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

Asthma Clinical Trial

Official title: Enhancing Asthma Care and Outcome Through the Implementation of Asthma-Guidance and Prediction System (a-GPS) on Asthma Management Program: A Randomized Block Design

Status Completed

Clinical Trial Summary

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.

Clinical Trial Description

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. ;

Related Conditions & MeSH terms

• Asthma

• NCT number: NCT02865967
• Study type: Interventional
• Source: Mayo Clinic
• Status: Completed
• Phase: N/A
• Start date: August 2016
• Completion date: December 2017