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Medical-Resource Use for Suspected Tuberculosis in a New York City Hospital

Published online by Cambridge University Press:  02 January 2015

Robert I. Griffiths ,
Charles L. Hyman ,
Samy I. McFarlane ,
Guillermo R. Saurina ,
Jane E. Anderson ,
Theodore O'Brien ,
Caroline Popper ,
Margaret M. McGrath ,
Robert J. Herbert  and
Marcelino F. Sierra
Robert I. Griffiths*
Affiliation:
Covance Health Economics and Outcomes Services Inc, Washington, DC Program for Medical Technology and Practice Assessment, Johns Hopkins University School of Medicine, Baltimore, Maryland
Charles L. Hyman
Affiliation:
The State University of New York, Health Science Center at Brooklyn, Brooklyn, New York Kings County Hospital Center, Brooklyn, New York Medicalliance, Inc, Columbia, Maryland
Samy I. McFarlane
Affiliation:
The State University of New York, Health Science Center at Brooklyn, Brooklyn, New York Kings County Hospital Center, Brooklyn, New York
Guillermo R. Saurina
Affiliation:
The State University of New York, Health Science Center at Brooklyn, Brooklyn, New York Kings County Hospital Center, Brooklyn, New York
Jane E. Anderson
Affiliation:
Medicalliance, Inc, Columbia, Maryland
Theodore O'Brien
Affiliation:
Becton Dickinson and Company, Franklin Lakes, New Jersey
Caroline Popper
Affiliation:
Becton Dickinson and Company, Franklin Lakes, New Jersey
Margaret M. McGrath
Affiliation:
Covance Health Economics and Outcomes Services Inc, Washington, DC
Robert J. Herbert
Affiliation:
Covance Health Economics and Outcomes Services Inc, Washington, DC
Marcelino F. Sierra
Affiliation:
The State University of New York, Health Science Center at Brooklyn, Brooklyn, New York Kings County Hospital Center, Brooklyn, New York
*
Covance Health Economics and Outcomes Services Inc, 1100 New York Ave NW, Suite 200 E, Washington, DC 20005-3934; e-mail robert.griffiths@covance.com
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Abstract

Objective:

To compare resource use by diagnostic outcome among hospital admissions during which tuberculosis (TB) was suspected.

Design:

Retrospective study based on chart review and microbiology laboratory data.

Setting:

The department of medicine in a municipal hospital serving central Brooklyn, New York.

Participants:

We identified all adult admissions in 1993 during which TB was suspected. We assigned each admission to one of four mutually exclusive groups defined by the results of microbiological tests (acid-fast bacilli [AFB] smear and culture): culture-positive and smear-positive (C + S +); culture-positive and smear-negative (C + S−); culture-negative and smear-positive (C−S+); or culture-negative and smear-negative (C−S−). Each admission was divided into two separate periods to which the utilization of medical resources was assigned: the diagnostic and the postdiagnostic periods, which were separated by the date of receipt of the first definitive culture report.

Results:

Data on 519 admissions (93 C+S+; 57 C+S−; 30 C−S+; and 339 C−S−) were analyzed. Although C+S+ were more likely than other groups to have an admitting diagnosis of TB, approximately one quarter of the admissions without TB (C−S+, C−S−) were admitted with the principal diagnosis of TB. For the four groups, C+S+, C+S−, C−S+, and C−S−, the respective rates of TB isolation and anti-TB treatment, and median lengths of isolation were 98%, 87%, and 34 days; 74%, 74%, and 7 days; 83%, 83%, and 15 days; and 44%, 29%, and 0 days. During the diagnostic period, the rate and length of isolation were similar in the AFB-smear—positive groups (C+S+ and C−S+). We estimated that admissions without culture-proven TB (C−S+ and C−S−) accounted for 3,174 (36%) of the 8,712 days of TB isolation expended and for 65% of the 16,671 days of anti-TB treatment. The vast majority of this resource consumption (2,737 [86%] of 3,174 days of isolation) occurred during the diagnostic period before a definitive culture result was known.

