A120 A HUMAN-CENTERED DESIGN APPROACH TO THE DEVELOPMENT OF A VACCINE IMPLEMENTATION STRATEGY IN PATIENTS WITH INFLAMMATORY BOWEL DISEASE
Bibliographic record
Abstract
Abstract Background Vaccination uptake amongst patients with inflammatory bowel disease (IBD) remains suboptimal. Our previous study assessed perceived barriers and solutions related to implementation of evidence-based guidelines for vaccine preventable illness (VPI). Barriers included limited time, lack of access to a family physician, and incomplete understandings of coverage/access to vaccines. Aims The aim of this study was to use human-centered design (HCD) to design a vaccine implementation program in patients with IBD. Methods The HCD approach consisted of multiple phases. Phase 1 (discovery and define) consisted of semi-structured interviews of healthcare providers. Phase 1 also included the development of a context-specific patient journey map of the processes involved in accessing vaccines. This map was developed in collaboration with a multidisciplinary IBD team. Phase 2 involved identifying common barriers and facilitators through thematic analysis and journey mapping. In Phase 3, these analyses were used to design an implementation strategy for evidence-based management of VPI in the local health system context. Results Twelve interviews (including 11 gastroenterologists and one IBD nurse practicing in Nova Scotia and New Brunswick) were conducted. Mean participant age was 45.1 years, with 63.6% identifying practice in an urban/academic setting compared to a rural/community setting (36.4%). Lack of access to a family physician, limited time, vaccine hesitancy, and incomplete understanding of coverage/access to vaccines were among the barriers identified. Using facilitator themes as well as the journey mapping process, a proposal for an early implementation strategy prototype was designed. Prototype development involved collaborative partnership with a third-party patient support program to overcome various barriers identified in our surveys. Conclusions Barriers to implementation of evidence-based guidelines for management of VPI are well documented. The use of HCD to design an effective implementation strategy that is sensitive to the local healthcare context holds potential to increase access to and uptake of high quality, evidence-based VPI management. In future studies, the implementation-effectiveness of the implementation strategy (model prototype) will be evaluated and compared to standard of care. Funding Agencies None
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.052 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".