Decision Support for Lower Respiratory Infections in Children

(ROADS Trial)

Recruiting at 2 trial locations

Overseen By Justine Stassun, MS

Age: < 18

Sex: Any

Trial Phase: Academic

Sponsor: Vanderbilt University Medical Center

No Placebo Group All trial participants will receive the active study treatment (no placebo)

Compensation: Varies

Number of Visits: Unknown

Duration: 10 days

2800 Participants Needed

What You Need to Know Before You Apply

What is the purpose of this trial?

This trial focuses on reducing inappropriate antibiotic use in children with lower respiratory tract infections (LRTI) such as pneumonia or bronchiolitis. The study tests two new tools, ED Clinical Decision Support (CDS-ED) and Transitions Clinical Decision Support (CDS-Tr), designed to assist doctors in emergency departments and hospitals in making informed decisions about antibiotic use. Researchers compare these tools against usual care to evaluate their effectiveness. Children visiting the emergency room or admitted to the hospital with symptoms like a cough or shortness of breath may be suitable candidates for this trial. As an unphased trial, this study provides a unique opportunity to contribute to important research that could enhance antibiotic use in children.

Will I have to stop taking my current medications?

The trial information does not specify whether you need to stop taking your current medications. It focuses on reducing inappropriate antibiotic use for certain infections in children.

What prior data suggests that these clinical decision support tools are safe for use in pediatric emergency and inpatient settings?

Research has shown that clinical decision support (CDS) systems can help reduce unnecessary antibiotic use for respiratory infections. This is important because antibiotics can cause side effects, especially when not needed. CDS technology is generally well-accepted because it aids doctors in making better decisions rather than introducing a new drug or treatment.

Studies on similar CDS tools have demonstrated their effectiveness in hospitals. They help medical staff adhere more closely to guidelines, resulting in fewer unnecessary antibiotics. This enhances safety by reducing the risk of antibiotic side effects. While no direct human trial data exists for this specific CDS tool, similar tools have proven to be safe. ^{1 2 3 4 5}

Why are researchers excited about this trial?

Researchers are excited about this trial because it explores the potential of clinical decision support tools to improve care for children with lower respiratory infections. Unlike standard treatments that rely solely on the clinician's judgment and experience, these tools provide real-time, evidence-based guidance tailored to specific clinical settings. The ED Clinical Decision Support (CDS-ED) and Transitions Clinical Decision Support (CDS-Tr) tools aim to enhance decision-making in emergency and inpatient settings, respectively. By integrating these tools, the study hopes to optimize treatment plans, improve patient outcomes, and potentially streamline healthcare processes.

What evidence suggests that these clinical decision support tools are effective for reducing inappropriate antibiotic use in pediatric lower respiratory infections?

Research has shown that clinical decision support (CDS) systems can significantly reduce unnecessary antibiotic prescriptions for respiratory infections. One study suggested that these tools help doctors use antibiotics more appropriately for respiratory tract infections. In this trial, emergency room doctors will use the CDS-ED tool to improve antibiotic decision-making. Meanwhile, hospital doctors will use the CDS-Tr tool to ensure treatments align with the latest guidelines. Both tools, part of separate treatment arms in this trial, aim to address the issue of overprescribing antibiotics, which can lead to unwanted side effects and antibiotic resistance. These interventions have shown promise in aligning treatments with recommended practices. ^{1 3 6 7 8}

Who Is on the Research Team?

Derek J Williams, MD, MPH

Principal Investigator

Vanderbilt University Medical Center

Are You a Good Fit for This Trial?

This trial is for children visiting the emergency department (ED) with lower respiratory tract infections like pneumonia, bronchiolitis, or asthma-related infections. It aims to reduce unnecessary antibiotic use in these patients.

Inclusion Criteria

I have been to the emergency department or admitted to the hospital.

My electronic health records show signs of a lung infection based on my symptoms and nurse's notes.

Exclusion Criteria

Not applicable.

Timeline for a Trial Participant

Screening

Participants are screened for eligibility to participate in the trial

2-4 weeks

Treatment

Participants receive clinical decision support interventions in the ED and hospital settings to reduce inappropriate antibiotic use

10 days

Ongoing monitoring during hospital stay

Follow-up

Participants are monitored for safety and effectiveness after treatment, including antibiotic exposure and clinical outcomes

42 days

Extension

Long-term monitoring of antibiotic use and clinical outcomes

Up to 42 days post-discharge

What Are the Treatments Tested in This Trial?

