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?

Eliminating inappropriate antibiotic use in pediatric lower respiratory tract infections (LRTI) is the central focus of this research. LRTIs (pneumonia, bronchiolitis, and infection-related exacerbations of asthma) account for nearly one-third of all emergency department (ED) visits and 40% of all infection-related hospitalizations in US children. LRTIs also account for more antibiotic use in children's hospitals than any other condition, despite most LRTIs being viral in nature. Inappropriate antibiotics are associated with substantial adverse effects. Accordingly, national guidelines strongly discourage routine antibiotic use for bronchiolitis and acute asthma and argue for significantly reducing antibiotic exposure (initiation, spectrum, and duration) in pneumonia. To address the problem of inappropriate antibiotic use, hospital-based antimicrobial stewardship programs (ASPs) are now common nationwide, and these programs have demonstrated effectiveness in some hospital settings. Unfortunately, traditional ASP approaches do not translate well to the fast-paced and unpredictable ED environment, and hospital-based ASP resources are finite and not always immediately available. Clinical decision support (CDS) embedded within the electronic health record (EHR) is a strategy that could address the ED antibiotic stewardship gap. Informed by a deep understanding of the key facilitators and barriers to using CDS to support appropriate antibiotic use in ED and hospital settings, the investigators have developed two stewardship-focused CDS interventions for pediatric LRTI. The overarching goal of this research is to rigorously evaluate the implementation and effectiveness of these CDS tools, alone and in combination, against usual care only in a pragmatic randomized clinical trial at 3 U.S. children's hospitals.

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.

Is the clinical decision support system safe for use in children?

Clinical decision support systems (CDSS) have been studied for their potential to reduce medical errors, but improper design can introduce new errors. Usability issues in CDSS for conditions like pneumonia have been noted, which could lead to adverse medical events if not properly addressed. ^{1 2 3 4 5}

How is the ED Clinical Decision Support (CDS-ED) treatment for lower respiratory infections in children different from other treatments?

The ED Clinical Decision Support (CDS-ED) treatment is unique because it uses technology to guide healthcare providers in making better decisions about antibiotic use, aiming to reduce unnecessary prescriptions and improve adherence to guidelines, which is not a standard approach in treating lower respiratory infections in children. ^{1 3 6 7 8}

What data supports the effectiveness of the treatment ED Clinical Decision Support (CDS-ED) and Transitions Clinical Decision Support (CDS-Tr) 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 guideline-adherent antibiotic prescribing for pediatric infections, suggesting potential benefits for managing lower respiratory infections in children. ^{1 2 3 6 9}

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 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]

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 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 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]

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]

Citations

1. Germany pubmed.ncbi.nlm.nih.gov

Evaluation of an Antimicrobial Stewardship Decision Support for Pediatric Infections. [2023]

2. Germany pubmed.ncbi.nlm.nih.gov

Examining Workflow in a Pediatric Emergency Department to Develop a Clinical Decision Support for an Antimicrobial Stewardship Program. [2019]

3. Canada pubmed.ncbi.nlm.nih.gov

Clinical Decision Support to Reduce Opioid Prescriptions for Dental Extractions using SMART on FHIR: Implementation Report. [2023]

4. United States pubmed.ncbi.nlm.nih.gov

Antibiotic clinical decision support for pneumonia in the ED: A randomized trial. [2023]

5. United States pubmed.ncbi.nlm.nih.gov

Impact of Clinical Decision Support on Antibiotic Prescribing for Acute Respiratory Infections: a Cluster Randomized Implementation Trial. [2021]

6. United States pubmed.ncbi.nlm.nih.gov

How usability of a web-based clinical decision support system has the potential to contribute to adverse medical events. [2022]

7. Canada pubmed.ncbi.nlm.nih.gov

Pediatricians' Understanding and Experiences of an Electronic Clinical-Decision-Support-System. [2022]

8. United States pubmed.ncbi.nlm.nih.gov

Impact of a computerized template on antibiotic prescribing for acute respiratory infections in children and adolescents. [2018]

9. United States pubmed.ncbi.nlm.nih.gov

Clinical decision support systems and infection prevention: to know is not enough. [2015]