Developing and Implementing Asthma-Guidance and Prediction System (a-GPS) for Better Asthma Management

NCT ID: NCT02865967

Last Updated: 2020-11-16

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

COMPLETED

Clinical Phase

NA

Total Enrollment

185 participants

Study Classification

INTERVENTIONAL

Study Start Date

2016-08-31

Study Completion Date

2017-12-31

Brief Summary

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Asthma is the most common chronic condition in children and one of the five most burdensome diseases in the United States. Despite this, research and care for childhood asthma are limited by inefficient utilization of electronic medical records (EMRs) to facilitate large-scale studies and care.

The primary goal of this clinical trial is to implement the asthma-Guidance and Prediction System (a-GPS) on the Asthma Management Program (AMP, a current care coordination program for asthma care of children aged 5-17 years at Mayo Clinic). Primary hypothesis: The implementation of a-GPS in the current care is logistically feasible.

Detailed Description

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Despite the availability of evidence-based guidelines for asthma management and effective asthma therapies, asthma continues to cause a significant morbidity and burden to our society. Growing deployments of Electronic Health Records (EHRs) systems have established large practice-based longitudinal datasets, which allow for the identification of patient cohorts for epidemiological investigations and population-based management. Natural Language Processing (NLP; automated chart review using computer program) has received great attention and has played a critical role in secondary use of EHRs for clinical care and translational research. For example, we recently developed an NLP algorithm for the Predetermined Asthma Criteria (PAC) that can ascertain asthma status without manual chart review.

The primary goals of this proposed clinical trial are 1) to implement the asthma-Guidance and Prediction System (a-GPS) on Asthma Management Program (AMP, a current care coordination program for asthma care of children aged 5-17 years at Mayo Clinic) and 2) assess the impact of a-GPS on the primary and secondary end points for a one-year study period. These goals will be accomplished by conducting a randomized clinical trial with block design for three groups of children as the groups (blocks) of children are significantly heterogeneous in terms of receiving asthma care.

The a-GPS program includes 1) natural language processing (NLP) capabilities (i.e., automated EHR review to identify asthma status (yes vs. no) and monitor asthma activity (onset, remission, and relapse) in real time), 2) temporal and geospatial trends analysis of asthma outcome and care, and 3) asthma care optimization through predictive analytics.

The primary end points include asthma outcome using quarterly measured age-appropriate asthma control questionnaire (ie, Asthma Control Test (ACT; validated for children aged ≥ 4 years) scores for children ≥ 4 years: a total duration of ACT scores \> 19, or Test for Respiratory and Asthma Control in Kids (TRACK; validated for children under 5 years) scores for children \<4 years: a total duration of TRACK scores \< 80), care quality (timely care in response to asthma-related events), and costs (total costs per member). For those in Block 3, the rate of a physician diagnosis of asthma during the study will be also compared between the intervention and control groups as a measure for quality care.

Conditions

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Asthma

Keywords

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Decision Support Techniques Delayed Diagnosis Natural Language Processing Geographic Information Systems

Study Design

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Allocation Method

RANDOMIZED

Intervention Model

PARALLEL

Primary Study Purpose

SUPPORTIVE_CARE

Blinding Strategy

SINGLE

Participants

Study Groups

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Block1_Intervention

Usual care + a-GPS

Group Type EXPERIMENTAL

Usual care + a-GPS

Intervention Type OTHER

Clinicians will be provided a-GPS data on a regular basis for intervention group, but not control group such as their risk factors for asthma, quality of care, and asthma outcomes.

Block1_Control

Usual Care

Group Type OTHER

Usual care

Intervention Type OTHER

The subjects will be treat for their asthma by their physicians according to usual care.

Block2_Intervention

Usual care + a-GPS

Group Type EXPERIMENTAL

Usual care + a-GPS

Intervention Type OTHER

Clinicians will be provided a-GPS data on a regular basis for intervention group, but not control group such as their risk factors for asthma, quality of care, and asthma outcomes.

