Context Predicting hospital readmission risk is of great interest to identify which patients
would benefit most from care transition interventions, as well as to risk-adjust readmission …

Aims Readmission rates for patients with heart failure have consistently remained high over
the past two decades. As more electronic data, computing power, and newer statistical …

Importance Several attempts have been made at developing models to predict 30-day
readmissions in patients with heart failure, but none have sufficient discriminatory capacity …

Background Unplanned readmission of a hospitalized patient is an indicator of patients'
exposure to risk and an avoidable waste of medical resources. In addition to hospital …

Aims This study aims to investigate hospital readmissions and timing, as well as risk factors
in a real world heart failure (HF) population. Methods and results All patients discharged …

Objective To evaluate the prevalence of seven social factors using physician notes as
compared to claims and structured electronic health records (EHR s) data and the resulting …

Objective Hospital readmission costs a lot of money every year. Many hospital readmissions
are avoidable, and excessive hospital readmissions could also be harmful to the patients …

BACKGROUND: The accuracy of current models to predict the risk of unplanned
readmission or death after a heart failure (HF) hospitalization is uncertain. METHODS: We …

This research studies the risk prediction of hospital readmissions using metaheuristic and
data mining approaches. This is a critical issue in the US healthcare system because a large …

Context There is increasing interest in reporting risk-standardized outcomes for Medicare
beneficiaries hospitalized with acute ischemic stroke, but whether it is necessary to include …