Terri Smith1, Carla L Philmon2, Gregory D Johnson3, William S Ward4, LaToya L Rivers5, Sharon A Williamson6, Edward L Goodman7. 1. Clinical Pharmacy Specialist, Department of Pharmacy, Texas Health Presbyterian Hospital of Dallas , Dallas, Texas. 2. Clinical Pharmacy Manager, Department of Pharmacy, Texas Health Presbyterian Hospital of Dallas , Dallas, Texas. 3. Pharmacy Director, Department of Pharmacy, Texas Health Presbyterian Hospital of Dallas , Dallas, Texas. 4. Decision Support Analyst, Department of Finance, Texas Health Presbyterian Hospital of Dallas , Dallas, Texas. 5. Data Warehouse Administrator, Department of Quality Improvement, Texas Health Presbyterian Hospital of Dallas , Dallas, Texas. 6. Infection Prevention Manager, Department of Infection Prevention, Texas Health Presbyterian Hospital of Dallas , Dallas, Texas. 7. Hospital Epidemiologist, Department of Internal Medicine, Texas Health Presbyterian Hospital of Dallas , Dallas, Texas .
Abstract
BACKGROUND: Antibiotic stewardship has been proposed as an important way to reduce or prevent antibiotic resistance. In 2001, a community hospital implemented an antimicrobial management program. It was successful in reducing antimicrobial utilization and expenditure. In 2011, with the implementation of a data-mining tool, the program was expanded and its focus transitioned from control of antimicrobial use to guiding judicious antimicrobial prescribing. OBJECTIVE: To test the hypothesis that adding a data-mining tool to an existing antimicrobial stewardship program will further increase appropriate use of antimicrobials. DESIGN: Interventional study with historical comparison. METHODS: Rules and alerts were built into the data-mining tool to aid in identifying inappropriate antibiotic utilization. Decentralized pharmacists acted on alerts for intravenous (IV) to oral conversion, perioperative antibiotic duration, and restricted antimicrobials. An Infectious Diseases (ID) Pharmacist and ID Physician/Hospital Epidemiologist focused on all other identified alert types such as antibiotic de-escalation, bug-drug mismatch, and double coverage. Electronic chart notes and phone calls to physicians were utilized to make recommendations. RESULTS: During 2012, 2,003 antimicrobial interventions were made with a 90% acceptance rate. Targeted broad-spectrum antimicrobial use decreased by 15% in 2012 compared to 2010, which represented cost savings of $1,621,730. There were no statistically significant changes in antimicrobial resistance, and no adverse patient outcomes were noted. CONCLUSIONS: The addition of a data-mining tool to an antimicrobial stewardship program can further decrease inappropriate use of antimicrobials, provide a greater reduction in overall antimicrobial use, and provide increased cost savings without negatively affecting patient outcomes.
BACKGROUND: Antibiotic stewardship has been proposed as an important way to reduce or prevent antibiotic resistance. In 2001, a community hospital implemented an antimicrobial management program. It was successful in reducing antimicrobial utilization and expenditure. In 2011, with the implementation of a data-mining tool, the program was expanded and its focus transitioned from control of antimicrobial use to guiding judicious antimicrobial prescribing. OBJECTIVE: To test the hypothesis that adding a data-mining tool to an existing antimicrobial stewardship program will further increase appropriate use of antimicrobials. DESIGN: Interventional study with historical comparison. METHODS: Rules and alerts were built into the data-mining tool to aid in identifying inappropriate antibiotic utilization. Decentralized pharmacists acted on alerts for intravenous (IV) to oral conversion, perioperative antibiotic duration, and restricted antimicrobials. An Infectious Diseases (ID) Pharmacist and ID Physician/Hospital Epidemiologist focused on all other identified alert types such as antibiotic de-escalation, bug-drug mismatch, and double coverage. Electronic chart notes and phone calls to physicians were utilized to make recommendations. RESULTS: During 2012, 2,003 antimicrobial interventions were made with a 90% acceptance rate. Targeted broad-spectrum antimicrobial use decreased by 15% in 2012 compared to 2010, which represented cost savings of $1,621,730. There were no statistically significant changes in antimicrobial resistance, and no adverse patient outcomes were noted. CONCLUSIONS: The addition of a data-mining tool to an antimicrobial stewardship program can further decrease inappropriate use of antimicrobials, provide a greater reduction in overall antimicrobial use, and provide increased cost savings without negatively affecting patient outcomes.
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