Natural Language Processing to Assess Documentation of Features of Critical Illness in Discharge Documents of Acute Respiratory Distress Syndrome Survivors.

Journal: Annals of the American Thoracic Society

Published Date: Sep 1, 2016

Abstract

RATIONALE: Transitions to outpatient care are crucial after critical illness, but the documentation practices in discharge documents after critical illness are unknown.

Authors

Gary E Weissman

1 Pulmonary, Allergy, and Critical Care Division, Hospital of the University of Pennsylvania.
Michael O Harhay

2 Leonard Davis Institute of Health Economics, and.
Ricardo M Lugo

4 Division of Cardiovascular Medicine, Vanderbilt University School of Medicine, Nashville, Tennessee.
Barry D Fuchs

1 Pulmonary, Allergy, and Critical Care Division, Hospital of the University of Pennsylvania.
Scott D Halpern

1 Pulmonary, Allergy, and Critical Care Division, Hospital of the University of Pennsylvania.
Mark E Mikkelsen

1 Pulmonary, Allergy, and Critical Care Division, Hospital of the University of Pennsylvania.

Keywords

Aged Critical Illness Documentation Female Humans Intensive Care Units Length of Stay Male Medical Informatics Middle Aged Multivariate Analysis Natural Language Processing Patient Discharge Regression Analysis Respiration, Artificial Respiratory Distress Syndrome Survivors Transitional Care United States

External Resources

View on PubMed Access via DOI PubMed (27333269)

Natural Language Processing to Assess Documentation of Features of Critical Illness in Discharge Documents of Acute Respiratory Distress Syndrome Survivors.

Abstract

Authors

Keywords

External Resources

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