Identifying patients at risk of nursing home admission: The Leeds Elderly Assessment Dependency Screening tool (LEADS).
BACKGROUND
Discharge from hospital to a nursing home represents a major event in the life of an older person and should only follow a comprehensive functional and medical assessment. A previous study identified 3 dependency scales able to discriminate across outcomes for older people admitted to an acute setting. We wished to determine if a single dependency scale derived from the 3 scales could be created. In addition could this new scale with other predictors be used as a comprehensive tool to identify patients at risk of nursing home admission.


METHODS
Items from the 3 scales were combined and analysed using Rasch Analysis. Sensitivity and specificity analysis and ROC curves were applied to identify the most appropriate cut score. Binary logistic regression using this cut-off, and other predictive variables, were used to create a predictive algorithm score. Sensitivity, specificity and likelihood ratio scores of the algorithm scores were used to identify the best predictive score for risk of nursing home placement.


RESULTS
A 17-item (LEADS) scale was derived, which together with four other indicators, had a sensitivity of 88% for patients at risk of nursing home placement, and a specificity of 85% for not needing a nursing home placement, within 2 weeks of admission.


CONCLUSIONS
A combined short 17-item scale of dependency plus other predictive variables can assess the risk of nursing home placement for older people in an acute care setting within 2 weeks of admission. This gives an opportunity for either early discharge planning, or therapeutic intervention to offset the risk of placement.
School of Allied Health Professions, Leeds Metropolitan University, Leeds, UK. a.slade@leedsmet.ac.uk
Anita
A
Slade
Jon
J
Fear
Alan
A
Tennant
D000359:Aftercare; D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D005260:Female; D015577:Geriatric Assessment / Q000379:methods*; D006302:Health Services Research; D006801:Humans; D016015:Logistic Models; D008297:Male; D009735:Nursing Homes / Q000706:statistics & numerical data*; D010351:Patient Discharge; D018570:Risk Assessment / Q000379:methods*; D012307:Risk Factors; D012720:Severity of Illness Index; D011795:Surveys and Questionnaires; D006113:United Kingdom