Interventions

• ED Clinical Decision Support (CDS-ED)
• Transitions Clinical Decision Support (CDS-Tr)

Trial Overview

The study tests two electronic Clinical Decision Support systems: one used in the ED (CDS-ED), and another during hospital transitions (CDS-Tr). The goal is to see if they help doctors prescribe antibiotics appropriately compared to usual care.

How Is the Trial Designed?

Group I: CDS-Tr Experimental Treatment 1 Intervention

The Transitions clinical decision support tool will be offered to inpatient/ICU providers in these enrolled encounters.

Group II: CDS-ED Experimental Treatment 1 Intervention

The ED clinical decision support tool will be offered to emergency department providers in these enrolled encounters.

Group III: Usual Care: Emergency Department Active Control 1 Intervention

No experimental decision support will be provided to the emergency medicine providers in encounters randomized to the control arm. All patients will receive usual care and treatment will not be restricted or altered in any way by the study.

Group IV: Usual Care: Inpatient Active Control 1 Intervention

No experimental decision support will be provided to the inpatient/ICU providers in encounters randomized to the control arm. All patients will receive usual care and treatment will not be restricted or altered in any way by the study.

Who Is Running the Clinical Trial?

Vanderbilt University Medical Center

Lead Sponsor

Trials

922

Recruited

939,000+

Agency for Healthcare Research and Quality (AHRQ)

Collaborator

Trials

415

Recruited

6,777,000+

University of California, San Francisco

Collaborator

Trials

2,636

Recruited

19,080,000+

Published Research Related to This Trial

A cluster randomized clinical trial involving 33 primary care practices and over 100,000 patient visits found that an integrated clinical prediction rule (iCPR) tool did not significantly reduce antibiotic prescribing rates for acute respiratory infections, with 35% of intervention visits and 36% of control visits resulting in prescriptions.

The study highlights the challenges of implementing clinical decision support tools in diverse primary care settings, as the iCPR tool was used in only 6.9% of eligible visits and did not lead to changes in the rates of related diagnostic tests either.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Impact of Clinical Decision Support on Antibiotic Prescribing for Acute Respiratory Infections: a Cluster Randomized Implementation Trial. Mann, D., Hess, R., McGinn, T., et al.[2021]

A study observing 23 healthcare providers in a children's emergency department over 90 hours identified 64 different activities related to antibiotic prescribing, highlighting the need for clinical decision support (CDS) systems to align with the varied workflows of different provider roles.

Clinicians made treatment decisions at key points in patient care, such as after patient examinations or discussions with specialists, indicating that CDS systems should be designed to assist at these specific decision-making moments to enhance antimicrobial stewardship programs.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Examining Workflow in a Pediatric Emergency Department to Develop a Clinical Decision Support for an Antimicrobial Stewardship Program. Ozkaynak, M., Wu, DTY., Hannah, K., et al.[2019]

A clinical decision support (CDS) system was developed to provide personalized pain management recommendations for dentists, aiming to reduce opioid prescriptions after dental extractions, and was implemented in a study involving patients from February 2020 to May 2021.

The CDS tool, which integrates with electronic health records and utilizes patient-specific data, showed variable provider engagement, with up to 87.4% of providers using it during extraction encounters, indicating its potential for improving pain management practices in dental settings.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Clinical Decision Support to Reduce Opioid Prescriptions for Dental Extractions using SMART on FHIR: Implementation Report. Rindal, DB., Pasumarthi, DP., Thirumalai, V., et al.[2023]

In a study involving 1027 pediatric patients with pneumonia, the use of electronic health record-based clinical decision support (CDS) did not significantly improve overall guideline-concordant antibiotic prescribing compared to usual care, with rates of 51.7% for CDS and 53.3% for usual care.

However, CDS was more effective for patients discharged from the emergency department, achieving 74.9% guideline-concordant prescribing compared to 66.0% for usual care, and it also resulted in a shorter mean time to first antibiotic administration (3.0 hours vs. 3.4 hours).

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Antibiotic clinical decision support for pneumonia in the ED: A randomized trial. Williams, DJ., Martin, JM., Nian, H., et al.[2023]

A newly developed automated clinical decision support (CDS) system significantly improved guideline-adherent antibiotic prescribing for pediatric community-acquired pneumonia (CAP) by 31% compared to standard order sets, based on usability testing with 21 emergency department providers.

Providers preferred the CDS system for its better explanations of antibiotic choices and additional resources, indicating enhanced usability and potential for reduced workload, although the latter showed a non-significant trend.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Evaluation of an Antimicrobial Stewardship Decision Support for Pediatric Infections. McGonagle, EA., Karavite, DJ., Grundmeier, RW., et al.[2023]

The implementation of the acute respiratory illness interactive template (ARI-IT) within electronic health records led to a significant reduction in antibiotic prescriptions for pediatric acute respiratory infections, decreasing from 39.9% to 31.7%.

