13.Qualitative02.Implementation science - sporedata/researchdesigneR GitHub Wiki

• When there is ample evidence in support of a healthcare practice (therapy, diagnostic tool, etc.), but that information still hasn't moved to clinical practice. For example, we might know that a certain behavioral therapy unquestionably helps patients, but most clinicians and hospitals have not added that to their daily routine.
• When there is ample evidence that a given healthcare practice does not work, but clinicians still use it, then de-implementation protocols can be applied.
• Used in exploring the effects of important Medicare policy changes on physician practices and patient outcomes. Researchers have applied implementation science to study healthcare disparities, across topics and settings such as obesity, mental illness, and primary care services [6]

1. Ample evidence in support of the clinical practice.
2. Suboptimal implementation of that practice in routine clinical settings.

Implementation Science protocols are used to understand the reasons why the implementation is not happening, and then change the scenario to enhance adherence to increase the use of that clinical practice. Implementation Science methods are usually focused on mixed methods, meaning that they will use qualitative techniques (interviews, focus groups, ethnographic observations) combined with quantitative methods (analysis of EHR data, cohorts, trials, etc.). Implementation Science 3.0

The first step is to choose an initial implementation framework, which will usually be composed of components from several existing frameworks [1]. This framework is then revised during the project to adapt to local conditions. For instance, the Health Equity Implementation Framework showcases one way to modify an implementation framework to better assess health equity determinants as well [6].

An effectiveness-implementation hybrid design takes a dual focus a priori in assessing clinical effectiveness and implementation. There are three hybrid types. The key to hybrid designs 1, 2, and 3 is that the designs are progressively merging the assessment of effectiveness and implementation.

Effectiveness is about comparing two or more interventions (usually a treatment). Implementation comes from the assumption that one intervention is unarguably better than the other, and now the question it asks is how you take that evidence and implement it in clinical practice. Surprisingly, not only the vast majority of interventions we know to work from research studies actually don't get to patients, even after more than a decade. Implementation science tries to change that.

Hybrid designs 1 through 3 progressively blend the effectiveness and implementation testing. For example, in type I, one does effectiveness first and gather info on implementation as a secondary task (but you don't test different forms of implementation). In hybrid type II, you test both effectiveness and implementation at the same time. That might seem contradictory, since in order to implement you need to be sure that it is effective. The answer is that you might know that it works in general, but might want to test it for a specific subgroup where effectiveness might be questionable. Then, for type III, you switch the focus from effectiveness to implementation, where your primary focus is on implementation, while you might be testing effectiveness as a secondary goal. So, for example, you would randomize an implementation strategy, and just collect info on effectiveness but without a formal testing.

• StaRi

See corresponding packages for qualitative or mixed methods.

• Qualitative or mixed methods.
• Causal analyses
• Randomized trials, preferably two-stage preference trials (inherently valuable for Implementation Science studies) or stepped-wedge trials (both tests and implements the intervention at the same time).

1. Books

   • Dissemination and Implementation Research in Health: Translating Science to Practice [2].
   • Implementation Science 3.0 [3].

2. Articles

   • Implementation science in healthcare: Introduction and perspective
   • The health equity implementation framework: proposal and preliminary study of hepatitis C virus treatment
   • ACC/AHA/NHLBI guidelines for optimal implementation practices [4].
   • Agile CFIR, a fairly popular Implementation Science framework [5].
   • Common references to Qualitative methods.

3. Videos and courses

   • Online Certificate in Implementation Science.

See corresponding packages for qualitative or mixed methods.

[1] Nilsen P. Making sense of implementation theories, models and frameworks. Implementation science. 2015 Dec;10(1):53.

[2] Brownson RC, Colditz GA, Proctor EK, editors. Dissemination and Implementation Research in Health: Translating Science to Practice. Oxford University Press; 2017 Dec 5.

[3] Albers B, Shlonsky A, Mildon R, editors. Implementation Science 3.0. Springer; 2020.

[4] Chan WV, Pearson TA, Bennett GC, Cushman WC, Gaziano TA, Gorman PN, Handler J, Krumholz HM, Kushner RF, MacKenzie TD, Sacco RL. ACC/AHA special report: clinical practice guideline implementation strategies: a summary of systematic reviews by the NHLBI Implementation Science Work Group: a report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines. Journal of the American College of Cardiology. 2017 Feb 28;69(8):1076-92.

[5] Keith RE, Crosson JC, O’Malley AS, Cromp D, Taylor EF. Agile CFIR, a fairly popular Implementation Science framework. Implementation Science. 2017 Dec 1;12(1):15.

[6] Woodward EN, Matthieu MM, Uchendu US, Rogal S, Kirchner JE. The health equity implementation framework: proposal and preliminary study of hepatitis C virus treatment. Implementation Science. 2019 Dec;14:1-8.