Identification of methicillin-resistant Staphylococcus aureus within the Nation’s Veterans Affairs Medical Centers using natural language processing

Author:

Jones Makoto,DuVall Scott L,Spuhl Joshua,Samore Matthew H,Nielson Christopher,Rubin Michael

Publisher

Springer Science and Business Media LLC

Subject

Health Informatics,Health Policy,Computer Science Applications

Reference16 articles.

1. Klevens RM, Morrison MA, Nadle J, Petit S, Gershman K, Ray S, Harrison LH, Lynfield R, Dumyati G, Townes JM: Invasive methicillin-resistant Staphylococcus aureus infections in the United States. JAMA. 2007, 298: 1763-1771. 10.1001/jama.298.15.1763.

2. National and State Population Estimates. [ http://www.census.gov/popest/states/NST-ann-est.html ]

3. Jain R, Kralovic SM, Evans ME, Ambrose M, Simbartl LA, Obrosky DS, Render ML, Freyberg RW, Jernigan JA, Muder RR: Veterans Affairs initiative to prevent methicillin-resistant Staphylococcus aureus infections. N Engl J Med. 2011, 364: 1419-1430. 10.1056/NEJMoa1007474.

4. Methicillin-Resistant Staphylococcus aureus (MRSA) Initiative. [ http://vaww.mrsa.va.gov/docs/VHAdirective2007-002.pdf ]

5. Rubin MA, Mayer J, Greene T, Sauer BC, Hota B, Trick WE, Jernigan JA, Samore MH: An agent-based model for evaluating surveillance methods for catheter-related bloodstream infection. AMIA Annu Symp Proc. 2008, 631-635.

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