Publication Date
7-18-2022
Keywords
delirium, electronic health record, ethnoracial, diagnosis, disease prediction model
Abstract
Delirium, a common and serious disorder in older hospitalized patients, remains underrecognized. While several delirium predictive models have been developed, only a handful have focused on electronic health record (EHR) data. This prospective cohort study of older inpatients (≥ 65 years old) aimed to determine if variables within our health system’s EHR could be used to identify delirium among hospitalized patients at the bedside. Trained researchers screened daily for delirium using the 3-minute diagnostic Confusion Assessment Method (3D-CAM). Patient demographic and clinical variables were extracted from the EHR. Among 408 participants, mean age was 75 years, 60.8% were female, and 82.6% were Black. Overall rate of delirium was 16.7%. Patients with delirium were older and more likely to have an infection diagnosis, prior dementia, higher Charlson comorbidity severity of illness score, lower Braden Scale score, and higher Morse Fall Scale score in the EHR (P < 0.01 for all). On multivariable analysis, a prior diagnosis of dementia (odds ratio: 5.0, 95% CI: 2.5–10.3) and a Braden score of < 18 (odds ratio: 2.8, 95% CI: 1.5–5.1) remained significantly associated with delirium among hospitalized patients. Further research in the development of an automated delirium prediction model is needed.
Recommended Citation
Khan A, Heslin K, Simpson M, Malone ML. Can variables from the electronic health record identify delirium at the bedside? J Patient Cent Res Rev. 2022;9:174-80. doi: 10.17294/2330-0698.1890
Online Supplemental Figure S1
Included in
Critical Care Commons, Critical Care Nursing Commons, Diagnosis Commons, Geriatrics Commons, Health Information Technology Commons, Health Services Research Commons, Mental Disorders Commons, Neurology Commons, Other Mental and Social Health Commons, Palliative Nursing Commons, Patient Safety Commons, Primary Care Commons
Submitted
July 6th, 2021
Accepted
January 20th, 2022
