METHODS FOR CARE INNOVATION
SESSIE 1 – 2 ARTIKELS + LESOPNAMES
DE GEEST ET AL: POWERING SWISS HEALTH CARE FOR THE FUTURE:
IMPLEMENTATION SCIENCE TO BRIDGE “THE VALLEY OF
DEATH”
- 2019 SAMS or Swiss Academy of Medical science bulletin addressed the rift between basic
scientific discoveries and their clinical use.
o “Valley of death” = distance between both.
§ Consists of well-researched, EB programmes, practices, procedures, products
and policies developed by health scientists that are now waiting on bookshelves
to be translated into real world settings.
§ 30 – 40% of patients do not receive treatments of proven efficacy, 20 – 25%
receive unnecessary or potentially harmful treatments.
o Same rift between clinical research and implementation of related health policies or
innovations in health services.
- 2019: report on improving patient safety and quality of care called for investment in
implementation science.
- Balas and Boren: 14% of published evidence is translated into clinical practice.
o Mean wait between innovation and application = 17 years.
o Implementation deficits contribute to excess research waste.
- 2 types of research waste:
o Research waste 1: results in a low proportion of the research initiated eventually
resulting in high-quality scientific evidence.
§ Research designed without reference to systematic reviews of the existing
evidence.
§ Research not published in full.
§ Studies with avoidable research flaws
§ Studies that are unusable, incompletely reported or both
§ Various measures have been implemented to reduce this type of waste, with
some success.
• Examples: obligation to register studies, widespread investment in
clinical research infrastructures for example clinical trial units,
guidelines supporting the quality of scientific reporting.
• But more measures are needed.
o Research waste 2: lack of effective and sustainable translation and implementation of
EB innovations from the trial word into daily clinical practice.
§ To guide the translation of well-conducted, well-reported studies into real-word
settings, an increased focus on “implementation science’ is needed and should
be added early in the research process.
• Implementation science = “the scientific study of methods to promote
the systematic uptake of research findings and other EB practices into
1
, routine practice, and, hence, to improve the quality and effectiveness of
health services and care”.
• Conducting and implementation science study implies not only a
scientific evaluation of effectiveness of an intervention in a real-world
setting, but also an evaluation of how and why it either works or fails in
the specific context in which it was tried.
• Evidence generated on effectiveness outcomes and from evaluation of
implementation pathways can subsequently be transferred to other
contexts to suport a more efficient implemenations and/or scaling up of
an intervention.
• Implementation science builds on existing research principles and
methods, but its focus is on external validity à it is attentitive to the
additional complexities that characterise real world contexts.
• Requires the integration of 7 specific considerations.
o Patient and public involvement: involving all relevant
stakeholders in all stages of the project.
o Contextual analysis: allows researchers to better understand
and map relevant characteristics of the setting in which the
intervention will be implemented. The information contributes
to effective intervention co-design and informs the choice of
contextually relevant implementation strategies.
o Implementation science-specific theoretical frameworks:
Guide parts or all of an implementation science sudy.
o Implementation strategies: facilitate adoption,
implementation, sustainability and scaling up of specific
interventions, programmes or practices.
o Effectiveness and implementation outcomes: concurrently
measured.
o Implementation sciencespecific designs: combine evaluation
of an intervention’s effectiveness and outcomes of
implementation efforts.
o Transdisciplinary research teams: complementary skill sets of
implementation scientists are aligned with the knowledge and
skills of other team members, incl. policy- and decisionmakers.
• To strengthen recognition of implementation science in Switzerland,
IMPACT was recently launched and pursues 4 major claims.
o To showcase implementation science healthcare projects
conducted by swiss healthcare researchers and institutions.
o To provide networking opportunities for implementation
science researchers and other interested stakeholders in
Switzerland.
o To provide implementation science training opportunities
o To leverage funding options for implementation science in
Switzerland.
- According to De Geest et al boosting the performance of the Swiss healthcare system requires
bridging ‘the valley of death’, which will involve increasing the research capacity for
implementational science.
o Implementation science needs to be recognised as an essential part of a high-
performing research enterprice, with high societal returns on investment.
2
, o As implementation science projects require competencies beyond the traditional
clinical research methods, researchers need opportunities both to develop
competencies and to learn the principles of implementation science.
o Implementation scientists should be involved early on in the design of clinical research
projects à potentially shorten not only the time to routine use of EB interventions, but
also enhance their sustainability after succesful implementation.
o Rigorous methods of attracting and developing stakeholder involvement in projects can
be fostered through the Swiss EUPATI National platform.
o Adequate funding mechanisms must be established to help fund implementation
science projects.
