Implementation Science: Improving Evidence-Based Practice and Healthcare Quality

Implementation Science: Improving Evidence-Based Practice and Healthcare Quality

Implementation Science: The Key to Optimizing Health Outcomes around the Globe

What does it take to increase patient satisfaction and health outcomes across the globe? How can research address real-life settings and target users of research, not only the pure production of knowledge? Is controlling for research variables in laboratory settings and recruiting participants who would benefit from a treatment enough? To answer such questions and the demands of today’s healthcare complexity, implementation science is becoming a vital tool in medical environments.

Implementation science is an emerging research area, which has the potential to optimize health systems throughout the globe. Its primary goals are to implement evidence-based interventions in practice settings and improve quality services at different levels of the healthcare system (e.g., patients, providers, researchers, policymakers). In fact, one of the primary definitions describes implementation science as “the scientific study of methods to promote the systematic uptake of research findings and other evidence-based programs into routine practice, and, hence, to improve the quality and effectiveness of health services” (Bauer et al., 2015).

Principles of Implementation Science: Making Sense of Complex Terminology

Nevertheless, how can stakeholders understand the basics of implementation science when the complexity of today’s research settings leads to the conceptualization of numerous ideas and terminology? For example, terms such as implementation science, knowledge translation, and quality improvement are almost overlapping. Furthermore, variables such as feasibility, adoption, and sustainability are often misinterpreted.

To specify the basic principles of implementation science, researchers should focus on assessing existing models instead of developing disconnected theoretical frameworks, which solely suit their research goals. Implementation science, in particular, requires solid theoretical foundations, so continuous testing is essential (Bauer et al., 2015). As implementation science targets the underutilization of an evidence-based strategy or interventions that prove to be successful, researchers should consider aspects, such as implementation barriers, success factors, processes of implementation, results, and sustainability. In other words, implementation science aims to understand what, why, and how research can improve the use of evidence-based programs in practice settings. To assess the effectiveness of a program, implementation science should engage stakeholders (e.g., populations that will be influenced by an intervention in real-world settings) and focus on the local context (e.g., the economics of implementation, epidemiological conditions, legal environment), as well as the structure of the actual system (e.g., non-governmental roles, private providers, etc.). The main goal is to enhance the spread of practices that can benefit psychosocial, medical, and financial interventions in practice.


Integrating Implementation Science within Practice Settings


Implementation Science Research:

Implementation science research is a complex process, which requires trans-disciplinary efforts and mixed methods. Through effectiveness-implementation hybrid trials, participatory action research, and models of change, implementation science research focuses not only on the effectiveness of an intervention but on rates and quality of use (e.g., the use of beta-blockers in myocardial infarction). Just like any other research, implementation science researchers must define a clear implementation research question. Also, they should define the primary audience of research, as well as influencing variables (e.g., implementation personnel) and outcomes (e.g., feasibility) (Peters et al., 2013). Note that to evaluate evidence-based practices in routine care, three types of evaluation exist in research settings:

  1. Process evaluation, which describes the use of an evidence program without providing feedback or change (e.g., observational study);
  2. Formative evaluation, which is included in the study hypothesis to improve the actual implementation process;
  3. Summative evaluation, assesses the impact and economic outcomes of an intervention (Bauer et al., 2015).

An example of formative evaluation is an implementation trial designed to increase the use of alcohol use disorder pharmacology in primary care. Interestingly, previous interviews with patients and providers have led to the categorization of the following barriers to implementation: lack of confidence in medication effectiveness; lack of skills; perceived low demand. Such barriers indicate the need for educational and marketing interventions tailored to both providers and patients. Some of the implementation strategies included in the trial included covered access to peer experts, feedback on prescribing methods, and direct-to-consumer mailing lists. Note that this particular implementation trial was assessed via interrupted time-series design with controls, with prescribing rates being monitored for nine months.

