Electronic Health Record Tools for Bronchiolitis

Recruiting at 2 trial locations

Overseen By Benjamin Bodnar, MD

Age: < 18

Sex: Any

Trial Phase: Academic

Sponsor: Johns Hopkins University

Disqualifiers: Birth encounter, ICU, >14 days

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

Compensation: Varies

Number of Visits: Unknown

Duration: 2-4 days

800 Participants Needed

Trial Summary

What is the purpose of this trial?

The goal of this experimental study is to learn whether different types of best practice advisories (BPAs) that direct clinicians to reference clinical guidelines embedded in the electronic health record (EHR) increase the delivery of evidence-based care in children presenting to the hospital with bronchiolitis. The main questions it aims to answer are: * Do BPAs improve clinicians' delivery of guideline-concordant care in bronchiolitis? * Do interruptive BPAs improve guideline-concordant care of bronchiolitis more than non-interruptive BPAs? Researchers will compare the treatment and outcomes of patients whose clinicians did not receive a BPA, to those whose clinicians received a non-interruptive BPA, to those whose clinicians received an interruptive BPA. Patients will continue to receive standard hospital care for bronchiolitis. Clinicians will: * retain access to an EHR-embedded clinical guideline for bronchiolitis care * be exposed to either no BPA, a non-interruptive BPA, or an interruptive BPA promoting the EHR-embedded clinical guideline (randomized per patient encounter)

Will I have to stop taking my current medications?

The trial information does not specify whether participants must stop taking their current medications. It seems that patients will continue to receive standard hospital care for bronchiolitis, so it's likely that any changes to medication would be part of that standard care.

What data supports the effectiveness of the treatment Leveraging Electronic Health Record Tools for bronchiolitis?

Electronic health records (EHRs) can improve the quality of patient care by providing detailed clinical information that helps monitor and enhance treatment practices. This approach has been used to improve evidence-based care in other conditions, suggesting potential benefits for bronchiolitis treatment as well. ^{1 2 3 4 5}

Is the use of electronic health record tools generally safe for humans?

Research shows that electronic health record tools can help detect adverse events (unintended harm from medical care) more accurately and efficiently, which can improve patient safety. However, there are usability challenges, especially in pediatric settings, that can lead to medication errors, such as improper dosing, which might harm patients. ^{6 7 8 9 10}

How does the electronic health record tool treatment for bronchiolitis differ from other treatments?

The electronic health record (EHR) tool for bronchiolitis is unique because it focuses on improving the quality of care through better data management and decision support, rather than directly treating the condition with medication. This approach uses technology to enhance the accuracy and completeness of patient information, which can lead to more informed and effective treatment decisions. ^{1 2 11 12 13}

Research Team

Benjamin Bodnar, MD

Principal Investigator

Johns Hopkins University

Eligibility Criteria

This trial is for children hospitalized with bronchiolitis. There are no specific inclusion or exclusion criteria provided, suggesting that the study may be broadly applicable to pediatric patients admitted with this condition.

Inclusion Criteria

Physicians and advanced practice providers entering the patient's chart or orders entry activity for Emergency Department (ED) and inpatient encounters

My child, 24 months or younger, is in the hospital with bronchiolitis.

Exclusion Criteria

Physicians and advanced practice providers who do not enter the patient's chart or orders entry activity

Current encounter is birth-encounter

I am currently in an intensive care unit.

Timeline

Screening

Participants are screened for eligibility to participate in the trial

1-2 weeks

Treatment

Patients receive standard hospital care for bronchiolitis with exposure to different types of BPAs

2-4 days

Inpatient hospital stay

Follow-up

Participants are monitored for safety and effectiveness after treatment

1 week

Treatment Details

Interventions

• Leveraging Electronic Health Record Tools

Trial Overview The study tests if best practice advisories (BPAs) in electronic health records help doctors follow guidelines for treating bronchiolitis. It compares no BPA, non-interruptive BPA, and interruptive BPA's effects on care quality.

Participant Groups

Group I: Non-interruptive BPA Experimental Treatment 1 Intervention

Clinicians will be exposed to an non-interruptive BPA directing the clinician to reference the EHR-embedded, evidence-based clinical guideline for the care of bronchiolitis.

Group II: Interruptive BPA Experimental Treatment 1 Intervention

Clinicians will be exposed to an interruptive BPA directing the clinician to reference the EHR-embedded, evidence-based clinical guideline for the care of bronchiolitis.

Group III: No BPA Active Control 1 Intervention

Clinicians will not be exposed to a BPA about the care of bronchiolitis. The participants will still have access to the EHR-embedded, evidence-based clinical guideline.

Who Is Running the Clinical Trial?

Johns Hopkins University

Lead Sponsor

Trials

2,366

Recruited

15,160,000+

Findings from Research

Out of 9,000 patient safety reports analyzed from 2012 to 2017, 36% identified usability issues related to electronic health records (EHRs) that contributed to medication events, highlighting significant safety concerns in pediatric care.

Among the usability issues, the most frequent problems were related to system feedback and visual display, with improper dosing being the most common medication error, indicating critical areas for improvement in EHR design to enhance safety for children.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Identifying Electronic Health Record Usability And Safety Challenges In Pediatric Settings. Ratwani, RM., Savage, E., Will, A., et al.[2019]

References

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

Addressing electronic clinical information in the construction of quality measures. [2014]

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

Validity of using an electronic medical record for assessing quality of care in an outpatient setting. [2019]

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

Implementation of electronic chemotherapy ordering: an opportunity to improve evidence-based oncology care. [2016]

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

Comparative Effectiveness Research Through a Collaborative Electronic Reporting Consortium. [2015]

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

Challenges in using electronic health record data for CER: experience of 4 learning organizations and solutions applied. [2022]

6. England pubmed.ncbi.nlm.nih.gov

Phenotyping for patient safety: algorithm development for electronic health record based automated adverse event and medical error detection in neonatal intensive care. [2022]

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

Automated detection of adverse events in children. [2013]

8. England pubmed.ncbi.nlm.nih.gov

Using electronic medical record data to report laboratory adverse events. [2020]

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

Identifying Electronic Health Record Usability And Safety Challenges In Pediatric Settings. [2019]

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

Automated adverse event detection collaborative: electronic adverse event identification, classification, and corrective actions across academic pediatric institutions. [2018]

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

Web-based electronic health records improve data completeness and reduce medical discrepancies in employee vaccination programs. [2015]

12. England pubmed.ncbi.nlm.nih.gov

The electronic health record as a catalyst for quality improvement in patient care. [2019]

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

Automating care quality measurement with health information technology. [2012]