Block2_Control

Usual care

Group Type OTHER

Usual care

Intervention Type OTHER

The subjects will be treat for their asthma by their physicians according to usual care.

Block3_Intervention

Usual care + a-GPS

Group Type EXPERIMENTAL

Usual care + a-GPS

Intervention Type OTHER

Clinicians will be provided a-GPS data on a regular basis for intervention group, but not control group such as their risk factors for asthma, quality of care, and asthma outcomes.

Block3_Control

Usual care

Group Type OTHER

Usual care

Intervention Type OTHER

The subjects will be treat for their asthma by their physicians according to usual care.

Interventions

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Usual care + a-GPS

Clinicians will be provided a-GPS data on a regular basis for intervention group, but not control group such as their risk factors for asthma, quality of care, and asthma outcomes.

Intervention Type OTHER

Usual care

The subjects will be treat for their asthma by their physicians according to usual care.

Intervention Type OTHER

Eligibility Criteria

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Inclusion Criteria

\- Must be enrolled in AMP at the time of enrollment.


* Physician diagnosis of persistent asthma by NLP program for the list of physician diagnoses referring to persistent asthma, and/or
* Persistent asthma equivalent condition by either the Healthcare Effectiveness Data and Information Set (HEDIS); (e.g., ER visit or hospitalization for asthma during the past 12 months) or the National Asthma Education and Prevention Program (NAEPP); (e.g., ≥2 exacerbations requiring oral systemic corticosteroids in the past 6 months for children aged 0-4 years and 12 months for those aged ≥5 years), and/or
* Physician diagnosis of asthma with controller medication (e.g., inhaled corticosteroid) documented in the past 12 months, but they were not enrolled in AMP at the time of enrollment or during run-in period.


\- Children must meet the criteria for asthma delineated in Table 1 in protocol for asthma and recurrent asthma-like symptoms, but do not have a documentation of a diagnosis of asthma in medical records aged 0-17 years.

Exclusion Criteria

* Non-Olmsted County residents
* Children who are not enrolled in Mayo Clinic downtown pediatric practice
* No research authorization for using medical records for research
* Immunosuppressive therapy
* Conditions making asthma ascertainment difficult for Block 3 (pulmonary function tests that showed forced expiratory volume at one second (FEV1) to be consistently below 50% predicted or diminished diffusion capacity, tracheobronchial foreign body at or about the incidence date of asthma, wheezing occurring only in response to anesthesia or medications, bullous emphysema or pulmonary fibrosis on chest radiograph, homozygous alpha 1-protease inhibitor deficiency (PiZZ) alpha1-antitrypsin, cystic fibrosis, other major chest disease such as severe kyphoscoliosis or bronchiectasis)
* Children and their caregivers who decline to participate in the study
Maximum Eligible Age

17 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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Mayo Clinic

OTHER

Sponsor Role lead

Responsible Party

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Young Juhn

M.D.

Responsibility Role PRINCIPAL_INVESTIGATOR

Principal Investigators

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Young J Juhn

Role: PRINCIPAL_INVESTIGATOR

Mayo Clinic

Locations

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Mayo Clinic in Rochester

Rochester, Minnesota, United States

Site Status

Countries

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United States

References

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Seol HY, Shrestha P, Muth JF, Wi CI, Sohn S, Ryu E, Park M, Ihrke K, Moon S, King K, Wheeler P, Borah B, Moriarty J, Rosedahl J, Liu H, McWilliams DB, Juhn YJ. Artificial intelligence-assisted clinical decision support for childhood asthma management: A randomized clinical trial. PLoS One. 2021 Aug 2;16(8):e0255261. doi: 10.1371/journal.pone.0255261. eCollection 2021.

Reference Type DERIVED
PMID: 34339438 (View on PubMed)

Related Links

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Other Identifiers

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15-004435

Identifier Type: -

Identifier Source: org_study_id