UNIVERSITY PARK, Pa. — Delirium is an acute but reversible sudden onset of confusion that is common in older adults. Although delirium screening is critical to delirium identification, many clinicians cite lack of time as one reason for being unable to fit it into their daily workload — thus over half of all delirium cases go unrecognized, according to an interdisciplinary team of researchers.
Nursing faculty and team identify time-efficient, delirium-screening protocol
Multiple Principal Investigator (MPI) Edward Marcantonio, from Harvard University, teamed up with Penn State College of Nursing professors Donna Fick (MPI), Marie Boltz and Project Director Erica Husser, and others to combat this issue by examining four delirium identification assessment protocols to better understand how to improve time efficiency and ultimately, delirium identification.
Data for the research came from two studies; the first conducted at an urban academic medical center and included interviews with 201 inpatients — aged 75 years or older — using the 3-Minute Diagnostic Confusion Assessment Method (3D-CAM) protocol. The second study involved the same academic medical center and a rural community hospital; combined, 330 inpatients — aged 70 years or older — were interviewed using the Researching Efficient Approaches to Delirium Identification (READI) protocol.
The research team studied the implications of making two changes to the 3D-CAM: using an ultra-brief screening tool (the UB-2) to quickly rule out delirium, and introducing a skip pattern so that once a delirium feature was identified, other questions could be skipped to reduce time.
The combinations of these approaches defined the four protocols:
- the full 3D-CAM;
- the 3D-CAM with the skip pattern;
- the UB-2, followed by the full 3D-CAM in individuals who failed the screening test; and
- the UB-2, followed by the 3D-CAM with skip pattern in individuals who failed the screening test.
The team compared the four protocols on three measures:
- sensitivity – the ability of a test to correctly identify those with the disease (true positive rate);
- specificity – the ability of a test to correctly identify those without the disease (true negative rate); and
- the average time required to complete the protocol.
Results showed that the 4th protocol – the UB-2 followed by the 3D-CAM with skip pattern in those who failed the screening, was the most time-efficient, taking a total of one minute and 14 seconds with 93% sensitivity and 95% specificity. Because the new approach was nearly two minutes faster than administering the full 3D-CAM to everyone, the authors termed this approach the Ultra-brief CAM, or UB-CAM.
Given its time efficiency and high accuracy, the UB-CAM holds promise for increasing implementation of systematic screening and improving detection of delirium in hospitalized older adults. The team continues to analyze new data, assessing the speed and accuracy of different types of clinicians administering the UB-CAM protocol (e.g., physicians, nurses, and nursing assistants), providing an important evidence base for implementing systematic hospital‐wide delirium identification.
“Implementing delirium identification approaches such as the UB-CAM in acute care is especially critical now. Almost one-third of older adults that are testing positive for COVID-19 are also presenting with delirium symptoms, with even higher rates in the ICU and in individuals with pre-existing dementia.” Fick explained. “Failure to recognize and address acute delirium in these patients can result in long term cognitive decline and diminished quality of life. Systematically screening for delirium can prevent harm and reduce health care costs during this difficult and uncertain time.”
Douglas Leslie from the Penn State College of Medicine, Claire Motyl from the University of Rochester, Long Ngo, Wenxiao Zhou, Yoojin Jung, and Sharon K. Inouye from the Beth Israel Deaconess Medical Center and the Harvard Medical School, also contributed to this research.
Read more about the research here.
Access the Ultra-Brief Confusion Assessment Method (UB-CAM) here.