Clinicians can independently predict 30-day hospital readmissions as well as the LACE index

Autor:	Erin P Dowling, William D. Miller, Kimngan Pham Nguyen, Sitaram Vangala
Jazyk:	angličtina
Rok vydání:	2018
Předmět:	Male medicine.medical_specialty Index (economics) Comorbidity 030204 cardiovascular system & hematology Prediction tools Logistic regression Patient Readmission Health administration 03 medical and health sciences 0302 clinical medicine Medical Staff Hospital Humans Medicine 030212 general & internal medicine Quality improvement Hospital readmissions Aged Receiver operating characteristic business.industry Health Policy lcsh:Public aspects of medicine Patient Acuity lcsh:RA1-1270 Length of Stay Middle Aged medicine.disease Predictive value Hospitals Patient Discharge LACE index Emergency medicine Female Day hospital Clinical Competence Emergency Service Hospital Epidemiologic Methods business Discharge planning Research Article
Zdroj:	BMC Health Services Research, Vol 18, Iss 1, Pp 1-6 (2018) BMC Health Services Research
ISSN:	1472-6963
DOI:	10.1186/s12913-018-2833-3
Popis:	Background Significant effort has been directed at developing prediction tools to identify patients at high risk of unplanned hospital readmission, but it is unclear what these tools add to clinicians’ judgment. In our study, we assess clinicians’ abilities to independently predict 30-day hospital readmissions, and we compare their abilities with a common prediction tool, the LACE index. Methods Over a period of 50 days, we asked attendings, residents, and nurses to predict the likelihood of 30-day hospital readmission on a scale of 0–100% for 359 patients discharged from a General Medicine Service. For readmitted versus non-readmitted patients, we compared the mean and standard deviation of the clinician predictions and the LACE index. We compared receiver operating characteristic (ROC) curves for clinician predictions and for the LACE index. Results For readmitted versus non-readmitted patients, attendings predicted a risk of 48.1% versus 31.1% (p
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c1a3da4a3727efd8e6008aab2935f309 http://link.springer.com/article/10.1186/s12913-018-2833-3 Zobrazit plný text záznamu Plný text ve formátu PDF Plný text ve formátu HTML
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