- Implementation science already promises to make clinical research far more cost-effective (by
shortening the time to routine use of results), the complexities of implementation science studies
need to be reflected in the fundin mechanisms.
- Strategies to apply implementation science methods to Swiss health research offer an excellent
return on investment. Designing studies to overcome translation barriers promises to remove
years from the current research process.
o In turn, this will maximise the entire Swiss research enterprise’s value for patients and
populations.
o In effect, it will bridge the valley of death.
ARTIKEL WHAT CAN IMPLEMENTATION SCIENCE DO FOR YOU? KEY SUCCESS
STORIES FROM THE FIELD”
- It explores how implementation science helps bridge the gap between research and practice by
ensuring that evidence-based health interventions are adopted, scaled, and sustained in real-
world care.
- Key examples of success:
o Chronic Disease Self-Management Programs (CDSMP): Empower patients to manage
long-term illnesses, spreading widely across the U.S. through community partnerships.
o Primary Care–Mental Health Integration: Collaborative care models for depression
improved outcomes and reduced suicide risk, especially in the U.S. Veterans Affairs
system.
o HIV Prevention (DEBI): Effective interventions were packaged and disseminated
nationwide, though sometimes criticized for being too top-down.
o Patient Safety Checklists: Reduced hospital-acquired infections significantly, saving
lives and costs when combined with leadership support and monitoring.
o Diabetes Prevention Program (DPP): Lifestyle interventions were successfully adapted
for community use, showing large-scale health benefits though with some challenges in
inclusivity.
- Lessons learned:
o A shared agenda among stakeholders and leadership support is essential.
o Conceptual frameworks (e.g., RE-AIM, REP) help guide implementation.
o Ongoing evaluation builds a strong case for sustaining interventions.
o Operational experts and frontline provider input ensure real-world fit.
o Adaptations are necessary while maintaining core intervention elements.
- Conclusion: Implementation science has strong potential to transform healthcare by improving
the uptake and sustainability of effective interventions, policies, and programs.
3
,RECORDING 1: IMPLEMENTATION SCIENCE – MAKING RESEARCH FINDINGS
MORE POWERFUL FOR CLINICAL USE
THE PROBLEM
- The leaky research pipeline: there is a lot of research waste.
o Research waste 1 à well described and existing measures against them.
§ If a project is done there is >50% designed without reference to systematic
reviews or existing evidence à projects being done that aren’t necessary or
aren’t embedded in literature.
§ >50% of publications have avoidable research flaws or biases à poor
methodologie.
§ 50% of research is never published in full.
§ 50% of the published papers are unusable or incompletely reported or both for
instance not enough information to replicate the research.
o Research waste 2:
§ If you have evidence, only a fraction of that evidence is implemented in the
clinical practice
§ Implementation science studies how to reduce research waste 2.
o It takes a mean of 17 years to get research evidence implemented.
- Increasing value and reducing research waste is an important goal in the scientific world.
- A lot of innovation is happening, not all of it is useful for implementation.
o “The best big idea is only going to be as good as its implementation”.
- “The valleys of death” = the gap between research and develepmoment and the trial world and
the real clinical world.
o 1 valley of death between university research institute and inddustry technology transfer.
o Another, even bigger valley of death is between industry technology transfer and the
clinical implementation.
o A lot of innovation takes place for example in biology, prevention, detection and
diagnosis, treatment, public health, if we then move into the real world we can see that
only a fraction (14%) ever arrives. The sustainability is even less.
o In the US: 85% of biomedical research is wasted and this implias a considerable
financial los that sum up to $268.4 billion US dollars.
§ This is a big problem.
- Tackling the valleys of death and the leaky research pipeline (both research waste 1 & 2) calls for
investment in better research infrastructure and also calls for new types of methodology à
implementation of implementation science.
o Example: innovation to reduce non-adherence to medications.
§ Patients not taking their medication results in 200.000 premature deaths a year
in Europe.
§ In Europe there are around 125 billion avoidable hospitalisations, emergency
care and outpation visits a year.
§ In research there have been investmensts done to tackle medication non-
adherence. A intervention namely ‘new medicine services’ has been done in the
UK. However the moment that this new service had been transfered to other
setting (being scaled up) à the effect waived.
§ In Switzerland there is a project called ‘myCare Start’, this starts from evidence
developped in ‘new medicine services’ and changing the intervention to work in
farmacies in Switzerland.