Theoretical Knowledge and the Science of Spread:

One of the most successful methods to integrate implementation science into research and enhance its sustainability is to acknowledge that all participants should be ready to change and optimize health value (e.g., consumers, sponsors, policymakers, and front-line providers). Researchers should also analyze why some innovations manage to spread while others fail (Bodenheimer, 2007). For instance, only six years after Apple had introduced the iPod, more than 88 million devices were sold. In contrast, although it was proven in 1601 that lemon juice could prevent scurvy, it was in 1795 when the British navy finally adopted this health innovation.

  • Note that one of the most influential theories to describe the spread of innovation is Everett Rogers’ Diffusion of Innovations theory. Rogers analyzes why a health campaign in Peru to prevent water-borne infections, and infant mortality failed. He claims that for an innovation to spread, an effective communication channel should be established to convince users that the innovation is better than the status quo. Innovators should analyze the structure of the social system and allow some time for the innovation to take off, usually described by an S-shaped curve. Interestingly, Rogers classifies people and their desire to change in the following categories: early adopters, early majority, late majority, and laggards.
  • Another important concept in implementation science is the tipping point described by Malcolm Gladwell. Gladwell claims that innovators and leaders should find a sticky message to tackle the practical concerns of health professionals who are not innovators or early adopters (e.g., “This change will help get you home half an hour earlier every day.”).
  • When it comes to the human factor in the science of spread, Paul Plsek also plays a crucial role in categorizing people and their willingness to change. Plsek establishes the following groups: pre-contemplation or those ready to consider a change; contemplation or those who are considering a change; action or those doing a concrete change; and maintenance or those who have made a change and are ready to continue it.
  • While innovators are fundamental to fostering the spread of innovations, we should note that the healthcare system is one working unity. Moreover, Sarah Fraser claims that the implementation of science is a continuous project, and innovators should not look down on the majority of people because the so-called laggards might be the pragmatists that know how the system works and hold it together (e.g., providers who work with patients daily).

Implementation science should include all those involved in the implementation process; from managers implementing quality improvement programs and policymakers that need evidence-based information to patients who need to change their behavior and the public.


Implementation Science: In a Nutshell

Given the abundance of scientific knowledge and publications, implementation science is becoming an essential tool to bridge the gap between research and care and optimize health outcomes across the globe. Alarmingly, according to data, any evidence-based practice can take up to 17 years to be incorporated into routine care; only half of the practices that get implemented manage to reach widespread clinical use (Bauer et al., 2015). This gap often leads to misused funding, poor outcomes, low-quality care, and legal issues. Previously, researchers thought that mere publication of results would lead to the adoption of a novel evidence-based program; this idealistic view was replaced by the idea that comprehensive real-time datasets could be enough to implement knowledge in quality care. Now, implementation science research aims to employ mixed methods to understand how interventions work in real-world conditions in order to improve quality services, health outcomes, patient satisfaction, and reimbursements across the globe. Researchers must focus not only on the effectiveness of an intervention but its quality use. Implementation science must focus on the local context, the system, and all the stakeholders affected by the implementation of a novel evidence-based intervention. For example, while pioneers and leaders can enhance the spread of scientific innovations, pragmatists and front-line providers are those who know how the system works and can help ideas transform practice settings. Implementation science is the missing link, which can help academic findings translate into public health benefits and high-quality care.

To sum up, implementation science is an emerging research field aiming to close the gap between medical research and practice settings. As today’s healthcare systems are highly demanding and dynamic, evidence-based strategies supported by implementation science research become crucial to optimize healthcare value around the globe.


  1. Bauer, M., Damschroder, L., Hagedorn, H., Smith, J., & Kilbourne, A. (2015). An introduction to implementation science for the non-specialist. BMC Psychology, 3 (1).
  2. Bodenheimer, T. (2007). The Science of Spread: How Innovations in Care Become the Norm.
  3. Peters, D., Adam, T., Alonge, O., Agyepong, I., & Tran, N. (2013). Implementation research: what it is and how to do it.
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