Literature DB >> 9510106

Respiratory isolation of tuberculosis patients using clinical guidelines and an automated clinical decision support system.

C A Knirsch1, N L Jain, A Pablos-Mendez, C Friedman, G Hripcsak.   

Abstract

OBJECTIVE: To evaluate a clinical guideline and an automated computer protocol for detection and respiratory isolation of tuberculosis (TB) patients.
DESIGN: An automated computer protocol was tested on a retrospective cohort of adult culture-positive TB patients admitted from 1992 to 1993 to Columbia-Presbyterian Medical Center and evaluated prospectively from July 1995 until July 1996.
SETTING: A large teaching hospital in New York City. PATIENTS: 171 adult patients admitted from 1992 to 1993 and 43 patients admitted between July 1995 and July 1996.
INTERVENTIONS: The 1990 Centers for Disease Control and Prevention guidelines for preventing transmission of TB were adapted to formulate clinical guidelines to ensure early isolation of TB patients at Columbia-Presbyterian Medical Center.
RESULTS: Implementation of a clinical respiratory isolation protocol resulted in a significant improvement in TB patient isolation rates, from 45 (51%) of 88 in 1992 to 62 (75%) of 83 in 1993 (P<.001). In testing automated protocols, the theoretical improvement would have identified an additional 27 patients not isolated by clinicians, making the overall isolation rate 134 (78%) of 171. For the prospective evaluation, 30 (70%) of 43 TB patients were isolated by clinicians adhering to the clinical protocol. Four additional patients were identified by the automated TB protocol, making the combined isolation rate 34 (79%) of 43.
CONCLUSIONS: A clinical policy to isolate TB patients and suspected human immunodeficiency virus-infected patients with cough, fever, or radiographic abnormalities improved isolation of culture-documented TB patients from 1992 to 1993. Automated computer protocols were successful in identifying additional potentially infectious patients that clinicians failed to place on respiratory isolation. Clinical and automated protocols combined resulted in better isolation rates than a clinical protocol alone.

Entities:  

Mesh:

Year:  1998        PMID: 9510106     DOI: 10.1086/647773

Source DB:  PubMed          Journal:  Infect Control Hosp Epidemiol        ISSN: 0899-823X            Impact factor:   3.254


  23 in total

1.  A technique for semantic classification of unknown words using UMLS resources.

Authors:  D A Campbell; S B Johnson
Journal:  Proc AMIA Symp       Date:  1999

2.  A reliability study for evaluating information extraction from radiology reports.

Authors:  G Hripcsak; G J Kuperman; C Friedman; D F Heitjan
Journal:  J Am Med Inform Assoc       Date:  1999 Mar-Apr       Impact factor: 4.497

3.  A method for vocabulary development and visualization based on medical language processing and XML.

Authors:  H Liu; C Friedman
Journal:  Proc AMIA Symp       Date:  2000

Review 4.  Detecting adverse events using information technology.

Authors:  David W Bates; R Scott Evans; Harvey Murff; Peter D Stetson; Lisa Pizziferri; George Hripcsak
Journal:  J Am Med Inform Assoc       Date:  2003 Mar-Apr       Impact factor: 4.497

5.  Automated extraction and normalization of findings from cancer-related free-text radiology reports.

Authors:  Burke W Mamlin; Daniel T Heinze; Clement J McDonald
Journal:  AMIA Annu Symp Proc       Date:  2003

6.  Automated encoding of clinical documents based on natural language processing.

Authors:  Carol Friedman; Lyudmila Shagina; Yves Lussier; George Hripcsak
Journal:  J Am Med Inform Assoc       Date:  2004-06-07       Impact factor: 4.497

Review 7.  Natural Language Processing Technologies in Radiology Research and Clinical Applications.

Authors:  Tianrun Cai; Andreas A Giannopoulos; Sheng Yu; Tatiana Kelil; Beth Ripley; Kanako K Kumamaru; Frank J Rybicki; Dimitrios Mitsouras
Journal:  Radiographics       Date:  2016 Jan-Feb       Impact factor: 5.333

8.  Automated detection of adverse events using natural language processing of discharge summaries.

Authors:  Genevieve B Melton; George Hripcsak
Journal:  J Am Med Inform Assoc       Date:  2005-03-31       Impact factor: 4.497

9.  Automation of a problem list using natural language processing.

Authors:  Stephane Meystre; Peter J Haug
Journal:  BMC Med Inform Decis Mak       Date:  2005-08-31       Impact factor: 2.796

10.  Bio-Ontology and text: bridging the modeling gap.

Authors:  Carol Friedman; Tara Borlawsky; Lyudmila Shagina; H Rosie Xing; Yves A Lussier
Journal:  Bioinformatics       Date:  2006-07-26       Impact factor: 6.937

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