4
,THE POTENTIAL SOLUTION
- Implementation science: bridging the gap between trial and real world settings to implement and
sustain evidence-based interventions – overcoming the valleys of death.
o Example: moving from the trial to the real world: improving medication adherence using
insights of implementation science
§ Even when there is relevent information on the bookshelves and we want to
translate it to real world settings. The how to translate it to the real world settings
is not provided.
§ Implementation science wants to help to define the strength of evidence of
innovations or interventions that have been developped and will show the way
forward and how we can implement these interventions in real world settings.
- A commonly used definition: “the scientific study of methods to promote the systematic uptake
of research findings and other EBP into routine practice, and, hence, to improve the quality and
effectiveness of health services and care.”
- There are different names for implementation science depending on the place in the world.
o If you do a research for implementation science, you need to include all these words.
o But in 2019 a MeSH-term was introduced for Implemenation science à more easily
accesible.
- Implementation science has gained a lot of traction in health sciences because of the gap
between research and real world practices.
- Clinical research focusses primarily on producing information on the efficacy of interventions à
important to see if the intervention works.
o But you won’t get the true impact on population level because it has been done in highly
research settings.
o In order to get to system sustainability it takes a long road.
§ Effectiveness
§ Sustainibility
§ Scalability
5
,- Trial world: “could it work?”
o Typically, all the work is done in the trial world. It is necessary to see if a product /
innovation is efficacious, if its safe.
o A RCT is done, it is highly controlled, people are randomized over the groups, the
intervention is delivered by people who know how to deliver it.
o Keep things clear = a lot of investment to make sure that there isn’t a lot of heterogeneity.
You want to make sure that the intervention is done with high fidelity.
- Real world: “does it work and when?”
o If the question has been answered that a new intervention is efficacious you can move
into the real world.
o To get into the real world, we must show that this intervention also works in real settings.
This is done in pragmatic trials. You let the intervention deliver by those who normally
deliver care, patients who aren’t the highly selected patients, etc.
o Typically, in pragmatic trails à more variability is allowed in setting, population, people
who do the intervention, …
o You allow complexity in the system.
o If you are able to show effectiveness in a pragmatic trail à even in not so controlled
circumstances the intervention still holds its effect.
o If you don’t find an effect anymore in a pragmatic trial à there is much more variability in
the real world, OR in a lot of cases this has to do with the fact that there hasn’t been a lot
of attention in how to bridge the gap, there is a failed implementation for example there
is no fidelity or you have an intervention and you move into a real world setting where the
acceptability is low, ...
§ If you know what the barriers are, you will be able to try to understand the
barriers which you can then use to develop the implementation strategies.
- Daily clinical practice: “what works when and why?”
o To understand the mechanisms when you move from trial world settings into real world
settings.
o The focus is on embracing complexity.
o Focus on the implementation outcomes and the specific mechanisms how interaction,
intervention, implementation strategies and context result in a specific outcome or not.
- In implementation science we want to understand why there is variability in outcomes and
explain the differential effect.
6
,- Voltage drop / the decline effect = an intervention moves over the bridge and there is a decrease
in the effectiveness as you go from efficacy to effectiveness to dissemination.
o X-as = research stage, Y-as expected effect
- Program drift = you have an intervention that has been developed and you move over the bridge.
As you move over the bridge, the initial intervention is not being delivered with a lot of fidelity /
parts of the intervention are being changed. There is a drop in the effect of the intervention.
o X-as = time, Y-as = expected effect
- Implementation science combines a variety of methods and strategies for powerful real-world
translation.
o Implementation science is more complex than clinical research à more elements are
being combined in order to get a new innovation into real world settings.
- The Basel Heptagon of implementation science
o Key elements of implementation science to successfully cross from the trial world to real
world settings.
o We have the trial world where efficacy is being tested. In order to get to real world
settings a number of building blocks need to be combined.
§ Strength of evidence of intervention: if an intervention has weak strength of
evidence à different than an intervention that has been tested and proved as
level 1a or 1b. Important to look at where the evidence is placed.
§ Implementation science theories / frameworks / models
§ Contextual analysis: look at how the world works – barriers and facillitators.
§ Stakeholder involvement: strategy has to be made at the start.
§ Implementation strategies: strategies that are added to an intervention to help
people / places to use the intervention.
§ Implementation & effectiveness outcomes & process evaluation: we want to
understand the mechanics of how the intervention has landed in the real world.
§ Hybrid (& other IS) designs: the evaluation of implementation and effectiveness
outcomes are done in hybrid designs.
§ Transdisciplinary approach: different disciplines help. A team consists of
colleagues from clinical practice, researchers and stakeholders.
- Implementation science phases:
o We want to achieve succesful implementation to improve outcomes in real world
settings.
