Dataset Information

Predicting hospital readmission risk: A prospective observational study to compare primary care providers' assessments with the LACE readmission risk index.

ABSTRACT:

Purpose

This study aims to determine if the primary care provider (PCP) assessment of readmission risk is comparable to the validated LACE tool at predicting readmission to hospital.

Methods

A prospective observational study of recently discharged adult patients clustered by PCPs in the primary care setting. Physician readmission risk assessment was determined via a questionnaire after the PCP reviewed the hospital discharge summary. LACE scores were calculated using administrative data and the discharge summary. The sensitivity and specificity of the physician assessment and the LACE tool in predicting readmission risk, agreement between the 2 assessments and the area under receiver operating characteristic (AUROC) curves were calculated.

Results

217 patient readmission encounters were included in this study from September 2017 till June 2018. The rate of readmission within 30 days was 14.7%, and 217 discharge summaries were used for analysis. The weighted kappa coefficient was 0.41 (95% CI: 0.30-0.51) demonstrating a moderate level of agreement. Sensitivity of physician assessment was 0.31 (95% CI: 0.22-0.40) and specificity was 0.80 (95% CI: 0.77-0.83). The sensitivity of the LACE assessment was 0.42 (95% CI: 0.25-0.59) and specificity was 0.79 (95% CI: 0.73-0.85). The AUROC for the LACE readmission risk was 0.65 (95% C.I. 0.55-0.76) demonstrating modest predictive power and was 0.57 (95% C.I. 0.46-0.68) for physician assessment, demonstrating low predictive power.

Conclusion

The LACE index shows moderate discriminatory power in identifying high-risk patients for readmission when compared to the PCP's assessment. If this score can be provided to the PCP, it may help identify patients who requires more intensive follow-up after discharge.

SUBMITTER: Walji S

PROVIDER: S-EPMC8673665 | biostudies-literature |

REPOSITORIES: biostudies-literature

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