APEX COPD is registry to provide a mechanism to standardize, store and utilize data to enable greater power to answer key research questions, and to improve patient outcomes in COPD primary care.
In the process of creating of a high-quality longitudinal dataset combining COPD templates and patient reported information and outcome (PRIO) to evaluate outcomes the APEX COPD registry supports changes and improvements in medical practice and deliver high quality research through the following mechanisms: * Templates integrated into the primary care clinical systems to support standardization of care and data over time. * Informing doctors at the point of consultation about the status of their patients through data-driven feedback. * Pre-filled electronic data templates from existing EHR data and questionnaires to reduce administrative burden for Primary Care Clinicians (PCC). * Engaging primary care clinicians in ongoing quality improvement initiatives directly at the point of care. * Research publications regarding treatment effectiveness and associated risk in mild to moderate COPD, reason for therapy switch/escalation and hidden undiagnosed and untreated COPD patients in primary care. * A strong network of primary care clinicians caring for patients with COPD in the US to drive the initiative and ensure impact on clinical practice through educational events, academic organizations and research outputs. The APEX COPD steering committee (SC) comprise of collective clinical expertise, scientific knowledge and experience in EHR, databases and research, forming an essential element of the APEX COPD registry. The SC plays an essential role in the development and governance of the APEX COPD registry, representing the sites participating, and providing the expertise necessary to implement and drive the initiative. Within this committee a smaller management group guides the operational aspects of the registry. The research database uses the Observational Medical Outcomes Partnership (OMOP) v5 Common Data Model (CDM) and the OMOP terminology will be updated at least bi-annually. Standardized OMOP Concept IDs will utilize SNOMED, RxNorm and may be adjusted to improve data compatibility with other OPC COPD databases.
Study Type
OBSERVATIONAL
Enrollment
4,500
Involves both EMR and PRIO data
Miramont Family Medicine
Fort Collins, Colorado, United States
Urban Family Practice
Buffalo, New York, United States
MetroHealth System
Cleveland, Ohio, United States
Bandera Family Health Care
San Antonio, Texas, United States
Describe and characterize the COPD primary care patient population's natural history
Baseline data from electronic health record (EHR) and patient reported information and outcomes (PRIO). The EHR data will be updated every three months.
Time frame: 31 December 2018 to 31 December 2022
Evaluate the comparative clinical, safety and cost effectiveness of current COPD treatments by class of therapy for COPD overall and in specific patient groups/phenotypes, to understand the predictors of response to available COPD treatment options
Patient reported information and outcomes (PRIO) will be collected annually and before very visit to their doctor
Time frame: 31 December 2018 to 31 December 2022
Improve quality of care, and primary care patient outcomes
Time frame: 31 December 2018 to 31 December 2022
Understand the clinical phenotypes
Time frame: 31 December 2018 to 31 December 2022
Understand the current burden and minimize side effects
Time frame: 31 December 2018 to 31 December 2022
Support the development of effective and efficient diagnostic routines
Time frame: 31 December 2018 to 31 December 2022
comparing clinician-diagnosed COPD at baseline against established
Time frame: 31 December 2018 to 31 December 2022
Describe disease management pattern
Time frame: 31 December 2018 to 31 December 2022
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Assess impact of inhaler technique
Time frame: 31 December 2018 to 31 December 2022
Describe factors associated with treatment choice at baseline
Time frame: 31 December 2018 to 31 December 2022
Describe risk factors
Time frame: 31 December 2018 to 31 December 2022
Assess the occurrence of exacerbations and other conditions
Time frame: 31 December 2018 to 31 December 2022
Assess biomarker data and estimate their predictive value for disease diagnosis
Time frame: 31 December 2018 to 31 December 2022
identify patients who may be eligible for participation in future research studies
Time frame: 31 December 2018 to 31 December 2022