  The use of a prediction and alerting system for ICU patients at high risk of delirium showed a potential increase in the quality of delirium care, including early detection and proper intervention.
authors.affiliation: Surgical Intensive Care Unit, Seoul St. Mary's Hospital, Seoul, Korea.
authors.forename: Suk-Hwa
authors.initials: SH
authors.lastname: Oh
authors.forename: Eun-Ju
authors.initials: EJ
authors.lastname: Park
authors.forename: Yinji
authors.initials: Y
authors.lastname: Jin
authors.forename: Jinshi
authors.initials: J
authors.lastname: Piao
authors.forename: Sun-Mi
authors.initials: SM
authors.lastname: Lee
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D003693:Delirium / Q000175:diagnosis* / Q000451:nursing*; D057286:Electronic Health Records; D055318:Evidence-Based Nursing; D005260:Female; D006801:Humans; D007362:Intensive Care Units; D008297:Male; D008403:Mass Screening / Q000295:instrumentation*; D008875:Middle Aged; D009730:Nursing Assessment; D056910:Republic of Korea; D012307:Risk Factors
keywords: Delirium; Nursing sensitive outcomes; Patient outcomes; Risk assessment