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Sponsored by: |
Vanderbilt University |
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Information provided by: | Vanderbilt University |
ClinicalTrials.gov Identifier: | NCT00699439 |
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.
Condition | Intervention |
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Asthma Medical Informatics |
Other: Paper-based asthma flow diagram |
Study Type: | Interventional |
Study Design: | Health Services Research, Randomized, Open Label, Parallel Assignment |
Official Title: | A Reminder System for Paper-Based Asthma Guidelines in the Pediatric Emergency Department |
Estimated Enrollment: | 400 |
Study Start Date: | February 2009 |
Estimated Study Completion Date: | January 2011 |
Estimated Primary Completion Date: | May 2009 (Final data collection date for primary outcome measure) |
Arms | Assigned Interventions |
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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.
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Other: Paper-based asthma flow diagram
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.
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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.
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Other: Paper-based asthma flow diagram
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.
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Asthma is the leading chronic childhood disease affecting 9 million children (12.5%) under 18 years of age (1). Asthma exacerbations cause an estimated 14 million missed school days (2) and more than 1.8 million emergency department (ED) visits annually (2), and account for >60% of asthma-related costs (3). The chronic characteristic of asthma carries a considerable economic burden.
Uncontrolled asthma can lead to exacerbations requiring the patient to seek immediate care, frequently in an ED setting. Several asthma guidelines, including the nationally accepted guideline from the National Heart, Lung, and Blood Institute (NHLBI), exist to support clinicians in providing adequate treatment. Utilization of and adherence with asthma guidelines improves patients' clinical care (4, 5). However, guideline adherence remains suboptimal.
In the ED, early recognition and accurate assessment of the severity of airway obstruction and response to therapy are fundamental to the improvement of health for patients with asthma. The NHLBI guidelines emphasize early recognition and treatment of asthma exacerbations, as well as appropriate treatment stratified by severity.
Computer applications for patient care can address barriers to optimal medical care. Computer systems have improved the use and adherence to practice guidelines, provide clinical alerts and reminders, and generate patient-specific treatment recommendations and educational material. Implementation of guideline-driven decision support is frequently paper-based or computerized. In either form a major barrier remains on the busy clinicians to remember to initiate the guideline a process and to embed the guideline tasks in the clinical workflow of the care team (5). The proposed study examines the benefits of a novel approach for reminding clinicians in an ED setting to use guideline-driven care. The approach will apply a workflow-embedded process taking advantage of an advanced information technology infrastructure. The informatics approach will include two elements: a) a computerized, real-time reminder system, which will automatically detect guideline-eligible patients without requiring additional data entry, and b) a computerized, workflow-embedded guideline implementation.
References
Ages Eligible for Study: | 2 Years to 18 Years |
Genders Eligible for Study: | Both |
Accepts Healthy Volunteers: | Yes |
Inclusion Criteria:
The study's inclusion criteria are:
Exclusion Criteria:
The exclusion criteria are:
Contact: Judith W Dexheimer, MS | 615-936-3573 | judith.dexheimer@vanderbilt.edu |
Contact: Dominik Aronsky, MD, PhD | 615-936-1739 | dominik.aronsky@vanderbilt.edu |
United States, Tennessee | |
Vanderbilt University | |
Nashville, Tennessee, United States, 37232 |
Principal Investigator: | Judith W Dexheimer, MS | Vanderbilt University |
Principal Investigator: | Dominik Aronsky, MD, PhD | Vanderbilt University |
Study Chair: | Donald H Arnold, MD, MPH | Vanderbilt University |
Responsible Party: | Vanderbilt University ( Judith Dexheimer ) |
Study ID Numbers: | 070206 |
Study First Received: | June 12, 2008 |
Last Updated: | December 12, 2008 |
ClinicalTrials.gov Identifier: | NCT00699439 History of Changes |
Health Authority: | United States: Institutional Review Board |
Medical Informatics Asthma Emergency Service, Hospital Bayesian Method |
Hypersensitivity Lung Diseases, Obstructive Respiratory Tract Diseases Bronchial Diseases Lung Diseases |
Hypersensitivity, Immediate Emergencies Asthma Respiratory Hypersensitivity |
Disease Attributes Hypersensitivity Lung Diseases, Obstructive Pathologic Processes Immune System Diseases Respiratory Tract Diseases |
Bronchial Diseases Lung Diseases Hypersensitivity, Immediate Emergencies Asthma Respiratory Hypersensitivity |