Accuracy of using automated methods for detecting adverse events from electronic health record data: A research protocol

Implementation Science

Volumn 10, Issue 1, 2015, Pages

  Rochefort, Christian M ^a,b   Buckeridge, David L ^a,b   Forster, Alan J ^c,d  

^a MCGILL UNIVERSITY   (Canada)

^b MCGILL UNIVERSITY   (Canada)

^c OTTAWA HOSPITAL RESEARCH INSTITUTE   (Canada)

^d UNIVERSITY OF OTTAWA   (Canada)

Author keywords

Acute care hospital; Adverse events; Automated detection; Data warehouse; Electronic health record; Natural language processing; Patient safety

Indexed keywords

ALGORITHM; CATHETER-RELATED INFECTIONS; CROSS INFECTION; DATA MINING; ELECTRONIC HEALTH RECORD; FALLING; HOSPITAL PATIENT; HUMAN; PNEUMONIA; PROCEDURES; SAMPLE SIZE; STANDARDS; STATISTICS AND NUMERICAL DATA;

ACCIDENTAL FALLS; ALGORITHMS; CATHETER-RELATED INFECTIONS; CROSS INFECTION; DATA MINING; ELECTRONIC HEALTH RECORDS; HUMANS; INPATIENTS; PNEUMONIA; SAMPLE SIZE;

EID: 84988735641     PISSN: None     EISSN: 17485908     Source Type: Journal    
DOI: 10.1186/s13012-014-0197-6     Document Type: Article

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