Machine Learning Models to Predict Readmission Risk of Patients with Schizophrenia in a Spanish Region.
Currently, high hospital readmission rates have become a problem for mental health services, because it is directly associated with the quality of patient care. The development of predictive models with machine learning algorithms allows the assessment of readmission risk in hospitals. The main obje...
| Publicado en: | International Journal of Mental Health & Addiction Vol. 22; no. 4; pp. 2508 - 2528 |
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| Autores principales: | , , , , , |
| Formato: | Artículo |
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Springer Nature
Aug2024
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| Materias: | |
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=179413551&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 179413551 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 15571874 46AW jtl: International Journal of Mental Health & Addiction issn: 15571874 maglogo: N pubinfo: dt: Aug2024 vid: 22 iid: 4 pid: 237 pub: Springer Nature artinfo: ui: 179413551 10.1007/s11469-022-01001-x ppf: 2508 ppct: 20 formats: fmt: – @attributes: type: T – @attributes: type: P size: 1.2MB tig: atl: Machine Learning Models to Predict Readmission Risk of Patients with Schizophrenia in a Spanish Region. aug: au: Góngora Alonso, Susel Herrera Montano, Isabel Ayala, Juan Luis Martín Rodrigues, Joel J. P. C. Franco-Martín, Manuel de la Torre Díez, Isabel affil: https://ror.org/01fvbaw18 Department of Signal Theory and Communications, and Telematics Engineering, University of Valladolid, Paseo de Belén, 15, 47011, Valladolid, Spain https://ror.org/048tesw25 Faculty of Health Sciences, European University of the Atlantic, Isabel Torres, 21, 39011, Santander, Spain Department of Education, International Iberoamerican University, 24560, Campeche, Mexico https://ror.org/05gbn2817 College of Computer Science and Technology, China University of Petroleum (East China), 266555, Qingdao, China https://ror.org/02ht4fk33 Instituto de Telecomunicações, Covilhã, Portugal Psychiatry and Mental Health Department, Zamora Hospital (Sacyl), Hernan Cortés, 45, 49021, Zamora, Spain su: Mental health services Machine learning Patient readmissions People with schizophrenia Public hospitals sug: subj: Mental health services Residential Mental Health and Substance Abuse Facilities Psychiatric and Substance Abuse Hospitals Offices of Mental Health Practitioners (except Physicians) General Medical and Surgical Hospitals Machine learning Patient readmissions People with schizophrenia Public hospitals keyword: Algorithms Readmission Risk factors Schizophrenia Algorithms Readmission Risk factors Schizophrenia ab: Currently, high hospital readmission rates have become a problem for mental health services, because it is directly associated with the quality of patient care. The development of predictive models with machine learning algorithms allows the assessment of readmission risk in hospitals. The main objective of this paper is to predict the readmission risk of patients with schizophrenia in a region of Spain, using machine learning algorithms. In this study, we used a dataset with 6089 electronic admission records corresponding to 3065 patients with schizophrenia disorders. Data were collected in the period 2005–2015 from acute units of 11 public hospitals in a Spain region. The Random Forest classifier obtained the best results in predicting the readmission risk, in the metrics accuracy = 0.817, recall = 0.887, F1-score = 0.877, and AUC = 0.879. This paper shows the algorithm with highest accuracy value and determines the factors associated with readmission risk of patients with schizophrenia in this population. It also shows that the development of predictive models with a machine learning approach can help improve patient care quality and develop preventive treatments. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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