1. Impact of clinical surveillance decision support software in optimizing pharmacy‐driven
antimicrobial stewardship interventions
Sohan Shah, BBA Candidate1; Yin Wong, PharmD, BCPS1,2; Marshall Robbins, PharmD3; Sabrina Thompson, PharmD3; Misty Clark, PharmD, BCPS3; Trent Beach, PharmD, MBA, MHA,
BCPS, FASHP, FACHE1
1CHSPSC, LLC., Department of Pharmacy Services, Franklin, TN
2Wolters Kluwer Health, Pharmacy OneSource®, Madison, WI
3Crestwood Medical Center, Department of Pharmacy, Huntsville, AL
Poster Number
5A-338
50th ASHP Midyear Clinical Meeting
New Orleans, Louisiana
December 6 – 10, 2015
BACKGROUND METHODS
DISCLOSURES
PURPOSE
CONCLUSION
Community Health Systems
Department of Pharmacy Services
Tel: 617-610-9255
Email: yin_wong@chs.net
Authors of this presentation have the following to disclose concerning possible financial or personal relationships with
commercial entities that may have direct or indirect interests in the subject matter of this presentation.
Yin Wong: Fellow, Wolters Kluwer Health
All other authors have nothing to disclose
REFERENCE
 Center for Disease Control and Prevention. Core Elements of Hospital Antibiotic Stewardship Programs.
Atlanta, GA: US Department of Health and Human Services, CDC; 2014.
 Dellit TH, Owens RC, McGowan Jr. JE, et al. Infectious Diseases Society of America and the Society for
Healthcare Epidemiology of America guidelines for developing an institutional program to enhance
antimicrobial stewardship. Clinical Infectious Diseases. 2007; 44: 159-177.
 The White House. National Action Plan for Combating Antibiotic-Resistant Bacteria. Washington D.C., MD:
The White House; 2015.
Our study is expected to demonstrate:
 An increase numbers of antimicrobial stewardship focused clinical
interventions
 The use of clinical surveillance decision support system can optimize
pharmacy-driven antimicrobial stewardship efforts
 In response to the upcoming Centers of Medicare & Medicaid
Services (CMS) Condition of Participation (COP) requirement for the
establishment of antimicrobial stewardship program (ASP) by end of
2017, healthcare professionals have been working persistently to
improve antimicrobial stewardship (AS) efforts
 Although traditionally ASP have been possible only in large academic
medical centers with sufficient resources, with the upcoming CMS
COP incentives, the development of ASP are expected to increase
 For hospitals that have restricted resources, clinical surveillance
decision support software can be implemented to assist pharmacists
in streamlining workflow and identify patients who are in need of
pharmacy-driven clinical intervention
 To investigate the impact of clinical surveillance decision support
software (Sentri7®; Madison WI) in optimizing pharmacy-driven
antimicrobial stewardship interventions, limited to de-escalation and
drug-bug mismatch
Diagram 2. Data Collection from Multiple Technology Platform (Pre-Data)
* CHS and Community Health Systems are tradenames /trademarks of CHSPSC, LLC, which provides management services to affiliates of Community Health Systems, Inc.
