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Record W4286486503 · doi:10.1186/s43058-022-00315-0

The effectiveness of champions in implementing innovations in health care: a systematic review

2022· review· en· W4286486503 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueImplementation Science Communications · 2022
Typereview
Languageen
FieldHealth Professions
TopicHealth Policy Implementation Science
Canadian institutionsInstitut du Savoir MontfortOttawa Public HealthOttawa HospitalMontfort HospitalUniversity of Ottawa
FundersCanadian Institutes of Health ResearchUniversity of Ottawa
KeywordsSystematic reviewHealth careMedicineRisk analysis (engineering)Management scienceBusinessMEDLINEEngineeringPolitical scienceEconomicsEconomic growth

Abstract

fetched live from OpenAlex

BACKGROUND: Champions have been documented in the literature as an important strategy for implementation, yet their effectiveness has not been well synthesized in the health care literature. The aim of this systematic review was to determine whether champions, tested in isolation from other implementation strategies, are effective at improving innovation use or outcomes in health care. METHODS: The JBI systematic review method guided this study. A peer-reviewed search strategy was applied to eight electronic databases to identify relevant articles. We included all published articles and unpublished theses and dissertations that used a quantitative study design to evaluate the effectiveness of champions in implementing innovations within health care settings. Two researchers independently completed study selection, data extraction, and quality appraisal. We used content analysis and vote counting to synthesize our data. RESULTS: After screening 7566 records titles and abstracts and 2090 full text articles, we included 35 studies in our review. Most of the studies (71.4%) operationalized the champion strategy by the presence or absence of a champion. In a subset of seven studies, five studies found associations between exposure to champions and increased use of best practices, programs, or technological innovations at an organizational level. In other subsets, the evidence pertaining to use of champions and innovation use by patients or providers, or at improving outcomes was either mixed or scarce. CONCLUSIONS: We identified a small body of literature reporting an association between use of champions and increased instrumental use of innovations by organizations. However, more research is needed to determine causal relationship between champions and innovation use and outcomes. Even though there are no reported adverse effects in using champions, opportunity costs may be associated with their use. Until more evidence becomes available about the effectiveness of champions at increasing innovation use and outcomes, the decision to deploy champions should consider the needs and resources of the organization and include an evaluation plan. To further our understanding of champions' effectiveness, future studies should (1) use experimental study designs in conjunction with process evaluations, (2) describe champions and their activities and (3) rigorously evaluate the effectiveness of champions' activities. REGISTRATION: Open Science Framework ( https://osf.io/ba3d2 ). Registered on November 15, 2020.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.082
metaresearch head score (Gemma)0.011
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.768
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0820.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0020.017
Science and technology studies0.0060.001
Scholarly communication0.0000.001
Open science0.0050.003
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.688
GPT teacher head0.764
Teacher spread0.076 · 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