7
,o We start with developing a stakeholder strategy à allows us to involve stakeholders in all
the parts of the projects.
o Typically 2 phases:
§ Phase A:
• Contextual analysis
• Followed by intervention development / adaptation.
• Develop implementation strategies or bundles.
§ Phase B:
• Evaluation: hybrid designs
o Evaluating effectiveness and also implementation outcomes.
• Process evaluation: mixed methods study to understand how the
mechanics of how the intervention and implementation have landed in
real world settings and produced specific outcomes.
o The implementation pathway: you understand what happens when you go from trial to
real world settings.
§ “The thing “= the intervention à effectiveness research looks at whether the
thing works.
• 7P’s:
o Programs
o Practices
o Principles
o Procedures
o Products
o Pills
o Policies
§ Focus on not only the intervention, but we also add “the stuff” namely the
implementation strategies.
• How best to help people/place do the thing.
• Implementation strategies are the stuff we do to try to help
people/places do the thing – built around the intervention.
• Derived from what we learn from a contextual analysis.
• Main implementation outcomes are how much and how well they do the
thing.
8
, § After we can do an evaluation: not only effectiveness outcomes but also more
proximal outcomes.
o Proximal and distal implementation outcomes
§ Proximal outcomes are immediate – often easier to effect and measure
• Acceptability, appropriateness, adoption
• Acceptability and appropriateness you can test before you start with
your projects.
§ Distal outcomes are longer term – often harder to measure and influenced by
multiple factors.
• Sustainability, penetration
• Effectiveness outcomes can come before distal implementation
outcomes.
§ Acceptability = perception among stakeholders that an intervention is
agreeable.
§ Adoption (uptake): intention, initial decision, or action to try or employ an
innovation or EBP.
§ Fidelity = the degree to which an intervention was implemented as it was
designed in an original protocol, plan, or policy (+/- adherence).
§ Reach = the degree to which the population that is eligible to benefit from an
intervention actually receives it.
§ Sustainability = the extent to which an intervention is maintained or
institutionalized in a given setting.
o Intervention vs implementation strategy
§ Implementation strategies are methods or techniques used to enhance the
adoption, implementation, sustainment, and scale-up of an intervention (7Ps)
• But implementation strategies can include a bundle of implementation
interventions!
o Stakeholder involvement = cornerstone in the research cycle.
o Mapping context is essential in implementation science to:
§ Understand facilitators and barriers for implementation as well as practice
patterns
§ Inform intervention development
§ Inform choice of implementation and sustainability strategies
§ Allows the interpretation of your implementation and effectiveness outcomes.
§ Examples multilevel context factors:
• Attitudes and preferences
• Leadership
• Organizational support
9
, • Financial resources
• Societal relations / support
• Organizational culture and climate
• Organizational readiness to change
- 3 types of effectiveness-implementation Hybrid designs
o Hybrid type 1
§ Being used when strength of evidence of an innovation / practice has not been
established.
§ Early stages of establishing if an intervention is efficacious.
§ Primary aim = determine effectiveness of a clinical intervention
§ Secondary aim = better understand the context for implementation
o Hybrid type 2
§ A trial where there is some evidence already for an innovation, it has an effect
and it’s safe, but you don’t know how to implement it.
§ Primary aim = determine effectiveness of a clinical intervention
§ Co-primary aim. Determine feasibility and/or impact of an implementation
strategy.
o Hybrid type 3
§ An innovation or intervention has been proven to be effective in several RCT’s.
Evidence has been combined in a meta-analysis.
§ There are clusters that are assigned to specific implementation bundles. To look
at the impact of an implementation strategy.
§ Primary aim = determine impact of an implementation strategy
§ Secondary aim = assess clinical outcomes associated with implementation trial.
o Hybrid type 1, 2 and 3 to help us think through different combinations of effectiveness
and implementation research.
- Consideration for integration implementation science early in the research pipeline. Pragmatic
shift
o Typically, the transitional model sees implementation as something that is coming. The
clinical research team has finished work and then it’s time for implementing.
o But better to start early with including implementation science principles.
§ The implementation team can be part of the research team and can inspire the
clinical research team.
RECORDING 4: THE SMILE PROJECT
- Example: The SMILe Project – development, implementation and Testing of an Integrated Model
of Care for allogeneic Stem Cell Transplantation facilitated by eHealth – an effectiveness
implementation science study (2021 – 2025)
- Evaluation is a hybrid effectiveness-implementation RCT
- Phase A: context analysis to develop/adapt and implement evidence
o Started with a context & technology-acceptance analysis.
