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IMplementing Predictive Analytics towards efficient COPD Treatments (IMPACT): protocol for a stepped-wedge cluster

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  • 1Collaboration for Outcomes Research and Evaluation (CORE), Faculty of Pharmaceutical Sciences, University of British Columbia, Vancouver, British Columbia, V6T 1Z3, Canada.

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Summary
This summary is machine-generated.

This study integrates a COPD exacerbation risk tool into routine care to improve treatment appropriateness and patient outcomes. The IMPACT trial will assess its impact on COPD management and patient well-being.

Keywords:
Chronic obstructive pulmonary diseaseClinical prediction modelsDecision aidPrescription appropriatenessProcess of careProtocolSex and gender

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Area of Science:

  • Pulmonary Medicine
  • Health Informatics
  • Clinical Trials

Background:

  • Personalized disease management using quantitative risk prediction can enhance patient care.
  • Integrating risk prediction tools into clinical workflows requires stakeholder input and rigorous evaluation.
  • The IMPACT study aims to bridge this gap in Chronic Obstructive Pulmonary Disease (COPD) management.

Purpose of the Study:

  • To integrate an exacerbation risk prediction tool into routine COPD care.
  • To evaluate the tool's impact on prescription appropriateness, medication adherence, quality of life, and exacerbation rates.
  • To investigate potential sex and gender disparities in COPD care.

Main Methods:

  • The IMPACT study involves two phases: development of decision support tools (for clinicians and patients) and a stepped-wedge cluster randomized controlled trial.
  • A user-centered approach guided the development of the ACCEPT decision intervention (ADI) and a patient information pamphlet.
  • The trial will enroll at least 24 pulmonologists across two clinics over 18 months, followed by a qualitative process evaluation.

Main Results:

  • Primary outcome: Impact on prescription appropriateness.
  • Secondary outcomes: Changes in medication adherence, quality of life, exacerbation rates, and sex/gender disparities.
  • The study is designed to provide data on the effectiveness of integrating predictive analytics into COPD management.

Conclusions:

  • The IMPACT study's findings will inform the integration of predictive tools into routine care, particularly with concurrent electronic health record system harmonization.
  • Positive results could facilitate large-scale implementation of improved COPD management strategies.
  • A process evaluation will guide future iterations and optimize tool uptake.