Critical Care Nursing 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 …

A Case For Delirium Risk Prediction Models To Aid In Triaging Resources To Those Most At Risk An Integrative Literature Review, Tammy Perttula

Nursing Masters Papers

Abstract

Delirium is a complex syndrome resulting from compounding effects of acute illness, comorbidities, and the environment. It results in adverse outcomes: elevated mortality rates, length of stay, readmissions, institutionalization, long-term cognitive changes, and diminished quality of life. The rate of iatrogenic delirium is astounding, ranging from 10%-89%. There are no curative treatments; thus, primary prevention is the key. The purpose of this literature review is to identify and critique the research for the accuracy of risk stratification and feasibility in practice. Support for interventions that prevent delirium is mounting; however, interventions are resource-intensive and often not implemented. Researchers have …