§ Stakeholders that were involved from the start
10
SESSIE 1 – 2 ARTIKELS + LESOPNAMES
DE GEEST ET AL: POWERING SWISS HEALTH CARE FOR THE FUTURE:
IMPLEMENTATION SCIENCE TO BRIDGE “THE VALLEY OF
DEATH”
- 2019 SAMS or Swiss Academy of Medical science bulletin addressed the rift between basic
scientific discoveries and their clinical use.
o “Valley of death” = distance between both.
§ Consists of well-researched, EB programmes, practices, procedures, products
and policies developed by health scientists that are now waiting on bookshelves
to be translated into real world settings.
§ 30 – 40% of patients do not receive treatments of proven efficacy, 20 – 25%
receive unnecessary or potentially harmful treatments.
o Same rift between clinical research and implementation of related health policies or
innovations in health services.
- 2019: report on improving patient safety and quality of care called for investment in
implementation science.
- Balas and Boren: 14% of published evidence is translated into clinical practice.
o Mean wait between innovation and application = 17 years.
o Implementation deficits contribute to excess research waste.
- 2 types of research waste:
o Research waste 1: results in a low proportion of the research initiated eventually
resulting in high-quality scientific evidence.
§ Research designed without reference to systematic reviews of the existing
evidence.
§ Research not published in full.
§ Studies with avoidable research flaws
§ Studies that are unusable, incompletely reported or both
§ Various measures have been implemented to reduce this type of waste, with
some success.
• Examples: obligation to register studies, widespread investment in
clinical research infrastructures for example clinical trial units,
guidelines supporting the quality of scientific reporting.
• But more measures are needed.
o Research waste 2: lack of effective and sustainable translation and implementation of
EB innovations from the trial word into daily clinical practice.
§ To guide the translation of well-conducted, well-reported studies into real-word
settings, an increased focus on “implementation science’ is needed and should
be added early in the research process.
• Implementation science = “the scientific study of methods to promote
the systematic uptake of research findings and other EB practices into
1
, routine practice, and, hence, to improve the quality and effectiveness of
health services and care”.
• Conducting and implementation science study implies not only a
scientific evaluation of effectiveness of an intervention in a real-world
setting, but also an evaluation of how and why it either works or fails in
the specific context in which it was tried.
• Evidence generated on effectiveness outcomes and from evaluation of
implementation pathways can subsequently be transferred to other
contexts to suport a more efficient implemenations and/or scaling up of
an intervention.
• Implementation science builds on existing research principles and
methods, but its focus is on external validity à it is attentitive to the
additional complexities that characterise real world contexts.
• Requires the integration of 7 specific considerations.
o Patient and public involvement: involving all relevant
stakeholders in all stages of the project.
o Contextual analysis: allows researchers to better understand
and map relevant characteristics of the setting in which the
intervention will be implemented. The information contributes
to effective intervention co-design and informs the choice of
contextually relevant implementation strategies.
o Implementation science-specific theoretical frameworks:
Guide parts or all of an implementation science sudy.
o Implementation strategies: facilitate adoption,
implementation, sustainability and scaling up of specific
interventions, programmes or practices.
o Effectiveness and implementation outcomes: concurrently
measured.
o Implementation sciencespecific designs: combine evaluation
of an intervention’s effectiveness and outcomes of
implementation efforts.
o Transdisciplinary research teams: complementary skill sets of
implementation scientists are aligned with the knowledge and
skills of other team members, incl. policy- and decisionmakers.
• To strengthen recognition of implementation science in Switzerland,
IMPACT was recently launched and pursues 4 major claims.
o To showcase implementation science healthcare projects
conducted by swiss healthcare researchers and institutions.
o To provide networking opportunities for implementation
science researchers and other interested stakeholders in
Switzerland.
o To provide implementation science training opportunities
o To leverage funding options for implementation science in
Switzerland.
- According to De Geest et al boosting the performance of the Swiss healthcare system requires
bridging ‘the valley of death’, which will involve increasing the research capacity for
implementational science.
o Implementation science needs to be recognised as an essential part of a high-
performing research enterprice, with high societal returns on investment.
2
, o As implementation science projects require competencies beyond the traditional
clinical research methods, researchers need opportunities both to develop
competencies and to learn the principles of implementation science.
o Implementation scientists should be involved early on in the design of clinical research
projects à potentially shorten not only the time to routine use of EB interventions, but
also enhance their sustainability after succesful implementation.
o Rigorous methods of attracting and developing stakeholder involvement in projects can
be fostered through the Swiss EUPATI National platform.
o Adequate funding mechanisms must be established to help fund implementation
science projects.
