{"data":{"id":"10.17026/dans-xq9-ny2h","type":"dois","attributes":{"doi":"10.17026/dans-xq9-ny2h","prefix":"10.17026","suffix":"dans-xq9-ny2h","identifiers":[{"identifier":"easy-dataset:109793","identifierType":"DANS-KNAW"},{"identifier":"588702 (MetisID)","identifierType":":unav"}],"alternateIdentifiers":[{"alternateIdentifierType":"DANS-KNAW","alternateIdentifier":"easy-dataset:109793"},{"alternateIdentifierType":":unav","alternateIdentifier":"588702 (MetisID)"}],"creators":[{"name":"J.M. Bos","nameType":"Personal","affiliation":["Radboud University"],"nameIdentifiers":[]},{"name":"G.A. Kalkman","nameType":"Personal","affiliation":[],"nameIdentifiers":[]},{"name":"H. Groenewoud","nameType":"Personal","affiliation":["Radboud University"],"nameIdentifiers":[]},{"name":"P.M. van den Bemt","nameType":"Personal","affiliation":[],"nameIdentifiers":[]},{"name":"P.A.G.M. de Smet","nameType":"Personal","givenName":"de","familyName":".G.M. de Smet","affiliation":["Radboud University"],"nameIdentifiers":[]},{"name":"J.E. Nagtegaal","nameType":"Personal","affiliation":[],"nameIdentifiers":[]},{"name":"A. Wieringa","nameType":"Personal","affiliation":[],"nameIdentifiers":[]},{"name":"G.J. van der Wilt","nameType":"Personal","affiliation":["Radboud University"],"nameIdentifiers":[]},{"name":"C. Kramers","nameType":"Personal","affiliation":["Radboud University"],"nameIdentifiers":[]}],"titles":[{"title":"Dataset belonging to: Prediction of clinically relevant adverse drug events in surgical patients"}],"publisher":"DANS Data Station Life Sciences","container":{},"publicationYear":2018,"subjects":[{"subject":"Medicine, Health and Life Sciences"},{"subject":"Social Sciences"},{"subject":"patient safety"},{"subject":"prediction model"},{"subject":"surgical ward"},{"subject":"adverse drug events"}],"contributors":[{"name":"C. Kramers","nameType":"Personal","contributorType":"ContactPerson","affiliation":[],"nameIdentifiers":[]}],"dates":[{"date":"2018-07-26","dateType":"Issued"},{"date":"2018-01-01","dateType":"Created"},{"date":"2018-07-31","dateType":"Submitted"},{"date":"2018-08-13","dateType":"Available"},{"date":"2026-08-24","dateType":"Updated"}],"language":null,"types":{"ris":"DATA","bibtex":"misc","citeproc":"dataset","schemaOrg":"Dataset","resourceTypeGeneral":"Dataset"},"relatedIdentifiers":[],"relatedItems":[],"sizes":["23078","5831","190075","200182","1940480","788","23046","1940346","1945669"],"formats":["application/zip","text/xml","application/pdf","application/pdf","text/tab-separated-values","text/plain","application/zip","text/tab-separated-values","text/tab-separated-values"],"version":"2.2","rightsList":[{"rightsUri":"info:eu-repo/semantics/closedAccess"},{"lang":"en","rights":"DANS Licence","rightsUri":"https://doi.org/10.17026/fp39-0x58"}],"descriptions":[{"description":"\u0026lt;p\u0026gt;Contains the data used for the study titled: Prediction of clinically relevant adverse drug events in surgical patients.\u0026lt;/p\u0026gt;\u0026lt;p\u0026gt;This dataset consists of data extracted from the P-REVIEW dataset. Data were collected for each admission, including patient characteristics, drug history, and biochemical, haematological, and microbiological markers. Using this dataset we aimed to develop a prediction model that helps to identify patients on the day of hospital admission who are at increased risk of developing a clinically relevant, preventable adverse drug event during their stay on a surgical ward.\u0026lt;/p\u0026gt;\u0026lt;p\u0026gt;The language of the dataset and codebook is Dutch.\u0026lt;/p\u0026gt;","descriptionType":"Abstract"},{"description":"\u0026lt;p\u0026gt;.por and .dta versions added by DANS\u0026lt;/p\u0026gt;","descriptionType":"Abstract"},{"description":"The metadata field 'Spatial Coverage Country' is being replaced by the new field 'Spatial Coverage 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