Development of an Antibiotic Spectrum Score Based on Veterans Affairs Culture and Susceptibility Data for the Purpose of Measuring Antibiotic De-Escalation: A Modified Delphi Approach

作者:Madaras Kelly Karl*; Jones Makoto; Remington Richard; Hill Nicole; Huttner Benedikt; Samore Matthew
来源:Infection Control and Hospital Epidemiology, 2014, 35(9): 1103-1113.
DOI:10.1086/677633

摘要

OBJECTIVE. Development of a numerical score to measure the microbial spectrum of antibiotic regimens (spectrum score) and method to identify antibiotic de-escalation events based on application of the score. DESIGN. Web-based modified Delphi method. PARTICIPANTS. Physician and pharmacist antimicrobial stewards practicing in the United States recruited through infectious diseases-focused listservs. METHODS. Three Delphi rounds investigated: organisms and antibiotics to include in the spectrum score, operationalization of rules for the score, and de-escalation measurement. A 4-point ordinal scale was used to score antibiotic susceptibility for organism-antibiotic domain pairs. Antibiotic regimen scores, which represented combined activity of antibiotics in a regimen across all organism domains, were used to compare antibiotic spectrum administered early (day 2) and later (day 4) in therapy. Changes in spectrum score were calculated and compared with Delphi participants' judgments on de-escalation with 20 antibiotic regimen vignettes and with non-Delphi steward judgments on de-escalation of 300 pneumonia regimen vignettes. Method sensitivity and specificity to predict expert de-escalation status were calculated. RESULTS. Twenty-four participants completed all Delphi rounds. Expert support for concepts utilized in metric development was identified. For vignettes presented in the Delphi, the sign of change in score correctly classified de-escalation in all vignettes except those involving substitution of oral antibiotics. The sensitivity and specificity of the method to identify de-escalation events as judged by non-Delphi stewards were 86.3% and 96.0%, respectively. CONCLUSIONS. Identification of de-escalation events based on an algorithm that measures microbial spectrum of antibiotic regimens generally agreed with steward judgments of de-escalation status.

  • 出版日期2014-9