Abstract

Background: Airway disease, including asthma and COPD, are highly prevalent among Veterans. Asthma affects 3-10% of Veterans with a 3-fold increase in incidence from 2003-2011, particularly among those with toxic service-related exposures; COPD affects almost 25% of Veterans. Inappropriate management increases risk of disease progression and exacerbations, worsening lung function, health-related quality of life, and increasing risk of morbidity, mortality, and illness-related expenses. Clinical practice guideline (CPG) utilization within the VA is unknown but is poor in other contexts. Guidelines are updated frequently, increasing difficulty of keeping up with changes, particularly in busy primary care practices managing multiple chronic conditions at once. Policies like prescription drug formulary changes affect the ability to stay concordant with guidelines. Significance: Currently, we lack an understanding of the factors associated with adherence to guidelines in airway disease care delivery within the VA. This limits our ability to design initiatives to bolster guideline concordant care or track progress in efforts to support clinician decisions around guideline utilization. This project aligns with HSR&D/ORD priorities for improving complex care delivery in primary care, putting VA data to work for Veterans, and focusing on conditions exacerbated by military service-related toxic exposures. Innovation & Impact: Currently, EHR or administrative data-based measures to assess airway disease CPG concordance are limited in both sensitivity and specificity. By creating an electronic health data definition of guideline-concordant airway disease care, enhanced with natural language processing (NLP), we will be able to assess the uptake and concordance to these CPGs over time with particular attention to how guideline and formulary changes affect concordance and create quality metrics to assess guideline concordance. By conducting qualitative interviews, we will further elucidate barriers and facilitators to CPG uptake, which will naturally catalyze our planned efforts to support CPG diffusion and implementation studies in airway disease. Specific Aims: Aim 1: Develop and validate EHR-based definitions for guideline-based airway disease care. Aim 2: Explore reasons for CPG discordance among clinicians and preferences for treatment among Veterans with airway disease using qualitative semi-structured interviews. Aim 3: Utilize the validated NLP-enhanced airway disease performance measure algorithms to determine rates of CPG-concordant care among Veterans with airway disease and to identify factors associated with variability and changes in rates. Methodology: We will obtain patient records for asthma and COPD using ICD-10 codes from October 1, 2015 to date at all VA facilities providing primary, specialty, and inpatient care. Electronic health record data including clinic/hospital visits and prescriptions, and NLP of clinical notes will be used to construct proxies for asthma and COPD guideline components mirroring the existing CPG definitions. A sample of clinical records will be abstracted for chart review from VA Greater Los Angeles, Puget Sound, and Birmingham to validate the constructed proxies in the administrative data definitions against provider assessments during clinical encounters. Regression models will be fit to explore guideline-concordant care over time and evaluate associations of key covariates with guideline-care discordance, including region/VISN, urban/rural distinctions, primary care only vs. specialty care involvement, patient sociodemographics, and comorbid conditions. Qualitative interviews will be undertaken to explore both clinician- and Veteran-centered reasons for uptake and disuse of guideline-based care e.g.: treatment preference for escalation and de-escalation of medications. Next Steps/Implementation: Upon successful validation of algorithms to assess airway disease CPG concordance and respective uptake/adherence rates, we will have useful measures to track CPG-based care and foundational data needed for the design and execution of a planned hybrid implementation-effectiveness trial to test provider support and patient education tools to improve guideline-concordant airway disease care.

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DRA: None at this time.

DRE: None at this time.

Keywords: None at this time.

MeSH Terms: None at this time.