An Opt-out Approach to Antimicrobial Stewardship Utilizing Electronic Alert Recommendations at a Community Hospital

Matthew Song, PharmD, Ashley M Wilde, PharmD, BCPS-AQ ID

Norton Healthcare, Department of Pharmacy

Acknowledgements: The authors would like to thank Dr Paul Schulz and Dr Shaina Doyen with their assistance in providing antimicrobial recommendations. Thanks to Dr William Harrington for assistance with data analysis.

Disclosures: Matthew Song and Ashley M. Wilde: nothing to disclose

Results

Corresponding AuthorAshley M Wilde, PharmD, BCPS-AQ ID

Norton Healthcare

200 E. Chestnut St

Louisville, KY 40202

Telephone: 502-629-5065

Ashley.Wilde@nortonhealthcare.org

Methods

Introduction

Discussion

Objectives

• Prospective audit and feedback (PAF) is a primary tool of antimicrobial stewardship1-4

• Execution of PAF in a community health-system traditionally requires communication with providers via telephone or face-to-face communication (less common due to lack of MD-led rounds), which can be inefficient

• Additional barriers to PAF include provider non-participation• Utilization of innovative interfaces in an electronic health record

coupled with opt-out antimicrobial stewardship principles can improve the efficiency of PAF and address barriers related to provider non-participation

1. To describe our experience with conducting opt-out prospective audit and feedback utilizing electronic alerts

2. To examine effects of using electronic alerts on antimicrobial usage and incidence of healthcare facility onset Clostridium difficile infection (HO-CDI)

Figure 1. Example Electronic Recommendation Setting

• Norton Audubon Hospital

• Community hospital

• 288 licensed adult beds

• Located in Louisville, Kentucky

• EPIC® EMR

Study design

• Retrospective, observational

• IRB approved

• Study Period: Jan 6th, 2016 – March 29th, 2016

• Generated list of alert responses reviewed

• Chart reviewed when responses were “defer to another provider” or “review chart and then manage orders”

• Recommendation excluded from analysis if BPA had no response

• Chi-squared used to analyze results

Accepted, 804, 69%

Not-

accepted,

366, 31%

Figure 3. Total Recommendations

0

2

4

6

8

10

12

14

16

18

Oct – Dec 2015 Jan – March 2016 April – June 2016

HO

-CD

I/

10

,00

0 P

ati

en

t D

ays

P=0.16P=0.12

0

20

40

60

80

100

120

140

160

180

200

DO

T/

10

00

Pati

en

t D

ays Oct – Dec 2015

Jan – March 2016

April – June 2016

P<0.05

Study definitions • Accepted

• Accepted: recommendation implemented• Accepted with modifications: implementation of antibiotic

change similar but not identical to recommendation• Accepted per protocol: recommendation implemented after no

rejection for > 24 hours• Not-accepted: not accepted, accepted with modifications, or accepted

per protocol• No response: patient discharged, expired, or made comfort measures

within 36 hours of recommendation or if recommendation was removed by ASP or malfunctioning

LRTI=Lower respiratory tract infections, SSTI=skin and soft tissue infections, B&J = bone and joint infections, LUTI = lower urinary tract infections, UUTI = upper urinary tract infections, AECOPD = acute exacerbation of chronic obstructive pulmonary disease, CNS infection = central nervous system infection

• 1170 recommendations were made during 84-day pilot period demonstrating efficiency of using electronic alerts

• 804 (69%) recommendations were accepted, accepted with modification, or accepted per protocol

• 113 (14%) recommendations were accepted per protocol demonstrating usefulness of opt-out strategy

• Total usage of target antibiotics decreased during time of pilot programAccepted,

649, 81%

Accepted with

modifications, 42, 5%

Accepted Per

Protocol, 113, 14%

Figure 4. Accepted Recommendations

Electronic alert recommendations• Target antibiotics: ceftriaxone, cefepime, piperacillin/tazobactam,

ciprofloxacin, levofloxacin, ertapenem, meropenem• Daily review: ID MD + ID PharmD + ID PharmD PGY-2

Table 1. Frequency of Accepted Recommendation by TypeDiscontinue

RecommendationDe-escalation

Recommendation

Total number of electronic recommendations 414 / 631 (66%) 376/524 (72%)

