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Record W2806926107 · doi:10.1186/s12913-018-3163-1

Applying the consolidated framework for implementation research to identify barriers affecting implementation of an online frailty tool into primary health care: a qualitative study

2018· article· en· W2806926107 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

VenueBMC Health Services Research · 2018
Typearticle
Languageen
FieldHealth Professions
TopicHealth Policy Implementation Science
Canadian institutionsInstitute of Population and Public HealthNova Scotia Health AuthorityDalhousie University
FundersCanadian Frailty Network
KeywordsImplementation researchMedicineHealth informaticsNursing researchQualitative researchHealth administrationContext (archaeology)Health services researchIntervention (counseling)NursingRelevance (law)Health carePublic healthMedical educationPsychological intervention

Abstract

fetched live from OpenAlex

BACKGROUND: Frailty is associated with multi-system deterioration, and typically increases susceptibility to adverse events such as falls. Frailty can be better managed with early screening and intervention, ideally conducted in primary health care (PHC) settings. This study used the Consolidated Framework for Implementation Research (CFIR) as an evaluation framework during the second stage piloting of a novel web-based tool called the Frailty Portal, developed to aid in the screening, identification, and care planning of frail patients in community PHC. METHODS: This qualitative study conducted semi-structured key informant interviews with a purposive sample of PHC providers (family physicians, nurse practitioners) and key PHC stakeholders who were administrators, decision makers and staff. The CFIR was used to guide data collection and analysis. Framework Analysis was used to determine the relevance of the CFIR constructs to implementing the Frailty Portal. RESULTS: A total of 17 interviews were conducted. The CFIR-inspired interview questions helped clarify critical aspects of implementation that need to be addressed at multiple levels if the Frailty Portal is to be successfully implemented in PHC. Finding were organized into three themes 1) PHC Practice Context, 2) Intervention attributes affecting implementation, and 3) Targeting providers with frail patients. At the intervention level the Frailty Portal was viewed positively, despite the multi-level challenges to implementing it in PHC practice settings. Provider participants perceived high opportunity costs to using the Frailty Portal due to changes they needed to make to their practice routines. However, those who had older patients, took the time to learn how to use the Frailty Portal, and created processes for sharing tasks with other PHC personnel become proficient at using the Frailty Portal. CONCLUSIONS: Structuring our evaluation around the CFIR was instrumental in identifying multi-level factors that will affect large-scale adoption of the Frailty Portal in PHC practices. Incorporating CFIR constructs into evaluation instruments can flag factors likely to impede future implementation and impact the effectiveness of innovative practices. Future research is encouraged to identify how best to facilitate changes in PHC practices to address frailty and to use implementation frameworks that honor the complexity of implementing innovations in PHC.

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)0.085
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science 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 score0.115
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0850.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.005
Science and technology studies0.0120.000
Scholarly communication0.0000.001
Open science0.0020.001
Research integrity0.0000.002
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 head0.630
GPT teacher head0.782
Teacher spread0.153 · 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