Clinical Decision Support for Respiratory Infections

Not currently recruiting at 3 trial locations
ST
Overseen BySumaiya Tasneem
Age: 18+
Sex: Any
Trial Phase: Academic
Sponsor: NYU Langone Health
No Placebo GroupAll trial participants will receive the active study treatment (no placebo)

What You Need to Know Before You Apply

What is the purpose of this trial?

This trial tests a new tool, the iCPR system, to assist nurses in deciding when to prescribe antibiotics for acute respiratory infections, such as coughs and sore throats. The goal is to ensure antibiotics are used only when necessary, based on the tool's guidance. The trial involves two groups: one using the new tool and one continuing with standard care. Nurses who regularly see patients and use electronic health records can participate. Patients eligible for this trial are those visiting participating clinics with a cough or sore throat complaint. As an unphased trial, this study allows patients to contribute to innovative healthcare solutions that could improve antibiotic use.

Do I need to stop my current medications to join the trial?

The trial information does not specify whether you need to stop taking your current medications. It focuses on evaluating a tool for prescribing antibiotics for respiratory infections.

What prior data suggests that this clinical prediction tool is safe for use in guiding antibiotic prescriptions?

Research has shown that the iCPR system, a decision-support tool for doctors, has been tested in regular healthcare settings. Although it did not significantly reduce antibiotic prescriptions for upper respiratory infections, studies found no evidence of harm or side effects from its use. Thus, the iCPR system is considered safe and well-tolerated for guiding treatment decisions for acute respiratory infections (ARIs).12345

Why are researchers excited about this trial?

Researchers are excited about the iCPR system because it's designed to enhance clinical decision-making for respiratory infections. Unlike standard care, which often relies on generalized protocols, the iCPR system provides personalized, real-time support by guiding healthcare providers through specific workflows and risk assessments. This approach allows for more tailored care, potentially improving patient outcomes and treatment efficiency. The combination of online and in-person training ensures that clinic personnel are well-equipped to use the system effectively, which could lead to better management of respiratory infections.

What evidence suggests that the iCPR system is effective for guiding antibiotic prescriptions for acute respiratory infections?

Research has shown that tools like the iCPR system, which participants in this trial may receive, can assist doctors and nurses in making better decisions about antibiotic use for respiratory infections. These tools guide healthcare providers on when to prescribe antibiotics. However, one study found that the iCPR tool did not significantly reduce antibiotic prescriptions in primary care settings. While these systems have the potential to aid decision-making, their actual impact on changing prescription habits can vary. This underscores the need for further research to determine how best to use these tools in different healthcare settings.36789

Who Is on the Research Team?

Devin Mann, MD | NYU Langone Health

Devin Mann, MD

Principal Investigator

NYU Langone Health

Are You a Good Fit for This Trial?

This trial is for patients aged 3-70 with sore throat and 18-70 with cough, seen at participating clinics. Nurses prescribing treatment must work at least half-time, be licensed, use the clinic's EHR system regularly, and see a sufficient number of patients to maintain skills.

Inclusion Criteria

I am between 3-70 years old with a sore throat, or 18-70 with a cough.
I visited a clinic for a cough or sore throat.
My clinic employs at least one full-time registered nurse.
See 4 more

Exclusion Criteria

I do not have chronic lung disease or a weakened immune system.
I can use English software for self-monitoring without issues.
I am unable or unwilling to give my consent for participation.
See 2 more

Timeline for a Trial Participant

Screening

Participants are screened for eligibility to participate in the trial

2-4 weeks

Training and Implementation

Clinic personnel receive online and in-person training on the iCPR tool, followed by implementation of the intervention

4-6 weeks
1 in-person training session, 1 follow-up training session

Evaluation

Evaluation of the iCPR tool's effectiveness in reducing antibiotic prescriptions and its adoption by nurses

6 months

Follow-up

Participants are monitored for safety and effectiveness after treatment

12 months

What Are the Treatments Tested in This Trial?

Interventions

  • iCPR system
Trial Overview The study tests an integrated clinical prediction tool in electronic health records (EHR) that helps nurses decide when antibiotics are needed for acute respiratory infections. It aims to ensure prescriptions are evidence-based.
How Is the Trial Designed?
2Treatment groups
Experimental Treatment
Active Control
Group I: iCPR groupExperimental Treatment1 Intervention
Group II: Control no intervention groupActive Control1 Intervention

Find a Clinic Near You

Who Is Running the Clinical Trial?

NYU Langone Health

Lead Sponsor

Trials
1,431
Recruited
838,000+

National Institute of Allergy and Infectious Diseases (NIAID)

Collaborator

Trials
3,361
Recruited
5,516,000+

Published Research Related to This Trial

The TREAT decision support system significantly improved the rate of appropriate antibiotic treatment in patients with suspected bacterial infections, achieving 70% compliance compared to 57% by physicians, while also using less broad-spectrum antibiotics and reducing costs by half.
In a randomized trial involving 2326 patients, intervention wards using TREAT had a higher rate of appropriate treatment (73% vs. 64%) and showed significant reductions in hospital stay length and total antibiotic costs, highlighting its efficacy in optimizing antibiotic use and minimizing resistance.
Improving empirical antibiotic treatment using TREAT, a computerized decision support system: cluster randomized trial.Paul, M., Andreassen, S., Tacconelli, E., et al.[2022]

Citations

1.pubmed.ncbi.nlm.nih.govpubmed.ncbi.nlm.nih.gov/32875505/
Impact of Clinical Decision Support on Antibiotic Prescribing ...Conclusions: The iCPR tool was not effective in reducing antibiotic prescription rates for upper respiratory infections in diverse primary care ...
Clinical Decision Support for Respiratory InfectionsResearch shows that clinical decision support systems (CDSSs), like the iCPR system, can improve the use of antibiotics for respiratory infections by helping ...
a randomized trial in diverse primary care settingsThis article discusses study design and implementation of a multicenter cluster randomized control trial of the iCPR clinical decision support system.
Efficacy of an Evidence-Based Clinical Decision Support in ...To assess the influence of a customized evidence-based clinical decision support tool on the management of respiratory tract infections.
Impact of Clinical Decision Support on Antibiotic ...Background Clinical decision support (CDS) is a promising tool for reducing antibiotic prescribing for acute respiratory infections (ARIs).
Impact of Clinical Decision Support on Antibiotic ...Conclusions. The iCPR tool was not effective in reducing antibiotic prescription rates for upper respiratory infections in diverse primary care settings. This ...
Nursing Performance Using Clinical Prediction Rules for ...We evaluated a case-based simulation of the diagnosis and treatment for acute respiratory infections using clinical prediction rules. As a secondary outcome, we ...
A systematic review of clinical prediction rules to ...Our goal was to identify existing clinical prediction rules for predicting hospitalisation due to lower respiratory tract infection (LRTI) in children in ...
Cardiopulmonary resuscitation and risk of transmission of ...Most cardiac arrest patients requiring CPR will not have an acute respiratory infection that has a high risk of transmission to health care workers (HCWs).
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