UNLOCKING GUIDELINE ADHERENCE: THE ROLE OF EMR-INTEGRATED IDENTIFICATION TOOLS IN FRENCH COPD PRIMARY CARE
Author(s)
Thibaut Goulvent, PhD1, Leanne Bui, Ms1, Morgane Sebert, PhD2, david koskas, MD2, Gwenaëlle Jacquand, Ms1.
1Digital Health & Innovation, AstraZeneca France, Courbevoie, France, 2Medical, AstraZeneca France, Courbevoie, France.
1Digital Health & Innovation, AstraZeneca France, Courbevoie, France, 2Medical, AstraZeneca France, Courbevoie, France.
OBJECTIVES: Chronic obstructive pulmonary disease (COPD) affects 7.5% of the French adult population (≈3.5 million individuals). Suboptimal COPD management generates a substantial economic burden estimated at €678 million in France. Acute exacerbations, whose frequency is directly linked to therapeutic inadequacy, represent the primary cost driver with an average cost of €9,623 per episode. The Application of French HAS (Haute Autorité de Santé) guidelines by general practitioners (GPs) in primary care remains suboptimal, particularly for identifying uncontrolled patients and adjusting therapy according to guideline-directed medical therapy (GDMT). This study evaluates the impact of clinical decision support tools integrated into electronic medical records (EMRs) on HAS guideline implementation during GP consultations.
METHODS: Comparative before-after study conducted across 2,300 primary care practices (≈4,600 GPs) participating in a structured COPD management program. Automated identification tools were proposed to detect uncontrolled patients (ICD-10 coding and/or COPD treatment history + antibiotic/systemic corticosteroid use) despite maintenance therapy, coupled with HAS guideline application support tools. Comparative analysis over 12 months pre-intervention (year n-1) versus 12 months post-intervention(year n+1)
RESULTS: Among 67,864 patients identified with signs of uncontrol, 12,315 received therapeutic adjustment post-intervention versus 8,627 pre-interventions (+42.8%).Optimizations included: 3,487 transitions from dual/open triple therapy to fixed-dose triple combination (+7.3%), 7,344 escalations from dual to open triple therapy (-1.7%), and 1,484 dual therapy modifications (49% LABA/LAMA→ICS/LABA; 51% ICS/LABA→LABA/LAMA). Median time between identification andGDMT initiation decreased from 6 to 3 months (-50%). ICD-10 coding improved by +4% overall and by +10% among initially uncoded patients.
CONCLUSIONS: EMR-integrated clinical decision support tools significantly improve identification of uncontrolled COPD patients and HAS guideline implementation in primary care, with measurable impact on therapeutic optimization and reduced time-to-treatment. These findings support development of health economic studies evaluating long-term impact on exacerbations, hospitalizations, and healthcare costs.
METHODS: Comparative before-after study conducted across 2,300 primary care practices (≈4,600 GPs) participating in a structured COPD management program. Automated identification tools were proposed to detect uncontrolled patients (ICD-10 coding and/or COPD treatment history + antibiotic/systemic corticosteroid use) despite maintenance therapy, coupled with HAS guideline application support tools. Comparative analysis over 12 months pre-intervention (year n-1) versus 12 months post-intervention(year n+1)
RESULTS: Among 67,864 patients identified with signs of uncontrol, 12,315 received therapeutic adjustment post-intervention versus 8,627 pre-interventions (+42.8%).Optimizations included: 3,487 transitions from dual/open triple therapy to fixed-dose triple combination (+7.3%), 7,344 escalations from dual to open triple therapy (-1.7%), and 1,484 dual therapy modifications (49% LABA/LAMA→ICS/LABA; 51% ICS/LABA→LABA/LAMA). Median time between identification andGDMT initiation decreased from 6 to 3 months (-50%). ICD-10 coding improved by +4% overall and by +10% among initially uncoded patients.
CONCLUSIONS: EMR-integrated clinical decision support tools significantly improve identification of uncontrolled COPD patients and HAS guideline implementation in primary care, with measurable impact on therapeutic optimization and reduced time-to-treatment. These findings support development of health economic studies evaluating long-term impact on exacerbations, hospitalizations, and healthcare costs.
Conference/Value in Health Info
2026-11, ISPOR Europe 2026, Vienna, Austria
Value in Health, Volume 29, Issue 12S
Code
MT15
Topic
Clinical Outcomes, Health Technology Assessment, Medical Technologies
Topic Subcategory
Digital Health
Disease
No Additional Disease & Conditions/Specialized Treatment Areas, Personalized & Precision Medicine, Respiratory-Related Disorders (Allergy, Asthma, Smoking, Other Respiratory)