First name
Bimal
Middle name
R
Last name
Desai

Title

Design and Implementation of a Visual Analytics Electronic Antibiogram within an Electronic Health Record System at a Tertiary Pediatric Hospital.

Year of Publication

2018

Number of Pages

37-45

Date Published

2018 Jan

ISSN Number

1869-0327

Abstract

<p><strong>BACKGROUND: </strong> Hospitals use antibiograms to guide optimal empiric antibiotic therapy, reduce inappropriate antibiotic usage, and identify areas requiring intervention by antimicrobial stewardship programs. Creating a hospital antibiogram is a time-consuming manual process that is typically performed annually.</p>

<p><strong>OBJECTIVE: </strong> We aimed to apply visual analytics software to electronic health record (EHR) data to build an automated, electronic antibiogram ("e-antibiogram") that adheres to national guidelines and contains filters for patient characteristics, thereby providing access to detailed, clinically relevant, and up-to-date antibiotic susceptibility data.</p>

<p><strong>METHODS: </strong> We used visual analytics software to develop a secure, EHR-linked, condition- and patient-specific e-antibiogram that supplies susceptibility maps for organisms and antibiotics in a comprehensive report that is updated on a monthly basis. Antimicrobial susceptibility data were grouped into nine clinical scenarios according to the specimen source, hospital unit, and infection type. We implemented the e-antibiogram within the EHR system at Children's Hospital of Philadelphia, a tertiary pediatric hospital and analyzed e-antibiogram access sessions from March 2016 to March 2017.</p>

<p><strong>RESULTS: </strong> The e-antibiogram was implemented in the EHR with over 6,000 inpatient, 4,500 outpatient, and 3,900 emergency department isolates. The e-antibiogram provides access to rolling 12-month pathogen and susceptibility data that is updated on a monthly basis. E-antibiogram access sessions increased from an average of 261 sessions per month during the first 3 months of the study to 345 sessions per month during the final 3 months.</p>

<p><strong>CONCLUSION: </strong> An e-antibiogram that was built and is updated using EHR data and adheres to national guidelines is a feasible replacement for an annual, static, manually compiled antibiogram. Future research will examine the impact of the e-antibiogram on antibiotic prescribing patterns.</p>

DOI

10.1055/s-0037-1615787

Alternate Title

Appl Clin Inform

PMID

29342478

Title

Safety of Automatic End Dates for Antimicrobial Orders to Facilitate Stewardship.

Year of Publication

2016

Number of Pages

1-5

Date Published

2016 May 13

ISSN Number

1559-6834

Abstract

<p>Following implementation of automatic end dates for antimicrobial orders to facilitate antimicrobial stewardship at a large, academic children's hospital, no differences were observed in patient mortality, length of stay, or readmission rates, even among patients with documented bacteremia. Infect Control Hosp Epidemiol 2016;1-5.</p>

DOI

10.1017/ice.2016.103

Alternate Title

Infect Control Hosp Epidemiol

PMID

27174362

Title

Optimization of drug-drug interaction alert rules in a pediatric hospital's electronic health record system using a visual analytics dashboard.

Year of Publication

2015

Number of Pages

361-9

Date Published

03/2015

ISSN Number

1527-974X

Abstract

<p><strong>OBJECTIVE: </strong>To develop and evaluate an electronic dashboard of hospital-wide electronic health record medication alerts for an alert fatigue reduction quality improvement project.</p>

<p><strong>METHODS: </strong>We used visual analytics software to develop the dashboard. We collaborated with the hospital-wide Clinical Decision Support committee to perform three interventions successively deactivating clinically irrelevant drug-drug interaction (DDI) alert rules. We analyzed the impact of the interventions on care providers' and pharmacists' alert and override rates using an interrupted time series framework with piecewise regression.</p>

<p><strong>RESULTS: </strong>We evaluated 2 391 880 medication alerts between January 31, 2011 and January 26, 2014. For pharmacists, the median alert rate prior to the first DDI deactivation was 58.74 alerts/100 orders (IQR 54.98-60.48) and 25.11 alerts/100 orders (IQR 23.45-26.57) following the three interventions (p&lt;0.001). For providers, baseline median alert rate prior to the first round of DDI deactivation was 19.73 alerts/100 orders (IQR 18.66-20.24) and 15.11 alerts/100 orders (IQR 14.44-15.49) following the three interventions (p&lt;0.001). In a subgroup analysis, we observed a decrease in pharmacists' override rates for DDI alerts that were not modified in the system from a median of 93.06 overrides/100 alerts (IQR 91.96-94.33) to 85.68 overrides/100 alerts (IQR 84.29-87.15, p&lt;0.001). The medication serious safety event rate decreased during the study period, and there were no serious safety events reported in association with the deactivated alert rules.</p>

<p><strong>CONCLUSIONS: </strong>An alert dashboard facilitated safe rapid-cycle reductions in alert burden that were temporally associated with lower pharmacist override rates in a subgroup of DDIs not directly affected by the interventions; meanwhile, the pharmacists' frequency of selecting the 'cancel' option increased. We hypothesize that reducing the alert burden enabled pharmacists to devote more attention to clinically relevant alerts.</p>

DOI

10.1136/amiajnl-2013-002538

Alternate Title

J Am Med Inform Assoc

PMID

25318641

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