- Implementation science already promises to make clinical research far more cost-effective (by
shortening the time to routine use of results), the complexities of implementation science studies
need to be reflected in the fundin mechanisms.
- Strategies to apply implementation science methods to Swiss health research offer an excellent
return on investment. Designing studies to overcome translation barriers promises to remove
years from the current research process.
o In turn, this will maximise the entire Swiss research enterprise’s value for patients and
populations.
o In effect, it will bridge the valley of death.
ARTIKEL WHAT CAN IMPLEMENTATION SCIENCE DO FOR YOU? KEY SUCCESS
STORIES FROM THE FIELD”
- It explores how implementation science helps bridge the gap between research and practice by
ensuring that evidence-based health interventions are adopted, scaled, and sustained in real-
world care.
- Key examples of success:
o Chronic Disease Self-Management Programs (CDSMP): Empower patients to manage
long-term illnesses, spreading widely across the U.S. through community partnerships.
o Primary Care–Mental Health Integration: Collaborative care models for depression
improved outcomes and reduced suicide risk, especially in the U.S. Veterans Affairs
system.
o HIV Prevention (DEBI): Effective interventions were packaged and disseminated
nationwide, though sometimes criticized for being too top-down.
o Patient Safety Checklists: Reduced hospital-acquired infections significantly, saving
lives and costs when combined with leadership support and monitoring.
o Diabetes Prevention Program (DPP): Lifestyle interventions were successfully adapted
for community use, showing large-scale health benefits though with some challenges in
inclusivity.
- Lessons learned:
o A shared agenda among stakeholders and leadership support is essential.
o Conceptual frameworks (e.g., RE-AIM, REP) help guide implementation.
o Ongoing evaluation builds a strong case for sustaining interventions.
o Operational experts and frontline provider input ensure real-world fit.
o Adaptations are necessary while maintaining core intervention elements.
- Conclusion: Implementation science has strong potential to transform healthcare by improving
the uptake and sustainability of effective interventions, policies, and programs.
3
,RECORDING 1: IMPLEMENTATION SCIENCE – MAKING RESEARCH FINDINGS
MORE POWERFUL FOR CLINICAL USE
THE PROBLEM
- The leaky research pipeline: there is a lot of research waste.
o Research waste 1 à well described and existing measures against them.
§ If a project is done there is >50% designed without reference to systematic
reviews or existing evidence à projects being done that aren’t necessary or
aren’t embedded in literature.
§ >50% of publications have avoidable research flaws or biases à poor
methodologie.
§ 50% of research is never published in full.
§ 50% of the published papers are unusable or incompletely reported or both for
instance not enough information to replicate the research.
o Research waste 2:
§ If you have evidence, only a fraction of that evidence is implemented in the
clinical practice
§ Implementation science studies how to reduce research waste 2.
o It takes a mean of 17 years to get research evidence implemented.
- Increasing value and reducing research waste is an important goal in the scientific world.
- A lot of innovation is happening, not all of it is useful for implementation.
o “The best big idea is only going to be as good as its implementation”.
- “The valleys of death” = the gap between research and develepmoment and the trial world and
the real clinical world.
o 1 valley of death between university research institute and inddustry technology transfer.
o Another, even bigger valley of death is between industry technology transfer and the
clinical implementation.
o A lot of innovation takes place for example in biology, prevention, detection and
diagnosis, treatment, public health, if we then move into the real world we can see that
only a fraction (14%) ever arrives. The sustainability is even less.
o In the US: 85% of biomedical research is wasted and this implias a considerable
financial los that sum up to $268.4 billion US dollars.
§ This is a big problem.
- Tackling the valleys of death and the leaky research pipeline (both research waste 1 & 2) calls for
investment in better research infrastructure and also calls for new types of methodology à
implementation of implementation science.
o Example: innovation to reduce non-adherence to medications.
§ Patients not taking their medication results in 200.000 premature deaths a year
in Europe.
§ In Europe there are around 125 billion avoidable hospitalisations, emergency
care and outpation visits a year.
§ In research there have been investmensts done to tackle medication non-
adherence. A intervention namely ‘new medicine services’ has been done in the
UK. However the moment that this new service had been transfered to other
setting (being scaled up) à the effect waived.
§ In Switzerland there is a project called ‘myCare Start’, this starts from evidence
developped in ‘new medicine services’ and changing the intervention to work in
farmacies in Switzerland.
