Real-time prediction of mortality, readmission, and length of stay using electronic health record data

Journal of the American Medical Informatics Association

Volumn 23, Issue 3, 2016, Pages 553-561

  Cai, Xiongcai ^a   Perez Concha, Oscar ^b   Coiera, Enrico ^b   Martin Sanchez, Fernando ^c   Day, Richard ^a   Roffe, David ^d   Gallego, Blanca ^b  

^a UNIVERSITY OF NEW SOUTH WALES   (Australia)

^b MACQUARIE UNIVERSITY   (Australia)

^c UNIVERSITY OF MELBOURNE   (Australia)

^d ST VINCENT S HOSPITAL   (Australia)

Author keywords

Length of stay; Mortality; Patient outcome; Prediction; Readmission

Indexed keywords

ACCURACY; ADULT; AREA UNDER THE CURVE; ARTICLE; BAYES THEOREM; DEATH; ELECTRONIC HEALTH RECORD; EMERGENCY WARD; FEMALE; FORECASTING; HOSPITAL ADMISSION; HOSPITAL DISCHARGE; HOSPITAL PATIENT; HOSPITAL READMISSION; HOSPITALIZATION; HUMAN; LENGTH OF STAY; MAJOR CLINICAL STUDY; MALE; MIDDLE AGED; MORTALITY; OUTCOME ASSESSMENT; POINT OF CARE SYSTEM; PREDICTIVE VALUE; PROBABILITY; RECEIVER OPERATING CHARACTERISTIC; HOSPITAL MORTALITY; PROGNOSIS; STATISTICAL MODEL;

BAYES THEOREM; ELECTRONIC HEALTH RECORDS; HOSPITAL MORTALITY; HOSPITALIZATION; HUMANS; LENGTH OF STAY; MODELS, STATISTICAL; PATIENT READMISSION; PROBABILITY; PROGNOSIS; ROC CURVE;

EID: 84979055388     PISSN: 10675027     EISSN: 1527974X     Source Type: Journal    
DOI: 10.1093/jamia/ocv110     Document Type: Article

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