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.
Slade
Anita
A
School of Allied Health Professions, Leeds Metropolitan University, Leeds, UK. a.slade@leedsmet.ac.uk
Fear
Jon
J
Tennant
Alan
A
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