As antibiotic resistance increases globally, it becomes more difficult to select empiric antibiotic therapy, particularly in patients with sepsis who stand to benefit from early adequate treatment. In particular it is difficult for clinicians to balance antibiotic stewardship principles (the need to avoid unnecessary prescribing of antibiotics that have an excessively broad spectrum of activity that favour resistance development) and under treatment. The integration of multiple risk variables for resistance are hard for clinicians to translate into clinical action, and is seemingly at odds with the natural inclination to provide heuristic/emotion-based antibiotic selection. The inappropriate treatment of sepsis is not uniformly too broad, or too narrow, and there is a need to optimize and tailor selection of antibiotic therapy to each patient, such that those that are at risk for resistant organisms receive broad therapy, and those that are not at risk, receive narrower antibiotic agents. Clinicians need support picking the right antibiotic for each patient, and from this they can potentially drive reduction of unnecessarily broad antibiotic prescribing while preserving adequacy of treatment. Individualized clinical prediction models and decision support interventions are promising approaches that meet these needs by improving the classification of patient risk for antibiotic resistant or susceptible infections in sepsis. Unfortunately, few have been validated in the clinical setting and larger rigorous studies are needed to provide the evidence to support broader clinical adoption. The investigators will perform a cluster randomized cross-over trial of an individualized antibiotic prescribing decision support intervention for providers treating hospitalized patients with suspected sepsis. The aim of this trial is to determine whether a stewardship led clinical decision support intervention can improve antibiotic de-escalation in patients with sepsis while maintaining or improving adequacy of antibiotic coverage. This decision support intervention will be based on a combination of proven decision heuristics (for Gram-positive organisms) and modelled predicted susceptibilities (for Gram-negative organisms) that are individualized to the patient. The primary outcome will be the proportion of patients de-escalated from their initial empiric regimen at 48 hours.
Study Type
INTERVENTIONAL
Allocation
RANDOMIZED
Purpose
TREATMENT
Masking
NONE
Enrollment
1,440
A clinical decision support algorithm for empiric antibiotic selection in suspected infection.
Trillium Health Partners
Mississauga, Ontario, Canada
RECRUITINGThe Ottawa Hospital
Ottawa, Ontario, Canada
RECRUITINGSunnybrook Health Sciences Centre
Toronto, Ontario, Canada
RECRUITINGNumber of Patients De-escalated
De-escalation from empiric antibiotic regimen at 48 hours (or at time of discharge if earlier) from receipt of index antibiotics \[Binary\].
Time frame: 48 hours
Time to adequate therapy for positive blood cultures
Time to adequate therapy for patients with positive blood cultures (hours from time of first index blood culture collection to first dose of agent(s) active against all pathogen(s) in the peri-index positive blood cultures). \[Continuous\] \[Stratified by ampC organisms\]
Time frame: 0-7 days
Time to adequate therapy for positive non-screening cultures
Time to adequate therapy for patients with positive non-screening cultures including blood cultures (hours from time of first index blood culture collection to first dose of agent(s) active against all pathogen(s) in the peri-index positive cultures). \[Continuous\]\[Stratified by ampC organisms\]
Time frame: 0-7 days
Number of Patients Receiving Adequate Therapy at 48 hours based on blood cultures
Receipt of adequate antibiotic therapy within 48 hours (or discharge if earlier) from first index blood culture collection for patients with positive blood cultures (active against all pathogens in peri-index positive blood cultures). \[Binary\]
Time frame: 48 hours
Number of Patients Receiving Adequate Therapy at 48 hours based on non-screening cultures
Receipt of adequate antibiotic therapy within 48 hours (or discharge if earlier) from first index blood culture collection for patients with positive non-screening cultures including blood (active against all pathogens in peri-index positive cultures). \[Binary\]
Time frame: 48 hours
Mortality
In-hospital mortality, during index admission, and within 90 days of index event. \[Binary\]
Time frame: 90 days
Length of stay
Hospital length of stay on index admission (days) up to 90 days. \[Continuous\]
Time frame: 0-90 days
De-escalation extent
Extent of antibiotic de-escalation at 48 hours from index or discharge if earlier (ordinal value up or down the de-escalation cascade, + escalation, - for de-escalation). \[Integer from -infinity to infinity\]
Time frame: 48 hours
Antibiotic spectrum at completion
Antibiotic spectrum rank at 7 days from index antibiotics (or discharge if earlier). \[Ordinal\]
Time frame: Completion of therapy, up to 90 days
Number of Patients with C.difficile Infection
Positive stool testing for Clostridioides difficile during index admission, and within 90 days of index. \[Binary\]
Time frame: 90 days
Number of Patients Requiring Dialysis
New requirement for dialysis during index admission, and within 90 days of index. \[Binary\]
Time frame: 90 days
Days of antibiotic therapy
Total antibiotic days of therapy (DOT) during the first 7 days from index antibiotics (or prior to discharge if earlier), including by spectrum-level. \[Continuous\]
Time frame: End of index admission, up to 90 days
Number of Patients with Antibiotic Escalation
Newly started Gram-positive or Gram-negative coverage, or increases in spectrum of antibiotic therapy, as part of the intervention recommendation. \[Binary\]
Time frame: 48 hours
Time to De-escalation
Description: Time to antibiotic de-escalation (hours from receipt of index antibiotics). \[Continuous\]\[Stratified by ampC organisms\]
Time frame: 0-7 days
Number of Patients with Recommended change in Gram-negative coverage
Recommended change in antibiotic therapy by Gram-negative model. \[Binary\]
Time frame: At time of assessment (0 days)
Number of Patients with Accepted change in Gram-negative coverage
Recommended change in antibiotic therapy by Gram-negative model was accepted (acceptance defined as change to some or all of the therapy as recommended within 24 hours of index). \[Binary\]
Time frame: Within 24 hours
Number of Patients with Recommended change in Gram-positive coverage
Recommended change in antibiotic therapy by Gram-positive algorithm. \[Binary\]
Time frame: At time of assessment (0 days)
Number of Patients with Accepted change in Gram-positive coverage
Recommended change in antibiotic therapy by Gram-positive algorithm was accepted and ordered (acceptance defined as change to some or all of the therapy as recommended within 24 hours of index). \[Binary\]
Time frame: Within 24 hours
Number of Patients with Non-recommended escalation at 7 days
Escalation of antibiotic therapy (apart from recommended escalation) within 7 days of receipt of index antibiotics (or prior to discharge if earlier). \[Binary\]
Time frame: 7 days
Number of Patients with ICU admit or mortality
Admitted to ICU on day 7 or not alive at day 7 from receipt of index antibiotics. \[Binary\]
Time frame: 7 days
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