Abstract
As part of a project to help physicians make more appropriate treatment decisions, we implemented a clinical prediction rule that computes the probability of true bacteremia for positive blood cultures and displays this information when culture results are viewed online. Prior to implementing the rule, we performed a revalidation study to verify the accuracy of the previously published logistic regression model. We randomly selected 114 cases of positive blood cultures from a recent one-year period and performed a paper chart review with the help of infectious disease experts to determine whether the cultures were true positives or contaminants. Based on the results of this revalidation study, we updated the probabilities reported by the model and made additional enhancements to improve the accuracy of the rule. Next, we implemented the rule into our hospital's laboratory computer system so that the probability information was displayed with all positive blood culture results. We displayed the prediction rule information on approximately half of the 2184 positive blood cultures at our hospital that were randomly selected during a 6-month period. During the study, we surveyed 54 housestaff to obtain their opinions about the usefulness of this intervention. Fifty percent (27/54) indicated that the information had influenced their belief of the probability of bacteremia in their patients, and in 28% (15/54) of cases it changed their treatment decision. Almost all (98% (53/54)) indicated that they wanted to continue receiving this information. We conclude that the probability information provided by this clinical prediction rule is considered useful to physicians when making treatment decisions.
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Selected References
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- Bates D. W., Cook E. F., Goldman L., Lee T. H. Predicting bacteremia in hospitalized patients. A prospectively validated model. Ann Intern Med. 1990 Oct 1;113(7):495–500. doi: 10.7326/0003-4819-113-7-495. [DOI] [PubMed] [Google Scholar]
- Bates D. W., Goldman L., Lee T. H. Contaminant blood cultures and resource utilization. The true consequences of false-positive results. JAMA. 1991 Jan 16;265(3):365–369. [PubMed] [Google Scholar]
- Bates D. W., Lee T. H. Rapid classification of positive blood cultures. Prospective validation of a multivariate algorithm. JAMA. 1992 Apr 8;267(14):1962–1966. [PubMed] [Google Scholar]
- MacGregor R. R., Beaty H. N. Evaluation of positive blood cultures. Guidelines for early differentiation of contaminated from valid positive cultures. Arch Intern Med. 1972 Jul;130(1):84–87. [PubMed] [Google Scholar]
- Poses R. M., Anthony M. Availability, wishful thinking, and physicians' diagnostic judgments for patients with suspected bacteremia. Med Decis Making. 1991 Jul-Sep;11(3):159–168. doi: 10.1177/0272989X9101100303. [DOI] [PubMed] [Google Scholar]
- Teich J. M., Glaser J. P., Beckley R. F., Aranow M., Bates D. W., Kuperman G. J., Ward M. E., Spurr C. D. The Brigham integrated computing system (BICS): advanced clinical systems in an academic hospital environment. Int J Med Inform. 1999 Jun;54(3):197–208. doi: 10.1016/s1386-5056(99)00007-6. [DOI] [PubMed] [Google Scholar]
- Teich J. M., Spurr C. D., Schmiz J. L., O'Connell E. M., Thomas D. Enhancement of clinician workflow with computer order entry. Proc Annu Symp Comput Appl Med Care. 1995:459–463. [PMC free article] [PubMed] [Google Scholar]
- Weingarten S. Practice guidelines and prediction rules should be subject to careful clinical testing. JAMA. 1997 Jun 25;277(24):1977–1978. [PubMed] [Google Scholar]
- Weinstein M. P., Reller L. B., Murphy J. R., Lichtenstein K. A. The clinical significance of positive blood cultures: a comprehensive analysis of 500 episodes of bacteremia and fungemia in adults. I. Laboratory and epidemiologic observations. Rev Infect Dis. 1983 Jan-Feb;5(1):35–53. doi: 10.1093/clinids/5.1.35. [DOI] [PubMed] [Google Scholar]