Examining Nurses' Trust and Acceptance of FAIR, an AI-powered Falls Risk Recommender

NANot yet recruitingINTERVENTIONAL
Enrollment

60

Participants

Timeline

Start Date

January 1, 2027

Primary Completion Date

December 31, 2027

Study Completion Date

June 30, 2029

Conditions
Falls Risk
Interventions
OTHER

Falls risk - Artificial Intelligence Recommender (FAIR)

"FAIR is an alert system built into the hospital's electronic medical record system. It is an adaptation of a machine learning model for fall risk calculation built in another hospital in Singapore. FAIR combines multiple patient-specific variables to identify if a patient is at increased risk of falling during their inpatient stay, marking them as a 'falls risk'.~Based on the 'flag' raised, the nurse will be instructed to prioritise her falls risk assessment of the patient (If deemed 'high risk') or to do so subsequently as a lower priority once other pressing patient care issues are resolved (if deemed 'low risk').~That way, it ensures the requirements of each patient receiving a falls risk assessment as scored through mWHeFRA are still met, with FAIR allowing nurses to better prioritise their focus and attention on the patient that most needs the assessment at point of admission,"

OTHER

modified Western Health Falls Risk Assessment Tool (mWHeFRA)

The mWHeFRA is the hospital's standard falls risk assessment tool. All nurses are expected to be proficient in its use to guide their risk assessment of patients

All Listed Sponsors
collaborator

Marquette University

OTHER

collaborator

Lee Kong Chian School of Medicine, Nanyang Technological University

UNKNOWN

lead

Tan Tock Seng Hospital

OTHER