4
,THE POTENTIAL SOLUTION
- Implementation science: bridging the gap between trial and real world settings to implement and
sustain evidence-based interventions – overcoming the valleys of death.
o Example: moving from the trial to the real world: improving medication adherence using
insights of implementation science
§ Even when there is relevent information on the bookshelves and we want to
translate it to real world settings. The how to translate it to the real world settings
is not provided.
§ Implementation science wants to help to define the strength of evidence of
innovations or interventions that have been developped and will show the way
forward and how we can implement these interventions in real world settings.
- A commonly used definition: “the scientific study of methods to promote the systematic uptake
of research findings and other EBP into routine practice, and, hence, to improve the quality and
effectiveness of health services and care.”
- There are different names for implementation science depending on the place in the world.
o If you do a research for implementation science, you need to include all these words.
o But in 2019 a MeSH-term was introduced for Implemenation science à more easily
accesible.
- Implementation science has gained a lot of traction in health sciences because of the gap
between research and real world practices.
- Clinical research focusses primarily on producing information on the efficacy of interventions à
important to see if the intervention works.
o But you won’t get the true impact on population level because it has been done in highly
research settings.
o In order to get to system sustainability it takes a long road.
§ Effectiveness
§ Sustainibility
§ Scalability
5
,- Trial world: “could it work?”
o Typically, all the work is done in the trial world. It is necessary to see if a product /
innovation is efficacious, if its safe.
o A RCT is done, it is highly controlled, people are randomized over the groups, the
intervention is delivered by people who know how to deliver it.
o Keep things clear = a lot of investment to make sure that there isn’t a lot of heterogeneity.
You want to make sure that the intervention is done with high fidelity.
- Real world: “does it work and when?”
o If the question has been answered that a new intervention is efficacious you can move
into the real world.
o To get into the real world, we must show that this intervention also works in real settings.
This is done in pragmatic trials. You let the intervention deliver by those who normally
deliver care, patients who aren’t the highly selected patients, etc.
o Typically, in pragmatic trails à more variability is allowed in setting, population, people
who do the intervention, …
o You allow complexity in the system.
o If you are able to show effectiveness in a pragmatic trail à even in not so controlled
circumstances the intervention still holds its effect.
o If you don’t find an effect anymore in a pragmatic trial à there is much more variability in
the real world, OR in a lot of cases this has to do with the fact that there hasn’t been a lot
of attention in how to bridge the gap, there is a failed implementation for example there
is no fidelity or you have an intervention and you move into a real world setting where the
acceptability is low, ...
§ If you know what the barriers are, you will be able to try to understand the
barriers which you can then use to develop the implementation strategies.
- Daily clinical practice: “what works when and why?”
o To understand the mechanisms when you move from trial world settings into real world
settings.
o The focus is on embracing complexity.
o Focus on the implementation outcomes and the specific mechanisms how interaction,
intervention, implementation strategies and context result in a specific outcome or not.
- In implementation science we want to understand why there is variability in outcomes and
explain the differential effect.
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,- Voltage drop / the decline effect = an intervention moves over the bridge and there is a decrease
in the effectiveness as you go from efficacy to effectiveness to dissemination.
o X-as = research stage, Y-as expected effect
- Program drift = you have an intervention that has been developed and you move over the bridge.
As you move over the bridge, the initial intervention is not being delivered with a lot of fidelity /
parts of the intervention are being changed. There is a drop in the effect of the intervention.
o X-as = time, Y-as = expected effect
- Implementation science combines a variety of methods and strategies for powerful real-world
translation.
o Implementation science is more complex than clinical research à more elements are
being combined in order to get a new innovation into real world settings.
- The Basel Heptagon of implementation science
o Key elements of implementation science to successfully cross from the trial world to real
world settings.
o We have the trial world where efficacy is being tested. In order to get to real world
settings a number of building blocks need to be combined.
§ Strength of evidence of intervention: if an intervention has weak strength of
evidence à different than an intervention that has been tested and proved as
level 1a or 1b. Important to look at where the evidence is placed.
§ Implementation science theories / frameworks / models
§ Contextual analysis: look at how the world works – barriers and facillitators.
§ Stakeholder involvement: strategy has to be made at the start.
§ Implementation strategies: strategies that are added to an intervention to help
people / places to use the intervention.
§ Implementation & effectiveness outcomes & process evaluation: we want to
understand the mechanics of how the intervention has landed in the real world.
§ Hybrid (& other IS) designs: the evaluation of implementation and effectiveness
outcomes are done in hybrid designs.
§ Transdisciplinary approach: different disciplines help. A team consists of
colleagues from clinical practice, researchers and stakeholders.
- Implementation science phases:
o We want to achieve succesful implementation to improve outcomes in real world
settings.
