scholarly journals A Pediatric Intensive Care Unit Bedside Computer Clinical Decision Support Protocol for Hyperglycemia Is Feasible, Safe and Offers Advantages

2017 ◽  
Vol 19 (3) ◽  
pp. 188-193 ◽  
Author(s):  
Eliotte L. Hirshberg ◽  
Michael J. Lanspa ◽  
Emily L. Wilson ◽  
Katherine A. Sward ◽  
Al Jephson ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Decision Support ◽  
Pediatric Intensive Care Unit ◽  
Clinical Decision Support ◽  
Pediatric Intensive Care ◽  
Clinical Decision

scholarly journals 1956. Reduction in Endotracheal Aspirate Cultures after Implementation of a Diagnostic Stewardship Intervention in a Pediatric Intensive Care Unit

2019 ◽  
Vol 6 (Supplement_2) ◽  
pp. S61-S61
Author(s):  
Anna Sick-Samuels ◽  
Jules Bergmann ◽  
Matthew Linz ◽  
James Fackler ◽  
Sean Berenholtz ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Decision Support ◽  
Pediatric Intensive Care Unit ◽  
Clinical Decision Support ◽  
Pediatric Intensive Care ◽  
Clinical Decision ◽  
Antibiotic Prescribing ◽  
Intervention Period ◽  
Endotracheal Aspirate

Abstract Background Clinicians obtain endotracheal aspirate (ETA) cultures from mechanically ventilated patients in the pediatric intensive care unit (PICU) for the evaluation of ventilator-associated infection (i.e., tracheitis or pneumonia). Positive cultures prompt clinicians to treat with antibiotics even though ETA cultures cannot distinguish bacterial colonization from infection. We undertook a quality improvement initiative to standardize the use of endotracheal cultures in the evaluation of ventilator-associated infections among hospitalized children. Methods A multidisciplinary team developed a clinical decision support algorithm to guide when to obtain ETA cultures from patients admitted to the PICU and ventilated for >1 day. We disseminated the algorithm to all bedside providers in the PICU in April 2018 and compared the rate of cultures one year before and after the intervention using Poisson regression and a quasi-experimental interrupted time-series models. Charge savings were estimated based on $220 average charge for one ETA culture. Results In the pre-intervention period, there was an average of 46 ETA cultures per month, a total of 557 cultures over 5,092 ventilator-days; after introduction of the algorithm, there were 19 cultures obtained per month, a total of 231 cultures over 3,554 ventilator-days (incident rate 10.9 vs. 6.5 per 100 ventilator-days, Figure 1). There was a 43% decrease in the monthly rate of cultures (IRR 0.57, 95% CI 0.50–0.67, P < 0.001). The ITSA revealed a pre-existing 2% decline in the monthly culture rate (IRR 0.98, 95% CI 0.97–1.00, P = 0.01), an immediate 44% drop (IRR 0.56, 95% CI 0.45–0.69, P = 0.02) and a stable rate in the post-intervention period (IRR 1.03, 95% CI 0.99–1.07, P = 0.09). The intervention led to an estimated $6000 in monthly charge savings. Conclusion Introduction of a clinical decision support algorithm to standardize the obtainment of ETA cultures from ventilated children was associated with a significant decline in the rate of ETA cultures. Additional investigation will assess the impact on balancing measures and secondary outcomes including mortality, duration of ventilation, duration of admission, readmissions, and antibiotic prescribing. Disclosures All Authors: No reported Disclosures.

Physicians’ responses to clinical decision support on an intensive care unit—Comparison of four different alerting methods

2013 ◽  
Vol 59 (1) ◽  
pp. 33-38 ◽  
Author(s):  
Anne-Marie J. Scheepers-Hoeks ◽  
Rene J. Grouls ◽  
Cees Neef ◽  
Eric W. Ackerman ◽  
Erik H. Korsten
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Decision Support ◽  
Clinical Decision Support ◽  
Clinical Decision

scholarly journals Prospective evaluation of medication-related clinical decision support over-rides in the intensive care unit

2018 ◽  
Vol 27 (9) ◽  
pp. 718-724 ◽  
Author(s):  
Adrian Wong ◽  
Mary G Amato ◽  
Diane L Seger ◽  
Christine Rehr ◽  
Adam Wright ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Decision Support ◽  
Clinical Decision Support ◽  
Adverse Drug Events ◽  
Clinical Decision ◽  
Limited Data ◽  
Exact Test ◽  
Increased Risk ◽  
Adjusted Logistic Regression

