Geriatrics Commons^™

Can Variables From The Electronic Health Record Identify Delirium At Bedside?, Ariba Khan, Kayla Heslin, Michelle Simpson, Michael L. Malone

Journal of Patient-Centered Research and Reviews

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 …

An Automated Model Using Electronic Health Record Data To Identify Delirium Among Hospitalized Older Adults: A Pilot Project, Ariba Khan, Maharaj Singh, Hina Singh, Ayesha Maria, Michelle Simpson

Journal of Patient-Centered Research and Reviews

Background: Delirium is a serious change in mental status with adverse outcomes, but remains underrecognized. The electronic health record (EHR) may assist in the identification of delirium.

Purpose: This study was performed to generate an automated delirium identification model using data from the EHR among hospitalized older adults.

Methods: Inpatients 65 years and older were included in this cross-sectional study. The researchers used “confusion assessment method” as the gold standard to identify delirium. Four categories of variables were obtained from the EHR on the day of and the day prior to researcher assessment: 1) hypoactive delirium (any one of the …

Prognostic Indices For Hospitalized Older Adults: A Meta-Analysis And Systematic Review, Ariba Khan, Ayesha Maria, James Hocker, Maharaj Singh, Michelle Simpson

Journal of Patient-Centered Research and Reviews

Background: A prognostication predictive model incorporated into the electronic health record (EHR) may be useful in assisting the health care team in accurately predicting mortality and may be used in appropriately allocating palliative care services.

Purpose: To systematically review and summarize current medical literature regarding the factors predictive of mortality in an inpatient population above 65 years of age.

Methods: Nondisease-specific prognostication indices that predict 1-year mortality in an inpatient population of adults over age 65 were included. We excluded studies that estimated intensive care unit, disease-specific or in-hospital mortality. A MEDLINE, CINAHL, Ovid and Cochrane literature search of English-language …