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Variation in the Use of Procedures to Monitor Antimicrobial Resistance in U.S. Hospitals

Published online by Cambridge University Press:  21 June 2016

Stephen D. Flach*
Affiliation:
Iowa City Veterans Affairs Medical Center, Iowa City, Iowa University of Iowa, Public Policy Center, Iowa City, Iowa University of Iowa Carver College of Medicine, Iowa City, Iowa
Daniel J. Diekema
Affiliation:
Iowa City Veterans Affairs Medical Center, Iowa City, Iowa
Jon W. Yankey
Affiliation:
Iowa City Veterans Affairs Medical Center, Iowa City, Iowa
Bonnie J. BootsMiller
Affiliation:
Iowa City Veterans Affairs Medical Center, Iowa City, Iowa
Thomas E. Vaughn
Affiliation:
University of Iowa College of Public Health, Iowa City, Iowa
Erika J. Ernst
Affiliation:
University of Iowa College of Pharmacy, Iowa City, Iowa
Bradley N. Doebbeling
Affiliation:
HSR&D Center on Implementing Evidence-Based Practice, Roudebush Veterans Affairs Medical Center the Regenstrief Institute Inc., Indiana University Center for Health Services and Outcomes Research, Indiana University School of Medicine, Indianapolis, Indiana
*
Department of Internal Medicine, SE 629 GH, University of Iowa College of Medicine, 200 Hawkins Drive, Iowa City, IA 52242[email protected]

Abstract

Background:

Antimicrobial resistance is a growing clinical and public health crisis. Experts have recommended measures to monitor antimicrobial resistance; however, little is known regarding their use.

Objective:

We describe the use of procedures to detect and report antimicrobial resistance in U.S. hospitals and the organizational and epidemiologic factors associated with their use.

Methods:

In 2001, we surveyed laboratory directors (n = 108) from a random national sample of hospitals. We studied five procedures to monitor antimicrobial resistance: (1) disseminating antibiograms to physicians at least annually, (2) notifying physicians of antimicrobial-resistant infections, (3) reporting susceptibility results within 24 hours, (4) using automated testing procedures, and (5) offering molecular typing. Explanatory variables included organizational characteristics and patterns of antimicrobial resistance for oxacillin-resistant Staphylococcus aureus, vancomycin-resistant enterococci, quinolone-resistant Escherichia coli, and extended-spectrum beta-lactamase-producing Klebsiella species. Generalized estimating equations accounting for the correlation among outcomes at the facility level were used to identify predictors of the five outcomes.

Results:

Use of the procedures ranged from 85% (automated testing) to 33% (offering molecular typing) and was related to teaching hospital status (OR, 3.1; CI95, 1.5–6.5), participation of laboratory directors on the infection control committee (OR, 1.7; CI95, 1.1–2.8), and having at least one antimicrobial-resistant pathogen with a prevalence greater than 10% (OR, 2.2; CI95, 1.4–3.3).

Conclusion:

U.S. hospitals underutilize procedures to monitor the spread of antimicrobial resistance. Use of these procedures varies and is related to organizational and epidemiologic factors. Further efforts are needed to increase their use by hospitals.

Type
Original Articles
Copyright
Copyright © The Society for Healthcare Epidemiology of America 2005