STUDY DESIGN
Study Design
 Single-center, quasi-experimental study
Study Site
 Crestwood Medical Center: a 150-bed rural, community-based hospital
located at central Alabama
Study Period
 Pre-period: March 1, 2014 to February 28, 2015 (12 months)
 Post-period: April 1, 2015 to March 31, 2016 (12 months)
Inclusion Criteria
 Adult patients ≥ 18 years of age
 Eligible for the following pharmacy-driven clinical interventions:
 Antimicrobial therapy de-escalation (defined as switching antibiotic
therapy from broad-spectrum to narrow-spectrum)
 Drug-bug mismatch (defined as culture & sensitivity results
demonstrating a resistant organism to prescribed antibiotic)
Diagram 1. Study Timeline
ACKNOWLEDGMENT
The authors of this poster would like to acknowledge the following CHSPSC, LLC clinical informatics and
Pharmacy OneSource® clinical services team member for providing their expertise and assistance for the
success of the described study:
Patrick Phiri, MSIS, MSPS: Analyst I, Clinical Informatics
Heather Rosdeutscher, PharmD, MHCI; Clinical Program Manager, Clinical Services
Manjunath Shetty Subbaiah, PMP: Director, Clinical Informatics
Eight rules, “triggers” have been identified and programmed into the Sentri7® software at study sites to prospectively identify AS efforts
Execution
Phase Rule Name Rule Description
1
Vancomycin Drug-Bug
Mismatch
Identify patients who are receiving vancomycin but
causative organism is resistant/intermediate to
vancomycin
Quinolone Drug-Bug
Mismatch
Identify patients who are receiving quinolone
therapy but causative organism is
resistant/intermediate to quinolone class
Carbapenem Drug-Bug
Mismatch
Identify patients who are receiving carbapenems
but causative organism is resistant/intermediate to
carbapenems
2
MSSA Streamlining
Identify patients who are receiving anti-MRSA
agent but culture & sensitive results show MSSA
VSE Streamlining
Identify patients with VSE infection but receiving
alternative broad-spectrum antibiotic
3
E.coli Streamlining
Identify patients who are receiving broad spectrum
gram-negative antibiotic but E.coli is sensitive to
narrow-spectrum antibiotic therapy
Echinocandins Use for
candida spp. Susceptible to
Fluconazole
Identify patients who are receiving echinocandins
but candida spp. is susceptible to azoles
Enterococcus faecalis
Streamlining
Identify patients who are receiving vancomycin or
linezolid but E. faecalis is sensitive to ampicillin
Table 1. Clinical Surveillance Rules Data Collection
The following data will be collected throughout study period:
 Patient demographics:
 Age
 Gender
 Primary diagnosis
 Prior admission
 Clinical lab data to assess organ functions
 Renal and liver labs
 Medication orders
 Microbiology labs:
 Specimen dates and source
 Culture & sensitivity
Pharmacy-driven Clinical Intervention Workflow
 Upon triggering an alert, pharmacists will be instructed to
review the eight rules, assess the patient’s information, and
make clinical recommendations to physicians as a part of their
daily workflow
 Pharmacists will then document interventions in the clinical
surveillance software
3/1/2014 3/31/2016
4/1/2014 7/1/2014 10/1/2014 1/1/2015 4/1/2015 7/1/2015 10/1/2015 1/1/2016
3/1/2014 - 2/28/2015
Pre-period: investigator queried data from various technology platform
to analyze potential antimicrobial stewardship interventions
11/20/20153/1/2015
4/1/2015 5/1/2015 6/1/2015 7/1/2015 8/1/2015 9/1/2015 10/1/2015 11/1/2015
3/1/2015 - 3/31/2015
Phase I Study Rules Implementation & Validation
6/30/2015 - 8/19/2015
Phase II Study Rules
Implementation & Validation
11/20/2015
Phase III Study Rules
Implementation & Validation Completed
3/1/2015 - 11/20/2015
Phase-Approach Intervention Implmentation & Validation
4/1/2015 - 3/31/2016
Post-period: investigator will gather data
from study rules and perform analysis to determine
the impact of clinical surveillance decision support
Sentri7®
Study site utilizes
Microscan® for
microbiology lab
testing
Microbiology data
then sent to Orchard®
interface system
Microbiology lab
data for pre-period
were queried from
Orchard®
Interface system
transferred data to the
electronic health record,
MedHost® at study site
Data source for pre-period:
Patient demographics, clinical lab
data and medication orders were
queried from EHR
Data-source for post-period: Patient demographics, clinical lab
data, medication orders, and microbiology lab data. The eight
antimicrobial stewardship focus rules were programmed into
Sentri7® to help identify patients of interest