LEADS: A Tool to Identify Patients at Risk of Nursing Home Admission
Author Information
Author(s): Anita Slade, Jon Fear, Alan Tennant
Primary Institution: Leeds Metropolitan University
Hypothesis
Can a single dependency scale be created from three existing scales to identify patients at risk of nursing home admission?
Conclusion
The LEADS scale can effectively assess the risk of nursing home placement for older patients within two weeks of hospital admission.
Supporting Evidence
- The LEADS scale showed a sensitivity of 88% and specificity of 85% for predicting nursing home placement.
- Using Rasch analysis, a 17-item scale was developed from three existing scales.
- The algorithm derived from the LEADS tool explained approximately 75% of the variance in predicting nursing home need.
Takeaway
Researchers created a simple 17-question tool to help doctors figure out if older patients might need to go to a nursing home after they leave the hospital.
Methodology
The study combined items from three dependency scales and used Rasch analysis, binary logistic regression, and ROC curves to develop and validate the LEADS tool.
Potential Biases
Potential bias due to the reliance on a single assessment and the low number of nursing home admissions.
Limitations
The study's predictive value may be overestimated due to the low number of patients entering nursing homes and the assessment being conducted only once within two weeks of admission.
Participant Demographics
Mean age of participants was 83.8 years, with 70.2% being female.
Statistical Information
P-Value
p<0.000
Confidence Interval
0.738–0.881
Statistical Significance
p<0.001
Digital Object Identifier (DOI)
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