854. The Impact of the CMS SEP-1 Core Measure on Antimicrobial Utilization: a Multicenter Interrupted Time-Series (ITS) Analysis
Session: Oral Abstract Session: Antimicrobial Stewardship: Better Prescribing, Better Outcomes
Thursday, October 4, 2018: 2:00 PM
Room: S 156

Background:  Hospitals began reporting the SEP-1 Core Measure to CMS in October 1, 2015, to promote the use of best practices for patients with sepsis. The impact of SEP-1 on overall antimicrobial utilization (AU), a potential unintended consequence, is unclear. 

Methods: We performed an ITS analysis to evaluate changes in antimicrobial utilization after SEP-1 implementation.  AU was measured as days of therapy (DOT)/1,000 days present (dp) for all adult inpatients who spent more than 24 hours in 18 hospitals in the southeastern US.  The 12-month period from 10/1/14 – 9/30/15 was defined as the “pre” period.  After a 1-month wash-in, the 12-month period from 11/1/15 – 10/31/16 was defined as the “post” period.  AU was aggregated by hospital by month for inpatient units.  Total AU and NHSN AU categories were analyzed separately.  ITS was modeled using a segmented regression analysis through a GEE model with negative binomial distribution and log link. 

Results:  362,460 patients had 688,583 DOT pre-SEP1 (mean 1.9 DOT/admission), and 291,884 patients had 530,382 DOT post-SEP1 (mean 1.8 DOT/admission).  The diagnosis of sepsis (3.1%) and median length of stay (3, IQR 2-4) were unchanged after SEP-1.  Utilization of combined vancomycin and piperacillin-tazobactam (P-T) increased 17% at SEP-1 implementation but this increase was not statistically significant (Table). Overall AU, anti-MRSA agents, and anti-pseudomonal agents were unchanged after SEP-1 (Figure, Table). 

:  Implementation of the CMS SEP-1 measure did not lead to higher rates of AU in our cohort of hospitals, though this study did not assess adherence to SEP-1.  Further research is needed to improve the use of antimicrobial therapy in hospitalized patients with suspected sepsis.   

Table.  Rate Ratios of AU (DOT/1,000 dp) in the Pre- and Post-SEP-1 periods


Pre-SEP-1 initial rate trend (95% CI; p-value)

Change in rate at implementation (95% CI; p-value)

Post-SEP-1 change in rate trend (95% CI; p-value)


1.00 (0.99-1.02); 0.98

1.05 (0.98-1.12); 0.17

0.99 (0.97-1.02); 0.53


0.99 (0.97-1.01); 0.34

1.09 (0.93-1.28); 0.30

1.00 (0.97-1.04); 0.80


1.00 (0.98-1.02); 0.78

1.05 (0.95-1.15); 0.33

0.99 (0.96-1.02); 0.48

Vancomycin + P-T

0.98 (0.95-1.01); 0.29

1.17 (0.96-1.41); 0.12

1.03 (0.98-1.08); 0.31

Figure.  Overall AU in the Pre- and Post-SEP1 periods – ITS Analysis

Deverick J. Anderson, MD, MPH, FIDSA, FSHEA1, Elizabeth Dodds Ashley, PharmD, MHS, FCCP, BCPS1, Alice Parish, MSPH2, Yuliya Lokhnygina, PhD2, Michael Z. David, MD, PhD3, Kevin Hsueh, MD4, Matthew Ryan, MPH1, Leigh Cressman, MA5, Pam Tolomeo, MPH5, Tracey Habrock-Bach, MBBS4, Cherie Hill, Database Analyst4, Rebekah W. Moehring, MD, MPH1 and CDC Prevention Epicenters Program, (1)Duke Center for Antimicrobial Stewardship and Infection Prevention, Durham, NC, (2)Biostatistics and Bioinformatics, Duke University Medical Center, Durham, NC, (3)Division of Infectious Diseases, Hospital of the University of Pennsylvania, Philadelphia, PA, (4)Division of Infectious Diseases, Washington University School of Medicine, St. Louis, MO, (5)Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania, Philadelphia, PA


D. J. Anderson, None

E. Dodds Ashley, None

A. Parish, None

Y. Lokhnygina, None

M. Z. David, None

K. Hsueh, None

M. Ryan, None

L. Cressman, None

P. Tolomeo, None

T. Habrock-Bach, None

C. Hill, None

R. W. Moehring, None

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