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Record W3008782492 · doi:10.1186/s12913-020-4935-y

Context, complexity and process in the implementation of evidence-based innovation: a realist informed review

2020· review· en· W3008782492 on OpenAlexaff
Karen Dryden‐Palmer, Christopher S. Parshuram, Whitney Berta

Bibliographic record

VenueBMC Health Services Research · 2020
Typereview
Languageen
FieldHealth Professions
TopicHealth Policy Implementation Science
Canadian institutionsInstitute for Clinical Evaluative SciencesSickKids FoundationHospital for Sick ChildrenUniversity of Toronto
Fundersnot available
KeywordsPsycINFOHealth informaticsContext (archaeology)Nursing researchKnowledge managementProcess (computing)Knowledge translationComputer scienceHealth administrationHealth careData scienceMEDLINEManagement scienceMedicineProcess managementPublic healthNursing

Abstract

fetched live from OpenAlex

BACKGROUND: This review of scholarly work in health care knowledge translation advances understanding of implementation components that support the complete and timely integration of new knowledge. We adopt a realist approach to investigate what is known from the current literature about the impact of, and the potential relationships between, context, complexity and implementation process. METHODS: Informed by two distinct pathways, knowledge utilization and knowledge translation, we utilize Rogers' Diffusion of Innovations theory (DOI) and Harvey and Kitson's integrated- Promoting Action on Research Implementation in Health Service framework (PARIHS) to ground this review. Articles from 5 databases; Medline, Scopus, PsycInfo, Web of Science, and Google Scholar and a search of authors were retrieved. Themes and patterns related to these implementation components were extracted. Literature was selected for inclusion by consensus. Data extraction was iterative and was moderated by the authors. RESULTS: A total of 67 articles were included in the review. Context was a central component to implementation. It was not clear how and to what extent context impacted implementation. Complexity was found to be a characteristic of context, implementation process, innovations and a product of the relationship between these three elements. Social processes in particular were reported as influential however; descriptions of how these social process impact were limited. Multiple theoretical and operational models were found to ground implementation processes. We offer an emerging conceptual model to illustrate the key discoveries. CONCLUSIONS: The review findings indicate there are dynamic relationship between context, complexity and implementation process for enhancing uptake of evidence-based knowledge in hospital settings. These are represented in a conceptual model. Limited empiric evidence was found to explain the nature of the relationships.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.043
metaresearch head score (Gemma)0.159
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.043
Threshold uncertainty score0.230

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0430.159
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0040.004
Bibliometrics0.0160.015
Science and technology studies0.0020.005
Scholarly communication0.0120.015
Open science0.0030.005
Research integrity0.0060.005
Insufficient payload (model declined to judge)0.0030.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.929
GPT teacher head0.796
Teacher spread0.133 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations135
Published2020
Admission routes1
Has abstractyes

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