TY - JOUR
T1 - Evaluating the predictive strength of the LACE index in identifying patients at high risk of hospital readmission following an inpatient episode:
T2 - retrospective cohort study
AU - Damery, Sarah
AU - Combes, Gill
PY - 2017/7/1
Y1 - 2017/7/1
N2 - Objective: To assess how well the LACE index and its constituent elements predicts 30-day hospital readmission and to determine whether other combinations of clinical or sociodemographic variables may enhance prognostic capability.Design: Retrospective cohort study with split sample design for model validation.Setting: One large hospital Trust in the West Midlands.Participants: All alive-discharge adult inpatient episodes between 1st January 2013 and 31st December 2014. Data sources: Anonymised data for each inpatient episode were obtained from the hospital information system. These included age at index admission, gender, ethnicity, admission/discharge date, length of stay, treatment specialty, admission type and source, discharge destination, comorbidities, number of accident and emergency (A&E) visits in the six months before the index admission, and whether a patient was readmitted within 30 days of index discharge. Outcome measures: Clinical and patient characteristics of readmission vs. non-readmission episodes, proportion of readmission episodes at each LACE score, regression modelling of variables associated with readmission to assess the effectiveness of LACE and other variable combinations to predict 30-day readmission.Results: The training cohort included data on 91,922 patient episodes. Increasing LACE score and each of its individual components were independent predictors of readmission (AUC 0.773; 95% CI: 0.768 to 0.779 for LACE; AUC 0.806; 95% CI: 0.801 to 0.812 for the four LACE components). A LACE score of 11 was most effective at distinguishing between higher and lower risk patients. However, only 25% of readmission episodes occurred in the higher scoring group. A model combining A&E visits and hospital episodes per patient in the previous year was more effective at predicting readmission (AUC 0.815; 95% CI: 0.810 to 0.819). Conclusions: Although LACE shows good discriminatory power in statistical terms, it may have little added value over and above clinical judgement in predicting a patient’s risk of hospital readmission.
AB - Objective: To assess how well the LACE index and its constituent elements predicts 30-day hospital readmission and to determine whether other combinations of clinical or sociodemographic variables may enhance prognostic capability.Design: Retrospective cohort study with split sample design for model validation.Setting: One large hospital Trust in the West Midlands.Participants: All alive-discharge adult inpatient episodes between 1st January 2013 and 31st December 2014. Data sources: Anonymised data for each inpatient episode were obtained from the hospital information system. These included age at index admission, gender, ethnicity, admission/discharge date, length of stay, treatment specialty, admission type and source, discharge destination, comorbidities, number of accident and emergency (A&E) visits in the six months before the index admission, and whether a patient was readmitted within 30 days of index discharge. Outcome measures: Clinical and patient characteristics of readmission vs. non-readmission episodes, proportion of readmission episodes at each LACE score, regression modelling of variables associated with readmission to assess the effectiveness of LACE and other variable combinations to predict 30-day readmission.Results: The training cohort included data on 91,922 patient episodes. Increasing LACE score and each of its individual components were independent predictors of readmission (AUC 0.773; 95% CI: 0.768 to 0.779 for LACE; AUC 0.806; 95% CI: 0.801 to 0.812 for the four LACE components). A LACE score of 11 was most effective at distinguishing between higher and lower risk patients. However, only 25% of readmission episodes occurred in the higher scoring group. A model combining A&E visits and hospital episodes per patient in the previous year was more effective at predicting readmission (AUC 0.815; 95% CI: 0.810 to 0.819). Conclusions: Although LACE shows good discriminatory power in statistical terms, it may have little added value over and above clinical judgement in predicting a patient’s risk of hospital readmission.
KW - LACE
KW - readmissions
KW - case finding
KW - risk stratification
KW - hospital
U2 - 10.1136/bmjopen-2017-016921
DO - 10.1136/bmjopen-2017-016921
M3 - Article
C2 - 28710226
SN - 2044-6055
VL - 7
JO - BMJ open
JF - BMJ open
IS - 7
M1 - e016921
ER -