A Tale of Two Methods: Chart and Interview Methods for Identifying Delirium
Saczynski, Jane S.
Kosar, Cyrus M.
Puelle, Margaret R.
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CitationSaczynski, Jane S., Cyrus M. Kosar, Guoquan Xu, Margaret R. Puelle, Eva Schmitt, Richard N. Jones, Edward R. Marcantonio, Bonnie Wong, Ilean Isaza, and Sharon K. Inouye. 2014. “A Tale of Two Methods: Chart and Interview Methods for Identifying Delirium.” Journal of the American Geriatrics Society 62 (3) (February 10): 518–524. doi:10.1111/jgs.12684.
To compare chart- and interview-based methods for identification of delirium.
Prospective cohort study.
Two academic medical centers.
Individuals aged 70 and older undergoing major elective surgery (N = 300) (majority orthopedic surgery).
Participants were interviewed daily during hospitalization for delirium using the Confusion Assessment Method (CAM; interview-based method), and their medical charts were reviewed for delirium using a validated chart-review method (chart-based method). Rate of agreement of the two methods and characteristics of those identified using each approach were examined. Predictive validity for clinical outcomes (length of stay, postoperative complications, discharge disposition) was compared. In the absence of a criterion standard, predictive value could not be calculated.
The cumulative incidence of delirium was 23% (n = 68) according to the interview-based method, 12% (n = 35) according to the chart-based method, and 27% (n = 82) according to the combined approach. Overall agreement was 80%; kappa was 0.30. The methods differed in detection of psychomotor features and time of onset. The chart-based method missed delirium in individuals that the CAM identified who were lacking features of psychomotor agitation or inappropriate behavior. The CAM-based method missed chart-identified cases occurring during the night shift. The combined method had high predictive validity for all clinical outcomes.
Interview- and chart-based methods have specific strengths for identification of delirium. A combined approach captures the largest number and broadest range of delirium cases.
Citable link to this pagehttp://nrs.harvard.edu/urn-3:HUL.InstRepos:32605865
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