Falls in hospitalized patients: can nursing information systems data predict falls?
Falls among inpatients are the most frequently reported critical incidents in hospitals and can have tragic consequences that affect morbidity and mortality. The present study aimed to determine whether certain nursing units of care identified on patient care plans can be used to predict falls among hospitalized inpatients. A retrospective analysis of 7167 inpatient admissions in the 2002 calendar year was conducted. Faller status was ascertained from the hospital's accident and incident monitoring system, and nursing units of care activated in the hospital's nursing information system were identified. Twelve nursing units of care predicted falls. Logistic regression analyses showed that nursing units of care related to patient safety, confusion, incontinence, medication, mobility, and sleep were significant risk factors for falls among inpatients. The number of nursing units of care activated also predicted falls. Data collected from nursing information systems can be used to identify patients at high risk of falls.
Giles
Lynne C
LC
Department of Rehabilitation and Aged Care and Flinders Centre for Clinical Change and Health Care Research, Flinders University, Adelaide, Australia.
Whitehead
Craig H
CH
Jeffers
Lesley
L
McErlean
Beth
B
Thompson
Dani
D
Crotty
Maria
M
D000058:Accidental Falls / Q000517:prevention & control / Q000706:statistics & numerical data*; D000368:Aged; D020000:Decision Support Systems, Clinical / Q000458:organization & administration; D005260:Female; D015577:Geriatric Assessment; D006751:Hospital Information Systems / Q000458:organization & administration*; D006801:Humans; D016015:Logistic Models; D008297:Male; D008403:Mass Screening / Q000458:organization & administration; D016347:Medical Records Systems, Computerized / Q000458:organization & administration*; D020380:Needs Assessment; D009730:Nursing Assessment; D015403:Nursing Evaluation Research; D048108:Nursing Informatics / Q000458:organization & administration*; D010347:Patient Care Planning; D011237:Predictive Value of Tests; D012189:Retrospective Studies; D018570:Risk Assessment / Q000458:organization & administration*; D012307:Risk Factors; D012308:Risk Management; D013021:South Australia