Despite the positive impact on reducing antibiotic use, the overall low adoption of the ARI-IT limited its effectiveness as an intervention in improving prescribing practices.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Impact of a computerized template on antibiotic prescribing for acute respiratory infections in children and adolescents. Bourgeois, FC., Linder, J., Johnson, SA., et al.[2018]

Clinical decision support (CDS) systems are valuable technologies that help healthcare providers follow best practices and protocols to enhance patient care, particularly in infection prevention and antimicrobial stewardship.

Despite their potential, the use of CDS systems for infection prevention is not widespread, and the article highlights successful examples and the infrastructure needed to develop effective CDS tools for improving infection control initiatives.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Clinical decision support systems and infection prevention: to know is not enough. Wright, MO., Robicsek, A.[2015]

A study analyzing the usability of clinical decision support systems (CDSS) for community-acquired pneumonia and neutropenic fever found 422 recorded events, including 3 mistakes that could have been life-threatening, highlighting the critical need for careful design and evaluation of these systems.

Incorporating usability engineering principles early in the design of CDSS can help identify interface issues that may lead to adverse medical events, emphasizing the importance of user-friendly software in improving patient safety.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

How usability of a web-based clinical decision support system has the potential to contribute to adverse medical events. Graham, TA., Kushniruk, AW., Bullard, MJ., et al.[2022]

The implementation of a Clinical Decision Support System (CDSS) with integrated Dose Range Check and Weight Based Dose Calculation at a pediatric hospital in Sweden was developed to reduce dosing errors, highlighting the importance of such systems in pediatric medication safety.

Interviews with 17 pediatricians revealed that while the CDSS is beneficial in preventing medication errors, there is a need for ongoing development and adaptation based on the practical experiences and contextual needs of healthcare providers.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Pediatricians' Understanding and Experiences of an Electronic Clinical-Decision-Support-System. Nydert, P., Vég, A., Bastholm-Rahmner, P., et al.[2022]

Citations

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withpower.com

withpower.com/trial/decision-support-for-lower-respiratory-infections-in-children-ae881

Decision Support for Lower Respiratory Infections in Children

Research shows that clinical decision support (CDS) systems can help reduce unnecessary antibiotic prescribing for acute respiratory infections and improve ...

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clinicaltrials.gov

clinicaltrials.gov/study/NCT06788093

Reducing Overuse of Antibiotics with Decision Support

Eliminating inappropriate antibiotic use in pediatric lower respiratory tract infections (LRTI) is the central focus of this research.

3.

ajtmh.org

ajtmh.org/view/journals/tpmd/112/5/article-p1168.xml

Electronic Clinical Decision Support Tools to Manage ...

Lower respiratory tract infections were the leading cause of death among children under 5 years and the fifth cause of death among adults over 69 years.

4.

pubmed.ncbi.nlm.nih.gov

pubmed.ncbi.nlm.nih.gov/33075037/

Cost Study of a Cluster Randomized Trial on a Clinical ...

This study aims to evaluate the impact of the decision rule on healthcare and societal costs, and to describe costs of children with suspected lower respiratory ...

5.

frontiersin.org

frontiersin.org/journals/pharmacology/articles/10.3389/fphar.2023.1253520/full

Effectiveness of decision support tools on reducing ...

This study suggests that CDSs effectively reduce inappropriate antibiotic use for RTIs among physicians.

6.

pmc.ncbi.nlm.nih.gov

pmc.ncbi.nlm.nih.gov/articles/PMC10247532/

Antibiotic Clinical Decision Support for Pneumonia in the ED

EHR-based CDS has proven effective, although the magnitude of benefit varies widely. Few evaluations of CDS have been conducted in the pediatric ED.

7.

publications.aap.org

publications.aap.org/pediatrics/article/156/1/e2024069478/202108/Clinical-Decision-Support-for-Septic-Shock-in-the

Clinical Decision Support for Septic Shock in the ...

The CDS used models identifying children who did not yet have shock but were predicted to be at high risk based on electronic health record data ...

8.

pmc.ncbi.nlm.nih.gov

pmc.ncbi.nlm.nih.gov/articles/PMC11374114/

Prognostic Clinical Decision Support for Pneumonia in the ...

Hospitalizations rates for childhood pneumonia vary widely. Risk-based clinical decision support (CDS) interventions may reduce unwarranted variation.