{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"omics_type":["Unknown"],"volume":["12(1)"],"submitter":["Wang L"],"funding":["T.T & W.F. Chao Foundation","John S. Dunn Research Foundation"],"pubmed_abstract":["Healthcare regulatory agencies have mandated a reduction in 30-day hospital readmission rates and have targeted COPD as a major contributor to 30-day readmissions. We aimed to develop and validate a simple tool deploying an artificial neural network (ANN) for early identification of COPD patients with high readmission risk. Using COPD patient data from eight hospitals within a large urban hospital system, four variables were identified, weighted and validated. These included the number of in-patient admissions in the previous 6 months, the number of medications administered on the first day, insurance status, and the Rothman Index on hospital day one. An ANN model was trained to provide a predictive algorithm and validated on an additional dataset from a separate time period. The model was"],"journal":["Scientific reports"],"pagination":["20633"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC9712389"],"repository":["biostudies-literature"],"pubmed_title":["An AI-driven clinical care pathway to reduce 30-day readmission for chronic obstructive pulmonary disease (COPD) patients."],"pmcid":["PMC9712389"],"pubmed_authors":["Li G","Wong SSY","Jackson RE","Xu P","Ezeana CF","Frost A","Wang L","Yin Z","Puppala M","Nezamabadi A","Ogunti R","He T","Wong STC","Yu X","Roberts AW"],"additional_accession":[]},"is_claimable":false,"name":"An AI-driven clinical care pathway to reduce 30-day readmission for chronic obstructive pulmonary disease (COPD) patients.","description":"Healthcare regulatory agencies have mandated a reduction in 30-day hospital readmission rates and have targeted COPD as a major contributor to 30-day readmissions. We aimed to develop and validate a simple tool deploying an artificial neural network (ANN) for early identification of COPD patients with high readmission risk. Using COPD patient data from eight hospitals within a large urban hospital system, four variables were identified, weighted and validated. These included the number of in-patient admissions in the previous 6 months, the number of medications administered on the first day, insurance status, and the Rothman Index on hospital day one. An ANN model was trained to provide a predictive algorithm and validated on an additional dataset from a separate time period. The model was","dates":{"release":"2022-01-01T00:00:00Z","publication":"2022 Nov","modification":"2025-04-19T03:33:03.03Z","creation":"2025-04-07T13:42:14.256Z"},"accession":"S-EPMC9712389","cross_references":{"pubmed":["36450795"],"doi":["10.1038/s41598-022-22434-3"]}}