Nursing assessment as an effective tool for the identification of delirium risk in older in‐patients: A case–control study

Abstract

Aims and objectives:To evaluate the usefulness of comprehensive nursing assessment as a strategy for determining the risk of delirium in older in-patients from a model of care needs based on variables easily measured by nurses.Background: There are many scales of assessment and prediction of risk of delir-

Acuity, nurse staffing and workforce, missed care and patient outcomes: A cluster‐unit‐level descriptive comparison

“…It is known that phlebitis is more likely to occur at any time, with increased catheter days and patient length of stay (LOS) (Ansel, Boyce, & Embree, 2017). Likewise, delirium is more likely to occur in patients with uncontrolled pain (Solà‐Miravete et al., 2018), which is consistent with the findings in this study. Finally, most SDU patients in this inquiry matched a surgical profile, which might exemplify the importance of outcome sensitivity measurement when considering selected target populations.…”

The utility of nursing instruments for daily screening for delirium: Delirium causes substantial functional impairment

“…Beyond confirming previous results of the impact of delirium on the level of functioning (Sola-Miravete et al, 2018), numerous new aspects of functional impairment have been elucidated in this study. This study helps to better understand delirium in the intensive care setting and could aid in profiling patients at risk for delirium and direct interventions.…”

“…The most comprehensive study to date assessed nursing tools for delirium identification and showed the following domains relevant to this study: Problems with nutrition and elimination, as well as self-care and mobility (Sola-Miravete et al, 2018). This study was performed on elderly patients on regular surgical and medical floors.…”

Development and Validation of an Electronic Health Record–Based Machine Learning Model to Estimate Delirium Risk in Newly Hospitalized Patients Without Known Cognitive Impairment

“…Existing clinical delirium risk prediction tools have achieved areas under the receiver operating characteristic curve (AUCs) of 0.69 to 0.81. 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 For example, UCSF Health (the University of California, San Francisco, Medical Center system) uses the AWOL screening tool to calculate delirium risk for newly admitted patients. 12 This tool assigns 1 point for each of the following criteria: age greater than 79 years; inability to spell world backward; disorientation to city, state, county, hospital name, or floor; and nurse-rated moderate or severe illness severity.…”

“…Furthermore, existing tools recapitulate well-studied delirium risk factors, such as cognitive impairment at baseline, delirium on admission, and severe illness. 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 For this subpopulation of patients with unambiguous risk of developing hospital-acquired delirium, UCSF Health routinely provides delirium prevention precautions. However, it remains of crucial importance to identify and intervene on behalf of patients with elevated risk of incident delirium who lack these apparent risk factors on admission.…”