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Instrumental variables for implementation science: exploring context-dependent causal pathways between implementation

Aaloke Mody1, Lindsey M Filiatreau2, Charles W Goss3

  • 1Division of Infectious Diseases, Department of Medicine, Washington University School of Medicine, Campus Box 8051, 4523 Clayton Avenue, St. Louis, MO, 63110, USA. aaloke.mody@wustl.edu.

Implementation Science Communications
|December 21, 2023
PubMed
Summary
This summary is machine-generated.

Instrumental variable (IV) methods help understand how implementation strategies (IS) affect evidence-based interventions (EBI) and patient outcomes. IV analysis isolates the impact of IS on EBI uptake and the EBI

Keywords:
Causal pathwaysImplementation mechanismsImplementation scienceInstrumental variablesIntervention uptakeMediators

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Area of Science:

  • Implementation Science
  • Causal Inference
  • Epidemiology

Background:

  • Implementation strategies (IS) and evidence-based interventions (EBI) effectiveness varies by context.
  • Understanding these variations is crucial for advancing implementation science.
  • Distinguishing IS from EBI efficacy overlooks their intertwined nature and context-dependency.

Purpose of the Study:

  • To explore instrumental variable (IV) analyses as a method for implementation science.
  • To isolate the effects of IS on implementation outcomes, EBI uptake on patient outcomes, and the overall IS effectiveness.
  • To examine how IS alters the context and thus the effect of an EBI.

Main Methods:

  • Utilizing instrumental variable (IV) analyses.
  • Randomized exposure to an implementation strategy.
  • Analyzing three quantities: IS effect on uptake, EBI uptake effect on patient outcomes, and IS overall effectiveness.
  • Illustrating with examples of ART initiation guidelines in Zambia and masking programs in Bangladesh.

Main Results:

  • IV analysis stages address causal questions in implementation science.
  • First stage: IS effect on EBI uptake.
  • Second stage: Complier average causal effect (CACE) of EBI on patient outcomes, accounting for differing uptake mechanisms and subgroups.
  • IV methods provide a framework linking IS and EBIs, highlighting IS as a contextual determinant.

Conclusions:

  • Instrumental variable (IV) methods, with random IS exposure, clarify the context-dependent relationships between IS, EBIs, and patient outcomes.
  • IV methods formalize that EBI causal effects are context-specific to the promoting IS.
  • Integrating implementation science with causal epidemiologic methods offers novel insights into mechanisms and context.