Closing the Evidence Gap in Interstitial Lung Disease. The Promise of Real-World Data
Am J Respir Crit Care Med
.
2019 May 1;199(9):1061-1065.
doi: 10.1164/rccm.201807-1209PP.
Authors
Erica Farrand
1
,
Kevin J Anstrom
2
,
Gordon Bernard
3
,
Atul J Butte
4
,
Carlos Iribarren
5
,
Brett Ley
1
,
Fernando J Martinez
6
,
Harold R Collard
1
Affiliations
1
1 Department of Medicine and.
2
2 Department of Biostatistics and Bioinformatics, Duke University, Durham, North Carolina.
3
3 Department of Medicine, Vanderbilt University, Nashville, Tennessee.
4
4 Bakar Computational Health Sciences Institute, University of California San Francisco, San Francisco, California.
5
5 Division of Research, Kaiser Permanente Northern California, Oakland, California; and.
6
6 Department of Medicine, Cornell University, New York, New York.
PMID:
30452876
DOI:
10.1164/rccm.201807-1209PP
No abstract available
MeSH terms
Big Data
Biomedical Research
Clinical Trials as Topic
Evidence-Based Practice
Humans
Lung Diseases, Interstitial / therapy*
Observational Studies as Topic