NCT00699439

Brief Summary

The primary idea is that the use of a computerized reminder system to help with the guideline implementation will increase utilization and adherence of guideline-driven care, leading to improved patient outcomes. The hypothesis we aim to address is that an automatic, computerized reminder system for detecting asthma patients in the pediatric ED will increase paper-based guideline utilization compared to paper-based guideline without the system. We aim to implement a real-time, computerized asthma detection system and integrate the system with the pediatric emergency department information system, and evaluate the effect of the asthma detection system on reminding clinicians to use the paper-based asthma guideline.

Trial Health

87
On Track

Trial Health Score

Automated assessment based on enrollment pace, timeline, and geographic reach

Enrollment
1,102

participants targeted

Target at P75+ for not_applicable asthma

Timeline
Completed

Started Jul 2009

Longer than P75 for not_applicable asthma

Geographic Reach
1 country

1 active site

Status
completed

Health score is calculated from publicly available data and should be used for screening purposes only.

Trial Relationships

Click on a node to explore related trials.

Study Timeline

Key milestones and dates

First Submitted

Initial submission to the registry

June 12, 2008

Completed
6 days until next milestone

First Posted

Study publicly available on registry

June 18, 2008

Completed
1 year until next milestone

Study Start

First participant enrolled

July 1, 2009

Completed
5.9 years until next milestone

Primary Completion

Last participant's last visit for primary outcome

June 1, 2015

Completed
Same day until next milestone

Study Completion

Last participant's last visit for all outcomes

June 1, 2015

Completed
Last Updated

August 17, 2018

Status Verified

August 1, 2018

Enrollment Period

5.9 years

First QC Date

June 12, 2008

Last Update Submit

August 15, 2018

Conditions

AsthmaMedical Informatics

Keywords

Medical InformaticsAsthmaEmergency Service, HospitalBayesian Method

Outcome Measures

Primary Outcomes (2)

  • Guideline utilization. Guideline utilization will be defined as having used the guideline for the documentation of at least one assessment (asthma score).

    Within 1 week after visit

  • Guideline Adherence. The measurement of guideline adherence includes three measures: a) asthma assessment (score); b) treatment compatible with assessment (or documentation of reason to deviate); and c) adherence to guideline schedule.

    Within 1 week after visit

Study Arms (2)

A

ACTIVE COMPARATOR

If a patient is identified as having an asthma exacerbation by the Bayesian Network, the paper-based flow-chart will be printed out to place on the chart.

Other: Paper-based asthma flow diagram

B

NO INTERVENTION

If a patient is identified as having an asthma exacerbation by the Bayesian Network, and assigned to the control group, no flow-chart will be printed out.

Interventions

Paper-based asthma flow diagramOTHER

If a patient is identified as having an asthma exacerbation by the Bayesian Network, the patients will be randomized to either arm A or B. If in A, the paper-based flow-chart will be printed out to place on the chart.

A

Eligibility Criteria

Age2 Years - 18 Years
Sexall
Healthy VolunteersYes
Age GroupsChild (0-17), Adult (18-64)

You may qualify if:

  • All patients aged 2-18 years;
  • Emergency Severity Index 2 to 5; AND
  • Availability of completed computerized triage documentation.

You may not qualify if:

  • Critically ill patients (Emergency Severity Index 1)
  • Patients who leave-without-being seen
  • Patients who leave against-medical-advice
  • Patients whose final diagnosis was not asthma (false positive identification by the detection system) or were determined not to be eligible for the guideline.

Contact the study team to confirm eligibility.

Sponsors & Collaborators

Study Sites (1)

Vanderbilt University

Nashville, Tennessee, 37232, United States

Location

Related Publications (4)

  • Dexheimer JW, Brown LE, Leegon J, Aronsky D. Comparing decision support methodologies for identifying asthma exacerbations. Stud Health Technol Inform. 2007;129(Pt 2):880-4.

    PMID: 17911842BACKGROUND

  • Sanders DL, Aronsky D. Prospective evaluation of a Bayesian Network for detecting asthma exacerbations in a Pediatric Emergency Department. AMIA Annu Symp Proc. 2006;2006:1085.

    PMID: 17238704BACKGROUND

  • Sanders DL, Aronsky D. Detecting asthma exacerbations in a pediatric emergency department using a Bayesian network. AMIA Annu Symp Proc. 2006;2006:684-8.

    PMID: 17238428BACKGROUND

  • Sanders DL, Gregg W, Aronsky D. Identifying asthma exacerbations in a pediatric emergency department: a feasibility study. Int J Med Inform. 2007 Jul;76(7):557-64. doi: 10.1016/j.ijmedinf.2006.03.003. Epub 2006 May 2.

    PMID: 16647876BACKGROUND

MeSH Terms

Conditions

AsthmaEmergencies

Condition Hierarchy (Ancestors)

Bronchial DiseasesRespiratory Tract DiseasesLung Diseases, ObstructiveLung DiseasesRespiratory HypersensitivityHypersensitivity, ImmediateHypersensitivityImmune System DiseasesDisease AttributesPathologic ProcessesPathological Conditions, Signs and Symptoms

Study Officials

  • Judith W Dexheimer, MS

    Vanderbilt University

    PRINCIPAL INVESTIGATOR

  • Dominik Aronsky, MD, PhD

    Vanderbilt University

    PRINCIPAL INVESTIGATOR

  • Donald H Arnold, MD, MPH

    Vanderbilt University

    STUDY CHAIR

Study Design

Study Type
interventional
Phase
not applicable
Allocation
RANDOMIZED
Masking
NONE
Purpose
HEALTH SERVICES RESEARCH
Intervention Model
PARALLEL
Sponsor Type
OTHER
Responsible Party
SPONSOR

Study Record Dates

First Submitted

June 12, 2008

First Posted

June 18, 2008

Study Start

July 1, 2009

Primary Completion

June 1, 2015

Study Completion

June 1, 2015

Last Updated

August 17, 2018

Record last verified: 2018-08

Locations

US(1)