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References

1.Institute of Medicine. Antimicrobial Drug Resistance: Issues and Options: Workshop Report. Washington, DC: National Academy Press; 1998.Google Scholar
2.Gold, HS, Moellering, RC Jr. Antimicrobial-drug resistance. N Engl J Med 1996;335:14451453.Google Scholar
3.Harrison, PF, Lederberg, J, eds. Antimicrobial Resistance Issues and Options: Workshop Report. Forum on Emerging Infections, Division of Health Sciences Policy, Institute of Medicine. Washington, DC: National Academy Press; 1998.Google Scholar
4.Kunin, CM. Resistance to antimicrobial drugs: a worldwide calamity. Ann Intern Med 1993;118:557561.Google Scholar
5.Schwartz, B, Bell, DM, Hughes, JM. Preventing the emergence of antimicrobial resistance: a call for action by clinicians, public health officials, and patients. JAMA 1997;278:944945.Google Scholar
6.Goldmann, DA, Weinstein, RA, Wenzel, RP, et al.Strategies to prevent and control the emergence and spread of antimicrobial-resistant microorganisms in hospitals: a challenge to hospital leadership. JAMA 1996;275:234240.Google Scholar
7.Shlaes, DM, Gerding, DN, John, JF, et al.Society for Healthcare Epidemiology of America and Infectious Diseases Society of America Joint Committee on the Prevention of Antimicrobial Resistance: guidelines for the prevention of antimicrobial resistance in hospitals. Clin Infect Dis 1997;25:584599.Google Scholar
8.Philipson, TJ. Economic epidemiology and infectious diseases. In: Culyer, AJ, Newhouse, JP, eds. Handbook of Health Economics, vol. 1B. New York: Elsevier Science; 2000:461536.Google Scholar
9.Ahituv, A, Hotz, V, Philipson, T. Is AIDS self-limiting? Evidence on the prevalence elasticity of demand for condoms. Journal of Human Resources 1996;31:869898.CrossRefGoogle Scholar
10.Mullahy, J. It'll only hurt a second? Microeconomic determinants of who gets flu shots. Health Economics 1999;8:924.Google Scholar
11.Philipson, TJ. Private vaccination and public health: an empirical examination for US measles. Journal of Human Resources 1996;31:611630.Google Scholar
12.Philipson, T, Posner, RA. Private Choices and Public Health: The AIDS Epidemic in an Economic Perspective. Cambridge, MA: Harvard University Press; 1993.Google Scholar
13.Diekema, DJ, Pfaller, MA, Jones, RN, et al.Survey of bloodstream infections due to gram-negative bacilli: frequency of occurrence and antimicrobial susceptibility of isolates collected in the United States, Canada, and Latin America for the SENTRY Antimicrobial Surveillance Program, 1997. Clin Infect Dis 1999;29:595607.Google ScholarPubMed
14.Wakefield, DS, Pfaller, M, Massanari, RM, Hammons, GT. Variation in methicillin-resistant Staphylococcus aureus occurrence by geographic location and hospital characteristics. Infect Control 1987;8:151157.Google Scholar
15.Dillman, DA. Mail and Internet Surveys: The Tailored Design Method, ed. 2. New York: John Wiley and Sons; 2000.Google Scholar
16.American Hospital Association. American Hospital Association Annual Survey Database: Fiscal Year 1999 Documentation. Chicago: American Hospital Association; 2001.Google Scholar
17.Institute of Medicine. For-Profit Enterprise in Health Care. Washington, DC: National Academy Press; 1986.Google Scholar
18.Liang, KY, Zeger, SL. Longitudinal data analysis using generalized linear model. Biometrika 1986;73:1322.Google Scholar
19.Ribaudo, HJ, Thompson, SG. The analysis of repeated multivariate binary quality of life data: a hierarchical model approach. Stat Methods Med Res 2002;11:6983.Google Scholar
20.Kaluzny, AD, Hernandez, SR. Organizational change and innovation. In: Shortell, SM, Kaluzny, AD, et al., eds. Health Care Management: A Text in Organizational Theory and Behavior, ed. 2. New York: John Wiley and Sons; 1988:379417.Google Scholar
21.Sloan, FA, Picone, GA, Taylor, DH, Chou, SY. Hospital ownership and cost and quality of care: is there a dime's worth of difference? Journal of Health Economics 2001;20:121.Google Scholar
22.Hirth, RA, Chernew, ME, Orzol, SM. Ownership, competition, and the adoption of new technologies and cost-saving practices in a fixed-price environment. Inquiry 2000;37:282294.Google Scholar
23.Donabedian, A. The Definition of Quality and Approaches to Its Assessment. Ann Arbor, MI: Health Administration Press; 1980.Google Scholar
24.Keeler, EB, Rubenstein, LV, Kahn, KL, et al.Hospital characteristics and quality of care. JAMA 1992;268:17091714.Google Scholar
25.Hartz, AJ, Krakauer, H, Kuhn, EM, et al.Hospital characteristics and mortality rates. N Engl J Med 1989;321:17201725.Google Scholar
26.Dudley, RA, Johansen, KL, Brand, R, Rennie, DJ, Milstein, A. Selective referral to high-volume hospitals: estimating potentially avoidable deaths. JAMA 2000;283:11591166.CrossRefGoogle ScholarPubMed
27.Taylor, DH, Whellan, DJ, Sloan, FAEffect of admission to a teaching hospital on the cost and quality of care for Medicare beneficiaries. N Engl J Med 1999;340:293299.Google Scholar
28.Kimberly, JR. Managerial Innovation in Handbook of Organizational Design: Adapting Organizations to Their Environmentalism, vol. 1. New York: Oxford University Press; 1981:84104.Google Scholar
29.Meyer, J, Rowan, B. Institutionalized organizations: formal structure as myth and ceremony. In: Powell, WW, DiMaggio, P, eds. The New Institutionalism in Organizational Analysis. Chicago: The University of Chicago Press; 1991:4162.Google Scholar
30.Hannan, MT, Freeman, J. Structural inertia and organizational change. American Sociological Review 1984:49:149164.CrossRefGoogle Scholar
31.Winter, SG. Organizing for continuous improvement. In: Cole, RE, Scott, WR, eds. The Quality Movement and Organization Theory. Thousand Oaks, CASage Publications; 2000:4964.Google Scholar
32.Diekema, DJ, BootsMiller, BJ, Vaughn, TE, et al.Antimicrobial resistance trends and outbreak frequency in United States hospitals. Clin Infect Dis 2004;38:7885.CrossRefGoogle ScholarPubMed