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,o We start with developing a stakeholder strategy à allows us to involve stakeholders in all
the parts of the projects.
o Typically 2 phases:
§ Phase A:
• Contextual analysis
• Followed by intervention development / adaptation.
• Develop implementation strategies or bundles.
§ Phase B:
• Evaluation: hybrid designs
o Evaluating effectiveness and also implementation outcomes.
• Process evaluation: mixed methods study to understand how the
mechanics of how the intervention and implementation have landed in
real world settings and produced specific outcomes.
o The implementation pathway: you understand what happens when you go from trial to
real world settings.
§ “The thing “= the intervention à effectiveness research looks at whether the
thing works.
• 7P’s:
o Programs
o Practices
o Principles
o Procedures
o Products
o Pills
o Policies
§ Focus on not only the intervention, but we also add “the stuff” namely the
implementation strategies.
• How best to help people/place do the thing.
• Implementation strategies are the stuff we do to try to help
people/places do the thing – built around the intervention.
• Derived from what we learn from a contextual analysis.
• Main implementation outcomes are how much and how well they do the
thing.
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, § After we can do an evaluation: not only effectiveness outcomes but also more
proximal outcomes.
o Proximal and distal implementation outcomes
§ Proximal outcomes are immediate – often easier to effect and measure
• Acceptability, appropriateness, adoption
• Acceptability and appropriateness you can test before you start with
your projects.
§ Distal outcomes are longer term – often harder to measure and influenced by
multiple factors.
• Sustainability, penetration
• Effectiveness outcomes can come before distal implementation
outcomes.
§ Acceptability = perception among stakeholders that an intervention is
agreeable.
§ Adoption (uptake): intention, initial decision, or action to try or employ an
innovation or EBP.
§ Fidelity = the degree to which an intervention was implemented as it was
designed in an original protocol, plan, or policy (+/- adherence).
§ Reach = the degree to which the population that is eligible to benefit from an
intervention actually receives it.
§ Sustainability = the extent to which an intervention is maintained or
institutionalized in a given setting.
o Intervention vs implementation strategy
§ Implementation strategies are methods or techniques used to enhance the
adoption, implementation, sustainment, and scale-up of an intervention (7Ps)
• But implementation strategies can include a bundle of implementation
interventions!
o Stakeholder involvement = cornerstone in the research cycle.
o Mapping context is essential in implementation science to:
§ Understand facilitators and barriers for implementation as well as practice
patterns
§ Inform intervention development
§ Inform choice of implementation and sustainability strategies
§ Allows the interpretation of your implementation and effectiveness outcomes.
§ Examples multilevel context factors:
• Attitudes and preferences
• Leadership
• Organizational support
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, • Financial resources
• Societal relations / support
• Organizational culture and climate
• Organizational readiness to change
- 3 types of effectiveness-implementation Hybrid designs
o Hybrid type 1
§ Being used when strength of evidence of an innovation / practice has not been
established.
§ Early stages of establishing if an intervention is efficacious.
§ Primary aim = determine effectiveness of a clinical intervention
§ Secondary aim = better understand the context for implementation
o Hybrid type 2
§ A trial where there is some evidence already for an innovation, it has an effect
and it’s safe, but you don’t know how to implement it.
§ Primary aim = determine effectiveness of a clinical intervention
§ Co-primary aim. Determine feasibility and/or impact of an implementation
strategy.
o Hybrid type 3
§ An innovation or intervention has been proven to be effective in several RCT’s.
Evidence has been combined in a meta-analysis.
§ There are clusters that are assigned to specific implementation bundles. To look
at the impact of an implementation strategy.
§ Primary aim = determine impact of an implementation strategy
§ Secondary aim = assess clinical outcomes associated with implementation trial.
o Hybrid type 1, 2 and 3 to help us think through different combinations of effectiveness
and implementation research.
- Consideration for integration implementation science early in the research pipeline. Pragmatic
shift
o Typically, the transitional model sees implementation as something that is coming. The
clinical research team has finished work and then it’s time for implementing.
o But better to start early with including implementation science principles.
§ The implementation team can be part of the research team and can inspire the
clinical research team.
RECORDING 4: THE SMILE PROJECT
- Example: The SMILe Project – development, implementation and Testing of an Integrated Model
of Care for allogeneic Stem Cell Transplantation facilitated by eHealth – an effectiveness
implementation science study (2021 – 2025)
- Evaluation is a hybrid effectiveness-implementation RCT
- Phase A: context analysis to develop/adapt and implement evidence
o Started with a context & technology-acceptance analysis.
§ Stakeholders that were involved from the start
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