Predicting readmissions: poor performance of the LACE index in an older UK population

interventions to prevent hospital readmission depend on the identification of patients at risk. The LACE index predicts readmission (and death) and is in clinical use internationally. The LACE index was investigated in an older UK population. randomly selected alive-discharge episodes were reviewed....

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Bibliographic Details
Published in:Age and ageing 2012-11, Vol.41 (6), p.784-789
Main Authors: Cotter, Paul E, Bhalla, Vikas K, Wallis, Stephen J, Biram, Richard W S
Format: Article
Language:English
Subjects:
Admission and discharge
Aged
Aged patients
Aged, 80 and over
Aging
Care and treatment
Company business management
Death
Elderly patients
Forecasting
Geriatric Assessment - methods
Geriatric nursing
Hospital admission and discharge
Hospital Mortality
Hospitals
Humans
Identification
Logistic Models
Management
Medical examination
Models, Statistical
Older people
Patient admissions
Patient Discharge - economics
Patient Discharge - statistics & numerical data
Patient Discharge - trends
Patient Readmission - economics
Patient Readmission - statistics & numerical data
Patient Readmission - trends
Predictions
Readmission
Reproducibility of Results
Risk Factors
State Medicine - economics
State Medicine - statistics & numerical data
United Kingdom
Validation
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Summary:interventions to prevent hospital readmission depend on the identification of patients at risk. The LACE index predicts readmission (and death) and is in clinical use internationally. The LACE index was investigated in an older UK population. randomly selected alive-discharge episodes were reviewed. A LACE score was calculated for each patient and assessed using receiver operator characteristic (ROC) curves. A logistic regression model was constructed, compared with the LACE and validated in a separate population. a total of 507 patients were included with a mean (SD) age of 85 (6.5) years; 17.8% were readmitted and 4.5% died within 30 days. The median LACE score of those readmitted compared with those who were not was 12.5 versus 12 (P = 0.13). The Lace index was only a fair predictor of both 30-day readmission and death with c-statistics of 0.55 and 0.70, respectively. Only the emergency department visit was an independent predictor of readmission, with a c-statistic of 0.61 for readmission. In a validation cohort of 507 cases, the c-statistic of the regression model was 0.57. the LACE index is a poor tool for predicting 30-day readmission in older UK inpatients. The absence of a simple predictive model may limit the benefit of readmission avoidance strategies.
ISSN:0002-0729
1468-2834
DOI:10.1093/ageing/afs073