BackgroundClinical decision support (CDS) displayed in electronic health records has been found to reduce the incidence of medication errors and adverse drug events (ADE). Recent data suggested that medication-related CDS alerts were frequently over-ridden, often inappropriately. Patients in the intensive care unit (ICU) are at an increased risk of ADEs; however, limited data exist on the benefits of CDS in the ICU. This study aims to evaluate potential harm associated with medication-related CDS over-rides in the ICU.MethodsThis was a prospective observational study of adults admitted to any of six ICUs between July 2016 and April 2017 at our institution. Patients with provider-overridden CDS for dose (orders for scheduled frequency and not pro re nata), drug allergy, drug–drug interaction, geriatric and renal alerts (contraindicated medications for renal function or renal dosing) were included. The primary outcome was the appropriateness of over-rides, which were evaluated by two independent reviewers. Secondary outcomes included incidence of ADEs following alert over-ride and risk of ADEs based on over-ride appropriateness.ResultsA total of 2448 over-ridden alerts from 712 unique patient encounters met inclusion criteria. The overall appropriateness rate for over-rides was 81.6% and varied by alert type. More ADEs (potential and definite) were identified following inappropriate over-rides compared with appropriate over-rides (16.5 vs 2.74 per 100 over-ridden alerts, Fisher’s exact test P<0.001). An adjusted logistic regression model showed that inappropriate over-rides were associated with an increased risk of ADEs (OR 6.14, 95% CI 4.63 to 7.71, P<0.001).ConclusionsApproximately four of five identified CDS over-rides were appropriately over-ridden, with the rate varying by alert type. However, inappropriate over-rides were six times as likely to be associated with potential and definite ADEs, compared with appropriate over-rides. Further efforts should be targeted at improving the positive predictive value of CDS such as by suppressing alerts that are appropriately over-ridden.

scholarly journals Comparison of Overridden Medication-related Clinical Decision Support in the Intensive Care Unit between a Commercial System and a Legacy System

2017 ◽  
Vol 08 (03) ◽  
pp. 866-879 ◽  
Author(s):  
Adrian Wong ◽  
Adam Wright ◽  
Diane Seger ◽  
Mary Amato ◽  
Julie Fiskio ◽  
...  
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Decision Support ◽  
Clinical Decision Support ◽  
Current System ◽  
Clinical Decision ◽  
Legacy System ◽  
Commercial System ◽  
Increased Risk ◽  
Two Systems

Summary Background: Electronic health records (EHRs) with clinical decision support (CDS) have shown to be effective at improving patient safety. Despite this, alerts delivered as part of CDS are overridden frequently, which is of concern in the critical care population as this group may have an increased risk of harm. Our organization recently transitioned from an internally-developed EHR to a commercial system. Data comparing various EHR systems, especially after transitions between EHRs, are needed to identify areas for improvement. Objectives: To compare the two systems and identify areas for potential improvement with the new commercial system at a single institution. Methods: Overridden medication-related CDS alerts were included from October to December of the systems’ respective years (legacy, 2011; commercial, 2015), restricted to three intensive care units. The two systems were compared with regards to CDS presentation and override rates for four types of CDS: drug-allergy, drug-drug interaction (DDI), geriatric and renal alerts. A post hoc analysis to evaluate for adverse drug events (ADEs) potentially resulting from overridden alerts was performed for ‘contraindicated’ DDIs via chart review. Results: There was a significant increase in provider exposure to alerts and alert overrides in the commercial system (commercial: n=5,535; legacy: n=1,030). Rates of overrides were higher for the allergy and DDI alerts (p<0.001) in the commercial system. Geriatric and renal alerts were significantly different in incidence and presentation between the two systems. No ADEs were identified in an analysis of 43 overridden contraindicated DDI alerts. Conclusions: The vendor system had much higher rates of both alerts and overrides, although we did not find evidence of harm in a review of DDIs which were overridden. We propose recommendations for improving our current system which may be helpful to other similar institutions; improving both alert presentation and the underlying knowledge base appear important.Citation: Wong A, Wright A, Seger DL, Amato MG, Fiskio JM, Bates D. Comparison of Overridden Medication-related Clinical Decision Support in the Intensive Care Unit between a Commercial System and a Legacy System. Appl Clin Inform 2017; 8: 866–879 https://doi.org/10.4338/ACI-2017-04-RA-0059

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