Semi-Automated Visualization and ANalysis of Trends: A "SAVANT" for Facilitating Antimicrobial Stewardship Using Antistaphylococcal Resistance and Consumption as a Prototype

Authors

Robert J. Clifford, Multidrug-Resistant Organism Repository and Surveillance Network, Walter Reed Army Institute of Research, Silver Spring, Maryland.
Uzo Chukwuma, EpiData Center Department, Navy and Marine Corps Public Health Center, Portsmouth, Virginia.
Michael E. Sparks, Multidrug-Resistant Organism Repository and Surveillance Network, Walter Reed Army Institute of Research, Silver Spring, Maryland.
Douglas Richesson, Multidrug-Resistant Organism Repository and Surveillance Network, Walter Reed Army Institute of Research, Silver Spring, Maryland.
Charlotte V. Neumann, EpiData Center Department, Navy and Marine Corps Public Health Center, Portsmouth, Virginia.
Paige E. Waterman, Global Emerging Infections Surveillance, Armed Forces Health Surveillance Center, Silver Spring, Maryland.
Jacob Moran-Gilad, Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer-Sheva, Israel.
Michael D. Julius, Multidrug-Resistant Organism Repository and Surveillance Network, Walter Reed Army Institute of Research, Silver Spring, Maryland.
Mary K. Hinkle, Multidrug-Resistant Organism Repository and Surveillance Network, Walter Reed Army Institute of Research, Silver Spring, Maryland.
Emil P. Lesho, Rochester Regional HealthFollow

Department

Infectious Diseases

Document Type

Article

Publication Title

Open Forum Infectious Diseases

Abstract

Background: Governments and health care regulators now require hospitals and nursing homes to establish programs to monitor and report antimicrobial consumption and resistance. However, additional resources were not provided. We sought to develop an approach for monitoring antimicrobial resistance and consumption that health care systems can implement with minimal added costs or modifications to existing diagnostic and informatics infrastructure. Methods: Using (1) the electronic laboratory information system of a nationwide managed care network, (2) the 3 most widely used commercial microbiology diagnostic platforms, and (3) , one of the most common causes of infections worldwide, as a prototype, we validated the approach dubbed "SAVANT" for Semi-Automated Visualization and ANalysis of Trends. SAVANT leverages 3 analytical methods (time series analysis, the autoregressive integrated moving average, and generalized linear regression) on either commercial or open source software to report trends in antistaphylococcal use and resistance. Results: All laboratory results from January 2010 through December 2015 from an annual average of 9.2 million health care beneficiaries were queried. Inpatient and outpatient prescription rates were calculated for 8 key antistaphylococcal compounds. Trends and relationships of antistaphylococcal consumption and resistance among 81 840 unique isolates from >6.5 million cultures were revealed. Conclusions: Using existing or freely available resources, SAVANT was successfully implemented across a complex and geographically dispersed 280-hospital network, bridging a critical gap between medical informatics, large-scale data analytics, and mandatory reporting of health care quality metrics.

First Page

ofy066

DOI

10.1093/ofid/ofy066

Volume

5

Issue

4

Publication Date

4-1-2018

PubMed ID

30568986

Recommended Citation

Clifford, R. J., Chukwuma, U., Sparks, M. E., Richesson, D., Neumann, C. V., Waterman, P. E., Moran-Gilad, J., Julius, M. D., Hinkle, M. K., & Lesho, E. P. (2018). Semi-Automated Visualization and ANalysis of Trends: A "SAVANT" for Facilitating Antimicrobial Stewardship Using Antistaphylococcal Resistance and Consumption as a Prototype. Open Forum Infectious Diseases, 5 (4), ofy066. https://doi.org/10.1093/ofid/ofy066