Session : SHEA Decennial Top Oral Abstract Awards

207 - Development of an Electronic Tool to Measure Daily Appropriateness of Inpatient Antibacterial Use

Oral Abstract

Location: On Demand

Background: Assessing antimicrobial use (AU) appropriateness is a cornerstone of antimicrobial stewardship, largely accomplished through time-intensive manual chart review of specific agents or diagnoses. Efforts to evaluate appropriateness have focused on assessing the appropriateness of an entire treatment course. An electronic measure was developed to assess the appropriateness of each day of inpatient AU leveraging electronic health record data.

Methods: We extracted contextual data including risk factors for resistant organisms, allergies, constitutional signs and symptoms from diagnostic and procedural codes, and microbiological findings from the electronic health records of patients in Veterans Health Administration inpatient wards reporting data to the National Healthcare Safety Network (NHSN) AU option from 2017 - 2018. Only antibacterial categories in Figure 1 were included. Respiratory, urinary tract, skin and soft-tissue, and other infection categories were defined and applied to each hospital day. Algorithm rules were constructed to evaluate AU based on the clinical context (e.g., in the ICU, during empiric therapy, drug-bug match, recommended drugs and duration). Rules were drawn from available literature, discussed with experts, and refined empirically. Generally, rules allowed for use of first-line agents unless risk factors or contraindications were identified. AU was categorized as appropriate, inappropriate, or indeterminate for each day, then aggregated into an overall measure of facility-level AU appropriateness. A validation set of 20 charts were randomly selected for manual review.

Results: Facility distribution of appropriateness, inappropriateness, and indeterminate AU by four of the adult 2017-baseline NHSN Standardized Antimicrobial Administration Ratio (SAAR) categories, are demonstrated in Figure 1. The median (interquartile range [IQR]) facility-level inappropriateness across all SAAR categories was 37.2% (29.4 – 52.5%). The median (IQR) facility-level indeterminate AU across all SAAR categories was 14.4% (9.1 – 21.2%). Chart review of 20 admissions showed agreement with algorithm appropriateness and inappropriateness in 95.4% of 240 antibacterial days.

Conclusion: We developed a comprehensive, flexible electronic tool to evaluate AU appropriateness for combinations of setting, antibacterial agent, syndrome, or timeframe (e.g., empiric, definitive, excess duration) of interest. Application of our algorithm in two years of VA acute care data suggest substantial inter-facility variability, with the highest rates of inappropriateness observed for anti-MRSA therapy. Preliminary chart review demonstrates agreement between electronic and manual review in more than 95% of antimicrobial days. This approach may be useful to identify potential stewardship targets, in the development of decision support systems, and in conjunction with other metrics to track AU over time.

Presenting Author(s)

Vanessa W. Stevens, PhD

Research Associate Professor
IDEAS Center of Innovation, VA Salt Lake City Health Care System
Salt Lake City, UT

Disclosure: I do not have any relevant financial / non-financial relationships with any proprietary interests.

Slides Slides and Audio

Co-Author(s)

PB

Pamela Belperio

Disclosure: No Disclosure
MN

Melinda M. Neuhauser, PharmD, MPH

Pharmacist and Acute Care Lead
Centers for Disease Control and Prevention
Chicago, Illinois

Disclosure: I do not have any relevant financial / non-financial relationships with any proprietary interests.
Lauri Hicks, DO

Director, Office of Antibiotic Stewardship
Centers for Disease Control and Prevention
Atlanta, Georgia

Disclosure: I do not have any relevant financial / non-financial relationships with any proprietary interests.
MN

McKenna Nevers

Disclosure: No Disclosure
Matthew B. Goetz, MD

Chief, Infectious Diseases
VA Greater Los Angeles Healthcare System and David Geffen School of Medicine at UCLA, VA-CDC Practice-Based Research Network
Los Angeles, CA

Disclosure: I do not have any relevant financial / non-financial relationships with any proprietary interests.
NC

Nai-Chung N. Chang, PhD

Postdoctoral Research Associate
University of Utah
Salt Lake City, Utah

Disclosure: No Disclosure
Arjun Srinivasan, MD

Associate Director for Healthcare Associated Infection Prevention Programs, Division of Healthcare Quality Promotion, National Center for Emerging and Zoonotic Infectious Diseases
Centers for Disease Control and Prevention
Atlanta, Georgia

Disclosure: No Disclosure
MJ

Makoto M. Jones, MD

Assistant Professor
IDEAS Center of Innovation, VA Salt Lake City Health Care System
Salt Lake City, Utah

Disclosure: I do not have any relevant financial / non-financial relationships with any proprietary interests.