74. Use of an Epic-Enabled Antimicrobial Stewardship Analytics Platform to Benchmark Suboptimal Restricted Antimicrobial Use Within an Academic Hospital
Session: Oral Abstract Session: Antibiotic Stewardship
Thursday, October 27, 2016: 9:00 AM
Room: 288-290

Background: 

Antibiotic stewardship programs (ASP) routinely use days of therapy per 1,000 patient days (DOT/1000PD) to measure and track aggregate antimicrobial use and impact of interventions. However, this metric does not discriminate between optimal and suboptimal use.

Methods:  At Stanford Health Care (SHC), the ASP, Clinical and Business Analytics, and Epic teams developed an electronic analytics platform that leverages Epic’s functionality to track suboptimal restricted antimicrobial use. With Epic v.2015, we modified 3 iVent fields of the template to identify appropriateness, the prescriber, and infectious disease (ID) consultant. This data was then collected during ASP prospective audit and feedback of restricted antimicrobials. Antimicrobial utilization and iVent data were sourced to an analytics platform for aggregation and visualization on a near real-time analytics platform that is refreshed daily.

Results:  The analytics platform was implemented in September 2015 and includes 5 analyses of 15 restricted antimicrobials (figures 1,2). Restricted antimicrobial DOT/1000PD dropped by 29% after ASP was established in 2012 and by 16% since September 2015 (projected >$3 million cost avoidance) (figure 2). Because our main goal was to reduce suboptimal use of antimicrobials, we quantified this with DOT/1000PD (figure 3), which decreased by 64% after we implemented a new restricted antimicrobial process in November 2015. We screened 92% of restricted antimicrobial orders and intervened on 25% of cases with an acceptance rate > 75%. Restricted antimicrobials were initiated by primary teams in 46% (421/906) of cases, and were suboptimal in >30% of cases amongst the 5 most frequent prescribers. Benchmarking of restricted antimicrobial use was used to report ASP metrics and provide departmental feedback.

Conclusion:  We created a real time stewardship analytics platform using data sourced from Epic. While DOT/1000PD may be useful for benchmarking antimicrobial use with external institutes, identification of suboptimal DOT/1000PD by individuals and service lines is a novel metric that has proven useful in identifying internal opportunities and allocating resources for stewardship efforts. Furthermore, this solution is scalable to other antimicrobials and organizations.



Lina Meng, PharmD1, Emily Mui, PharmD1, Gabriela Espinosa, MS2, Vinhkhoa Nguyen, PharmD3, Marisa Holubar, MD, MS4 and Stan Deresinski, MD, FIDSA4, (1)Pharmacy, Stanford Health Care, Stanford, CA, (2)Clinical & Business Analytics, Stanford Health Care, Palo Alto, CA, (3)Clinical Informatics, Stanford Health Care, Palo Alto, CA, (4)Division of Infectious Diseases and Geographic Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, CA

Disclosures:

L. Meng, None

E. Mui, None

G. Espinosa, None

V. Nguyen, None

M. Holubar, None

S. Deresinski, None

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