MétaCan
Menu
Back to cohort
Record W3107912902 · doi:10.1186/s12913-021-06501-5

Development of an Implementation Process Model: a Delphi study

2021· article· en· W3107912902 on OpenAlexaff
Gillian Parker, Monika Kastner, Karen Born, Whitney Berta

Bibliographic record

VenueBMC Health Services Research · 2021
Typearticle
Languageen
FieldHealth Professions
TopicHealth Policy Implementation Science
Canadian institutionsNorth York General HospitalInstitute for Work & HealthUniversity of Toronto
Fundersnot available
KeywordsDelphi methodKnowledge translationProcess (computing)Process managementContext (archaeology)Knowledge managementHealth informaticsScope (computer science)Nursing researchHealth administrationStakeholderHealth careComputer scienceMedicineManagement scienceNursingPublic healthEngineeringPolitical sciencePublic relations

Abstract

fetched live from OpenAlex

BACKGROUND: There is general scarcity of research on key elements of implementation processes and the factors which impact implementation success. Implementation of healthcare interventions is a complex process. Tools to support implementation can facilitate this process and improve effectiveness of the interventions and clinical outcomes. Understanding the impact of implementation support tools is a critical aspect of this process. The objective of this study was to solicit knowledge and agreement from relevant implementation science and knowledge translation healthcare experts in order to develop a process model of key elements in the implementation process. METHODS: A two round, modified Delphi study involving international experts in knowledge translation and implementation (researchers, scientists, professors, decision-makers) was conducted. Participants rated and commented on all aspects of the process model, including the organization, content, scope, and structure. Delphi questions rated at 75% agreement or lower were reviewed and revised. Qualitative comments supported the restructuring and refinement. A second-round survey followed the same process as Round 1. RESULTS: Fifty-four experts participated in Round 1, and 32 experts participated in Round 2. Twelve percent (n = 6) of the Round 1 questions did not reach agreement. Key themes for revision and refinement were: stakeholder engagement throughout the process, iterative nature of the implementation process; importance of context; and importance of using guiding theories or frameworks. The process model was revised and refined based on the quantitative and qualitative data and reassessed by the experts in Round 2. Agreement was achieved on all items in Round 2 and the Delphi concluded. Additional feedback was obtained regarding terminology, target users and definition of the implementation process. CONCLUSIONS: High levels of agreement were attained for all sub-domains, elements, and sub-elements of the Implementation Process Model. This model will be used to develop an Implementation Support Tool to be used by healthcare providers to facilitate effective implementation and improved clinical outcomes.

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 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)0.018
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.074
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0180.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0030.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.748
GPT teacher head0.779
Teacher spread0.032 · 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 teacher head, not a consensus.

Study designQualitative
Domainnot available
GenreEmpirical

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

Citations42
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueBMC Health Services ResearchSame topicHealth Policy Implementation ScienceFrench-language works237,207