Identifying delirium can be done effectively, quickly using app-directed protocol, study finds

Identifying delirium in vulnerable hospitalized adults using an app-directed protocol proved to be easy, quick, and accurate, according to an NIA-supported study. The findings, which were published recently in the Annals of Internal Medicine, suggest that clinicians — hospitalists, nurses, and certified nursing assistants (CNAs) — can accurately identify delirium in older, hospitalized adults in fewer than two minutes as part of their routine daily workflow.

Delirium — a state of acute confusion — affects millions of hospitalized older adults each year. In the short term, delirium is associated with longer hospital stays, increased nursing home use after hospitalization, and higher mortality. In the long term, delirium is linked with poor functional recovery, cognitive decline, and incident dementia.

Research shows that systematic screening improves delirium identification among hospitalized older adults. While other delirium-screening tools have been developed, few studies have tested their use by clinicians of various levels of training in real-world practices compared with a standard delirium assessment.

In this new study, researchers tested the ability of a tablet computer-based app to identify delirium compared with a standard delirium assessment. The app combines two previously tested and validated assessment protocols for delirium: an ultra-brief 2-item screen (UB-2) and a 3-minute assessment (3D-CAM). Both protocols are based on the Confusion Assessment Method (CAM), the most widely used bedside tool to assess delirium.

The study enrolled 527 general medicine inpatients who were 70 years or older. Of those participants, 35% had preexisting dementia, a condition known to increase the risk of being undiagnosed or misdiagnosed for delirium. Nearly 400 clinicians — hospitalists, nurses, and CNAs — took part in the study, completing delirium screens using the app within the context of their daily work on the hospital units. Using the app, CNAs screened patients for delirium with just the UB-2, and hospitalists and nurses screened patients with both the UB-2 and 3D-CAM.

Overall, 2,693 clinician delirium screens were completed using the app, with roughly a 97% completion rate, and an average completion time of fewer than two minutes, over the course of the two-day study period. Using the UB-2 screen, all three groups of clinicians correctly identified delirium when it was present (sensitivity) 82%-88% of the time and correctly avoided identifying delirium when it was absent (specificity) 64%-70% of the time. Using the UB-2 and 3D-CAM together, sensitivity among nurses and hospitalists was 63%-65% while specificity was 91%-93%.

The researchers noted that the app-directed protocol helped address two major barriers to delirium screening — lack of knowledge of how to assess delirium and lack of time. With only 12% to 35% of delirium cases currently detected in clinical practice, the app-directed protocol could substantially improve delirium identification among vulnerable hospitalized adults. The researchers suggested that to improve patient outcomes, tools for delirium identification like the app should be coupled with recommendations for delirium prevention or management. Additional research is needed to evaluate the cost of these screening protocols and to develop ways to help clinicians and hospital systems implement better delirium identification, management, and prevention strategies.

This research was supported by NIA grants R01AG030618, R24AG054259, and K24AG035075.

Reference: Marcantonio ER, et al. Comparative implementation of a brief app-directed protocol for delirium identification by hospitalists, nurses, and nursing assistants. Annals of Internal Medicine. 2021; doi:10.7326/M21-1687.