Implementation and Evaluation of an Algorithm for Isolation of Patients With Suspected Pulmonary Tuberculosis

Author:

Pegues Clare F.,Johnson Douglas C.,Pegues David A.,Spencer Maureen,Hopkins Cyrus C.

Abstract

AbstractObjective: To implement and evaluate an algorithm designed to assist in the consistent placement of patients with suspected pulmonary tuberculosis into negative-pressure isolation rooms (NPIRs).Design: A standard algorithm was designed for the appropriate room placement of patients with suspected pulmonary tuberculosis using clinical, radiographic, and laboratory criteria and reported risk factors. A case-patient was defined as an inpatient who had at least one Mycobacterium tuberculosis culture-positive respiratory specimen from January 1, 1993, through December 31, 1994. Demographic, clinical, laboratory, case contact, and isolation and room placement data were collected prospectively on all case-patients.Setting: A 900-bed university teaching and referral center.Results: During 1993 and 1994, 69 patients were evaluated for possible pulmonary tuberculosis, and 31 case-patients were identified. Of the 31 case-patients, 26 (84%) were placed on respiratory isolation in NPIRs, including 19 (61%) who were isolated within 24 hours of admission (1993, 14 of 20 [70%]; 1994, 5 of 11 [45%]). Seven case-patients (23%) were isolated in NPIRs following delays that ranged from 2 to 31 days (median, 9 days), and five case-patients (16%) never were isolated during admissions of from 3 to 28 days (median, 4 days). These 12 case-patients contributed a total of 136 patient-exposure days during their hospitalizations. Misclassification of patient risk status by user error delayed isolation of five (42%) of the 12 improperly isolated case-patients.Conclusions: The use of an algorithm incorporating radiographic, laboratory, and clinical criteria and reported risk factors may assist in the rapid isolation of patients with suspected pulmonary tuberculosis.

Publisher

Cambridge University Press (CUP)

Subject

Infectious Diseases,Microbiology (medical),Epidemiology

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