Decision support through risk cost estimation in 30-day hospital unplanned readmission.
other · Level V
Where this comes from
- Record sourced from PubMed, PMID 35839222.
- Also identified by DOI 10.1371/journal.pone.0271331 and PMC identifier 9286269.
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Abstract
Unplanned hospital readmissions mean a significant burden for health systems. Accurately estimating the patient's readmission risk could help to optimise the discharge decision-making process by smartly ordering patients based on a severity score, thus helping to improve the usage of clinical resources. A great number of heterogeneous factors can influence the readmission risk, which makes it highly difficult to be estimated by a human agent. However, this score could be achieved with the help of AI models, acting as aiding tools for decision support systems. In this paper, we propose a machine learning classification and risk stratification approach to assess the readmission problem and provide a decision support system based on estimated patient risk scores.
Medical subject headings
- Patient Discharge
- Patient Readmission