Reporting behaviors and perceptions toward the National Healthcare Safety Network antimicrobial use (AU) and antimicrobial resistance (AR) modules
Werth BJ, Dilworth TJ, Escobar ZK, et al. Reporting behaviors and perceptions toward the National Healthcare Safety Network antimicrobial use (AU) and antimicrobial resistance (AR) modules [published online ahead of print, 2022 Jun 15]. Infect Control Hosp Epidemiol. 2022;1-7. doi:10.1017/ice.2022.131
Objectives: To identify characteristics of US health systems and end users that report antimicrobial use and resistance (AUR) data, to determine how NHSN AUR data are used by hospitals and health systems and end users, and to identify barriers to AUR reporting.
Design: An anonymous survey was sent to Society of Infectious Diseases Pharmacists (SIDP) and Society for Healthcare Epidemiology of America (SHEA) Research Network members.
Methods: Data were collected via Survey Monkey from January 21 to February 21, 2020. Respondent and hospital data were analyzed using descriptive statistics.
Results: We received responses from 238 individuals across 43 US states. Respondents were primarily pharmacists (84%), from urban areas, (44%), from nonprofit medical centers (81%), and from hospitals with >250 beds (72%). Also, 62% reported data to the AU module and 19% reported data to the AR module. Use of software for local AU or AR tracking was associated with increased reporting to the AU module (19% vs 64%) and the AR module (2% vs 30%) (P < .001 each). Only 36% of those reporting data to the AU module used NHSN AUR data analysis tools regularly and only 9% reported data to the AR module regularly. Technical challenges and time and/or salary support were the most common barriers to AUR participation cited by all respondents. Among those not reporting AUR data, increased local expectations to report and better software solutions were the most commonly identified solutions to increase AUR reporting.
Conclusions: Efforts to increase AUR reporting should focus on software solutions and salary support for data-entry activities. Increasing expectations to report may incentivize local resource allocation to improve AUR reporting rates.