Median day of antibiotic (IQR) 3 (2-5) 3 (2-4)

Median number of recommendations per patient (IQR) 1 (1-1) 1 (1-1)

Table 2. Frequency of Accepted Recommendations by Indication and AntibioticIndication Discontinuation (%) De-escalation (%)

AECOPD 24/41 (59%) 44/62 (71%)B&J 2/5 (40%) 14/33 (42%)Bloodstream 5/6 (83%) 34/47 (72%)CNS infection 1/1 (100%) 2/3 (67%)Endovascular 2/2 (100%) 3/6 (50%)Intra-abdominal infection 37/55 (67%) 48/70 (69%)LRTI 186/287 (65%) 130/190 (68%)LUTI 122/183 (67%) 53/62 (85%)SSTI 9/15 (60%) 60/92 (65%)UUTI 3/5 (60%) 14/17 (82%)Other 24/47 (51%) 15/19 (79%)> 1 indication 16/25 (64%) 47/83 (57%)

AntibioticsCefepime 49/72 (68%) 83/111 (75%)Ceftriaxone 169/254 (67%) 119/157 (76%)Ciprofloxacin 41/72 (57%) 21/30 (70%)Ertapenem 1/1 (100%) 2/2 (100%)Levofloxacin 96/148 (65%) 65/90 (72%)Meropenem 7/9 (78%) 18/31 (58%)Piperacillin/tazobactam 60/87 (69%) 100/149 (67%)Vancomycin 29/44 (66%) 108/157 (69%)Other 66/121 (55%) 104/144 (72%)> 1 antibiotic 99/162 (61%) 203/295 (69%)

Table 3. Frequency of Accepted Recommendations by Clinical Reasoning and Specialty of Responding Provider

Clinical Reasoning Discontinuation (%) De-escalation (%)Afebrile 148/278 (53%) 36/53 (68%)Asymptomatic 13/20 (65%) 0 (0%)Bacteriuria or pyuria without urinary symptoms should NOT be treated per IDSA guidelines due to risk of antibiotic resistance and C. difficile without clinical benefit

42/71 (59%) 3/3 (100%)

Completed course of therapy 160/243 (66%) 6/8 (75%)Cultures & susceptibilities 9/13 (69%) 122/162 (75%)Drug-bug mismatch 1/2 (50%) 12/14 (86%)Duplicate therapy 1/2 (50%) 28/40 (70%)Has likely alternative diagnosis 101/151 (67%) 7/7 (100%)Low risk for MDR pathogens 0 (0%) 48/69 (70%)Narrowing spectrum 7/9 (78%) 217/297 (73%)Negative cultures 38/60 (63%) 16/26 (62%)PCT < 0.05 mg/dl 75/135 (56%) 15/21 (71%)Radiographic imaging not suggestive of pneumonia 48/63 (76%) 6/8 (75%)

Viral Infection 3/8 (38%) 4/6 (67%)Vitals signs WNL 82/123 (67%) 20/29 (69%)Other 166/247(67%) 138/206 (67%)> 1 clinical reasoning 269/409 (66%) 221/309 (72%)

Provider SpecialtyFamily Medicine 31/40 (78%) 33/52 (63%)General Surgery 15/18 (83%) 15/19 (79%)Infectious Diseases 30/48 (63%) 65/99 (66%)Internal Medicine 249/391 (64%) 198/265 (75%)Nephrology 13/15 (87%) 12/12 (100%)Pulmonology 39/71 (55%) 29/48 (60%)Urology 11/16 (69%) 3/4 (75%)Other 25/31 (81%) 21/25 (84%)

Figure 2. Summary of Electronic Recommendations

References1. Barlam TF, et al. Clin Infect Dis (2016); 62 (10): e51-e77

2. Carling P, et al. Infect Control Hosp Epidemiol (2003); 24 (9):699-706

3. Diaz ranados CA. Am J infect Control (2012); 40 (6): 526-9

4. Elligsen M, et al. Infect Control Hosp Epidemiol (2012); 33(4): 354-61

Intervention Period

1289 Electronic Alerts

Discontinuation

631 electronic alerts

De-escalation

524 electronic alerts

Other

15 electronic alerts

119 excluded

Figure 5. Impact of Recommendations on HO-CDI

Figure 6. Impact of Recommendations on Antimicrobial Use

Poster Number: 768