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The Value of Electronically Extracted Data for Auditing Outpatient Antimicrobial Prescribing

Published online by Cambridge University Press:  28 December 2017

Daniel J. Livorsi ,
Carrie M. Linn ,
Bruce Alexander ,
Brett H. Heintz ,
Traviss A. Tubbs  and
Eli N. Perencevich
Daniel J. Livorsi*
Affiliation:
Iowa City Veterans Affairs Health Care System, Iowa City, Iowa Division of Infectious Diseases, Department of Internal Medicine, University of Iowa Carver College of Medicine, Iowa City, Iowa
Carrie M. Linn
Affiliation:
College of Pharmacy, University of Iowa, Iowa City, Iowa
Bruce Alexander
Affiliation:
Iowa City Veterans Affairs Health Care System, Iowa City, Iowa
Brett H. Heintz
Affiliation:
Iowa City Veterans Affairs Health Care System, Iowa City, Iowa College of Pharmacy, University of Iowa, Iowa City, Iowa
Traviss A. Tubbs
Affiliation:
Iowa City Veterans Affairs Health Care System, Iowa City, Iowa
Eli N. Perencevich
Affiliation:
Iowa City Veterans Affairs Health Care System, Iowa City, Iowa Division of General Internal Medicine, Department of Internal Medicine, University of Iowa Carver College of Medicine, Iowa City, Iowa
*
Address correspondence to Daniel Livorsi, MD, MSc, Assistant Professor, Division of Infectious Diseases, University of Iowa Carver College of Medicine, Iowa VA Health Care System, 601 Highway 6 West, Iowa City, IA 52246 (daniel-livorsi@uiowa.edu).
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Abstract

OBJECTIVE

The optimal approach to auditing outpatient antimicrobial prescribing has not been established. We assessed how different types of electronic data—including prescriptions, patient-visits, and International Classification of Disease, Tenth Revision (ICD-10) codes—could inform automated antimicrobial audits.

DESIGN

Outpatient visits during 2016 were retrospectively reviewed, including chart abstraction, if an antimicrobial was prescribed (cohort 1) or if the visit was associated with an infection-related ICD-10 code (cohort 2). Findings from cohorts 1 and 2 were compared.

SETTING

Primary care clinics and the emergency department (ED) at the Iowa City Veterans Affairs Medical Center.

RESULTS

In cohort 1, we reviewed 2,353 antimicrobial prescriptions across 52 providers. ICD-10 codes had limited sensitivity and positive predictive value (PPV) for validated cases of cystitis and pneumonia (sensitivity, 65.8%, 56.3%, respectively; PPV, 74.4%, 52.5%, respectively). The volume-adjusted antimicrobial prescribing rate was 13.6 per 100 ED visits and 7.5 per 100 primary care visits. In cohort 2, antimicrobials were not indicated in 474 of 851 visits (55.7%). The antimicrobial overtreatment rate was 48.8% for the ED and 59.7% for primary care. At the level of the individual prescriber, there was a positive correlation between a provider’s volume-adjusted antimicrobial prescribing rate and the individualized rates of overtreatment in both the ED (r=0.72; P<.01) and the primary care setting (r=0.82; P=0.03).

CONCLUSIONS

In this single-center study, ICD-10 codes had limited sensitivity and PPV for 2 infections that typically require antimicrobials. Electronically extracted data on a provider’s rate of volume-adjusted antimicrobial prescribing correlated with the frequency at which unnecessary antimicrobials were prescribed, but this may have been driven by outlier prescribers.

Infect Control Hosp Epidemiol 2018;39:64–70

Type
Original Articles
Information
Infection Control & Hospital Epidemiology , Volume 39 , Issue 1 , January 2018 , pp. 64 - 70
Copyright
© 2017 by The Society for Healthcare Epidemiology of America. All rights reserved 

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