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

Abstract

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.

Evaluating Antimicrobial Use and Spectrum of Activity in Ontario Hospitals: Feasibility of a Multicentered Point Prevalence Study

“…Recently, there have been some examples in the literature of methods to determine the breadth of antibiotic exposure [12, 26], including the ASI [25]. In our pilot, we attempted to enhance conventional PPS metrics by including ASI normalized by patient cases.…”

“…The ASI was developed to categorize antibiotics based on their activity against clinically important organisms to benchmark utilization patterns across hospitals and is intended to provide a measure of the breadth of antibiotic exposure. Although there are several methods in the literature that provide similar measures [12, 26], the ASI was selected as it could be calculated using information already collected as part of the PPS. Mean patient ASI was determined for each hospital and by indication per patient case.…”

Outcomes Associated With Antimicrobial De-escalation of Treatment for Pneumonia Within the Veterans Healthcare Administration

“…In the original cohort of 31000 HCAP cases, approximately 20000 were excluded from the de-escalation analysis due to stays of <5 or >14 days to capture a time frame that allowed for culture results and clinical stability to be assessed [8–10]. It is possible that some patients were de-escalated and discharged before hospitalization day 5.…”

Expert Consensus on Metrics to Assess the Impact of Patient-Level Antimicrobial Stewardship Interventions in Acute-Care Settings

“…For example, de-escalation from broad to narrow antimicrobial therapy is an accepted, basic principle of antimicrobial stewardship that should be responsive to patient-level interventions. This metric was accepted in all criteria except the feasibility criterion due to the state of preliminary work in defining spectrum scores [11] and de-escalation events [12] from electronic data, the need for validation of these definitions in other study populations, and the need for more experience in implementing these metrics into routine practice. As another example, the panel achieved consensus that a days of therapy numerator over dominators of either patient-days or admissions were useful to capture in hospitals with electronic health records; however, several members voiced knowledge that many facilities lack the information technology resources to capture these data.…”