OBJECTIVE: State agencies have developed reporting systems of safety events that include events related to health information technology (HIT). These data come from hospital reporting systems where staff submit safety reports and nurses, in the role of safety managers, review, and code events. Safety managers may have varying degrees of experience with identifying events related to HIT. Our objective was to review events potentially involving HIT and compare those with what was reported to the state.

METHODS: We performed a structured review of 1 year of safety events from an academic pediatric healthcare system. We reviewed the free-text description of each event and applied a classification scheme derived from the AHRQ Health IT Hazard Manager and compared the results with events reported to the state as involving HIT.

RESULTS: Of 33,218 safety events for a 1-year period, 1247 included key words related to HIT and/or were indicated by safety managers as involving HIT. Of the 1247 events, the structured review identified 769 as involving HIT. In comparison, safety managers only identified 194 of the 769 events (25%) as involving HIT. Most events, 353 (46%), not identified by safety managers were documentation issues. Of the 1247 events, the structured review identified 478 as not involving HIT while safety managers identified and reported 81 of these 478 events (17%) as involving HIT.

CONCLUSIONS: The current process of reporting safety events lacks standardization in identifying health technology contributions to safety events, which may minimize the effectiveness of safety initiatives.

<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>

<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>

<p><strong>BACKGROUND: </strong>When initiated within 48 hours of the onset of symptoms, oseltamivir has been shown to reduce severity and length of influenza illness. Few studies have evaluated the use of oseltamivir in patients hospitalized with influenza.</p>

<p><strong>OBJECTIVE: </strong>To describe the prescribing practices for oseltamivir in children hospitalized with influenza and to evaluate a mechanism to improve the rate of appropriate prescription.</p>

<p><strong>DESIGN, SETTING, PATIENTS: </strong>Retrospective cohort study of 929 patients aged 21 years or younger hospitalized with community-acquired laboratory-confirmed influenza (CA-LCI) during 5 consecutive seasons (2000-2005). We examined oseltamivir eligibility, which included patients 1 year of age or older with an influenza test result available within 48 hours of symptom onset. During the 2005-2006 season, an observational trial of an electronic reminder was conducted to improve the frequency of oseltamivir prescription.</p>

<p><strong>MEASUREMENTS: </strong>Oseltamivir prescription.</p>

<p><strong>RESULTS: </strong>Of 305 patients (32.8%) eligible for treatment with oseltamivir, 49 (16.1% of those eligible) were prescribed oseltamivir during hospitalization. Prescription rates for indications consistent with the US Food and Drug Administration (FDA) approval ("on label") increased from 0% to 37.2% over 5 seasons (P &lt; 0.0001). Prescriptions outside this recommendation ("off label") also increased over 5 seasons (P &lt; 0.0001). Twenty-nine (5%) of 624 patients were treated with oseltamivir off label; 11 were less than 1 year of age. Initiation of a reminder had no impact on prescription (P &gt; 0.05).</p>

<p><strong>CONCLUSIONS: </strong>Oseltamivir was used infrequently for children hospitalized with influenza. In addition, use inconsistent with the FDA label of oseltamivir occurs. Mechanisms are needed to improve appropriate prescription of oseltamivir.</p>

<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>