Adaptation of Evidence-based Interventions and De-Implementation of Ineffective Programs
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Transcript of Adaptation of Evidence-based Interventions and De-Implementation of Ineffective Programs
Emerging Topics in Implementation Science
Adaptation of Evidence-based Interventions and
De-Implementation of Ineffective Programs
Wynne E. Norton, PhD
Program Officer, National Cancer Institute
November 14, 2017
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Disclosure
I have no financial relationships to disclose.
Opinions are mine, not official positions of the National Cancer
Institute, the National Institutes of Health, or the U.S. federal
government.
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Overview
Fidelity vs. adaptation of evidence-based interventions
Definitions, concepts, models, future research
De-implementation of ineffective programs
Definitions, NIH portfolio analysis, future research
Questions, comments
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Fidelity of Evidence-based Interventions
“Extent to which the intervention was delivered as planned. It
represents the quality and integrity of the intervention as conceived by
developers.” (Brownson et al., 2012)
Why is fidelity important?
Maintains integrity of intervention.
Increases probability that intervention will have impact.
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Fidelity Measurements
How do we know if fidelity is maintained?
Fidelity measures
Differentiate between intervention not working (ineffective) and
intervention not being implemented appropriately.
Self-report (e.g., clinicians), individual/patient reports,
observation, audio/video recordings.
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Adaptation of Evidence-based Interventions
“Planned or purposeful changes to the design or delivery of an
intervention” (Stirman et al., 2013).
Interventions likely need to be adapted to fit context:
Target population, delivery setting, urban/rural, community, etc.
“Intervention-implementation fit”
How do you adapt the evidence-based intervention to increase “fit”
without sacrificing potential impact on targeted outcomes?
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Intervention Elements: Core vs. Peripheral
Core Elements
Elements of the intervention that cannot be deleted or dropped
If elements are adapted, should be a planned and purposeful
process with input from end users
Peripheral Elements
Elements of the intervention that can be deleted or dropped, as
needed (e.g., limited resources, time constraints)
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Intervention Elements: Adaptation
What elements can be adapted…and by how much?
Elements that can be modified:
Names, pictures, places, quotes, nomenclature, incentives for
participation, timeline of delivery
Elements that should not be modified:
Health topic, entire sections of program, core elements, guiding model,
theory, or framework, targeted health behavior
R. Brownson. Red light, yellow light, green light adaptations.
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Intervention Elements: Guidance for Adaptation Process
How do I make modifications to intervention elements?
Purposeful
Planned
Informed by guiding theory, framework, or model of behavior change
underlying evidence-based intervention
Stakeholder input
Pilot test, revise
Monitor
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Toward a Science of Adaptation
How can we advance our scientific understanding of intervention
adaptation?
(1) Frameworks and models
Classification of adaptations (Stirman et al., 2013)
ADAPT-ITT (Wingood & DiClemente, 2008)
Dynamic Adaptation Process (Aarons et al., 2012)
Adaptome (Chambers & Norton, 2015)
(2) Research questions and opportunities
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Sources of Intervention Adaptation
Stirman et al., 2013
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Adaptation Frameworks & Models: ADAPT-ITT
Wingood & DiClemente, 2008
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ADAPT-ITT Model: Example
Wingood & DiClemente, 2008
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Dynamic Adaptation Process
Aarons et al., 2012
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Sources of Intervention Adaptation
Chambers & Norton, 2015
16Adaptome, Chambers & Norton, 2015
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Adaptation Research Questions and Opportunities
Assessment of intervention adaptation in vivo in local settings.
Standardized reporting of adaptation processes.
At what point does an existing evidence-based intervention become a
new intervention…and what does that mean in terms of ‘evidence’?
When and what type of adaptations lead to negative outcomes?
When and what type of adaptations lead to more outcomes (e.g.,
positive deviance)?
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De-Implementation of Ineffective Programs
Increasing recognition of harms associated with overscreening,
overdiagnosis, and overtreatment (overuse).
Use of ineffective, low-value, or untested practices, programs,
interventions.
Inefficiency, waste, poor use of resources.
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De-Implementation: Definitions and Terms
Nieven et al. 2015
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De-Implementation: Definitions and Terms
Disinvestment
Processes of withdrawing (partially or completely) health
resources from any existing health care practices, procedures,
technologies or pharmaceuticals that are deemed to deliver little or
no health gain for their cost, and are thus not efficient health
resource allocations.
De-adoption
Discontinuation of a clinical practice after it was previously
adopted.
Editor’s Note, Implementation Science, 2014; Elshaug et al., 2007; Prasad & Ioannidis, 2014
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De-Implementation: Definitions and Terms
De-prescribe
Process of tapering, stopping, discontinuing, or withdrawing drugs,
with the goal of managing polypharmacy and improving outcomes.
De-implementation “We regard de-implementation broadly as ‘stopping practices that are not
evidence-based.’”
Reduce (frequency and/or intensity) or stop the delivery of ineffective,
unproven, harmful, overused, inappropriate, and/or low-value health
services and practices provided to patients by healthcare practitioners
and systems.
Thompson & Farrell, 2013; Rogers, 2003; Prasad & Cifu, 2015; Norton et al., in press
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Current State of De-Implementation Research
Terminology, definitions
Conceptual papers
Specialized scientific conferences (e.g., Preventing Overdiagnosis)
Professional society initiatives (e.g., ChoosingWisely campaign)
Identification of possible strategies to reduce low-value care
Funded research studies…?
Norton et al., in press; Colla et al., 2016; Niven et al., 2015
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Systematic Review of NIH-funded Studies
Identify, describe, and characterize funded research grants on de-
implementation
Snapshot of state-of-the-science
Portfolio analysis across 27 NIH Institutes and Centers and AHRQ,
2000-2017
Searched grants database, 11 key terms, 3 specific funding
announcements
Assess eligibility, develop and apply codebook
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Results
N = 20 funded research grants
15 NIH funded, 5 AHRQ funded
11 awarded 2015-2016
Example grant titles
Impact of social contagion on physician use of unproven cancer
interventions
Identifying cascades of low-value care and the organizational
practices that prevent them
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Study Features*
Objectives Understand or characterize factors
influencing de-implementation
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Develop strategies to facilitate
de-implementation
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Health Area Cancer 8
Cardiovascular Disease 1
Infectious Diseases 3
Kidney Disease 1
Mental Health 2
Continuum of Care Prevention 2
Screening and/or Detection 5
Diagnosis 3
Treatment 14
*Select results
27*Select results
Study Features*
Health Service/
Practice
Drugs, Medications, or Therapies 15
Preventive, Diagnostic, or Screenings Tests 8
Setting Clinical care 16
Hospital 4
Assisted Living Facility 2
School 1
Design & Methods Experimental 7
Quasi-experimental 5
Observational 7
Mixed Methods 4
Qualitative 3
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Summary
Relatively few research grants focused on de-implementation.
Additional effort is needed to increase awareness of and interest in
studying de-implementation.
Funding opportunities.
Synthesize and operationalize terms.
Collaborate with ongoing initiatives.
Others?
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Future Directions
How are implementation and de-implementation similar?
How are they different?
Models, frameworks, theories?
Processes?
Strategies?
Ethical considerations?
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Closing
Very exciting time to be in the field of implementation research!
Opportunity to advance science and improve practice.
Adaptation and de-implementation are two emerging areas of inquiry
in the field.
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Questions? Comments?
Wynne E. Norton, PhD
Program Officer, Implementation Science
Division of Cancer Control and Population Sciences
National Cancer Institute
www.cancer.gov www.cancer.gov/espanol