Conclusions:

Our results suggest that prolonged diagnostic uncertainty and misclassification of cases due to false-positive and false-negative smears are associated with substantial medical-resource consumption. New diagnostic modalities that reduce the period of diagnostic uncertainty could reduce the utilization of resources later found to be unnecessary

Type
Original Articles
Information
Infection Control & Hospital Epidemiology , Volume 19 , Issue 10 , October 1998 , pp. 747 - 753
Copyright
Copyright © The Society for Healthcare Epidemiology of America 1998

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References

1.Cantwell, MF, Snider, DE, Cauthen, GM, Onorato, IM. Epidemiology of tuberculosis in the United States, 1985 through 1992. JAMA 1994;272:535–539.Google Scholar
2.Centers for Disease Control and Prevention. Tuberculosis morbidity—United States, 1995. MMWR 1996;45:365–370.Google Scholar
3.Blumberg, HM, Watkins, DL, Berschling, JD, Antle, A, Moore, P, White, N, et al. Preventing the nosocomial transmission of tuberculosis. Ann Intern Med 1995;122:658–663.Google Scholar
4.Stroud, LA, Tokars, JI, Grieco, MH, Crawford, JT, Culver, DH, Edlin, BR, et al. Evaluation of infection control measures in preventing the nosocomial transmission of multidrug-resistant Mycobacterium tuberculosis in a New York City hospital. Infect Control Hosp Epidemiol 1995;16:141–147.Google Scholar
5.Centers for Disease Control and Prevention. Guidelines for preventing the transmission of tuberculosis in health care settings, with special focus on HIV-related issues. MMWR 1990;39(RR-17):20.Google Scholar
6.Brown, RE, Miller, B, Taylor, WR, Palmer, C, Bosco, L, Nicola, RM, et al. Health-care expenditures for tuberculosis in the United States. Arch Intern Med 1995;155:1595–1600.Google Scholar
7.Arno, PS, Murray, CJL, Bonuck, KA, Alcabes, P. The economic impact of tuberculosis in hospitals in New York City: a preliminary analysis. Journal of Law, Medicine & Ethics 1993;21(3-4):317–323.Google Scholar
8.Shulkin, DJ, Brennan, PJ. The cost of caring for patients with tuberculosis: planning for a disease on the rise. Am J Infect Control 1995;23:1–4.Google Scholar
9.Scott, B, Schmid, M, Nettleman, MD. Early identification and isolation of inpatients at high risk for tuberculosis. Arch Intern Med 1994;154:326–330.Google Scholar
10.Greenberg, SD, Frager, D, Suster, B, Walker, S, Stavropoulos, C, Rothpearl, A. Active pulmonary tuberculosis in patients with AIDS: spectrum of radiographic findings (including a normal appearance). Radiology 1994;193:115–119.Google Scholar
11.Shinnick, TM, Good, RC. Diagnostic mycobacteriology laboratory practices. Clin Infect Dis 1995;21:291–299.Google Scholar
12.Bureau of Tuberculosis Control. Tuberculosis in New York City, 1994. Information Summary. New York, NY: New York City Department of Health; 1995.Google Scholar
13.Centers for Disease Control and Prevention. Reported tuberculosis in the United States, 1993. Atlanta GA: US Department of Health and Human Services, Public Health Service, CDC; 1994.Google Scholar
14.Zar, JH. 2nd ed. Biostatistical Analysis. Englewood Cliffs, NJ: Prentice Hall; 1984.Google Scholar
15.Hosmer, DW, Lemeshow, S. Applied Logistic Regression. New York, NY: John Wiley & Sons, Inc., 1989.Google Scholar
16.Rawlings, JO. Applied Regression Analysis: A Research Tool. Pacific Grove, CA: Wadsworth & Brooks/Cole Advanced Books & Software; 1988.Google Scholar
17.Yajko, DM, Madej, JJ, Ng, VL, Hadley, WK. Temporal changes in the positive predictive value of the acid fast (AFB) smear for tuberculosis: impact on the utility of nucleic acid amplification tests. 36th ICAAC. New Orleans, LA; 09 1996. Abstract D058.Google Scholar