“I think like if Albert Einstein and Superman had a baby, that's what it would take”: The experiences and perceptions of community and hospital healthcare professionals in a seniors’ patient navigator program
Bibliographic record
Abstract
Introduction The success of new patient navigation programs have mostly been described from the perspectives of patient outcomes. Little is known about how patient navigators interact with healthcare professionals in the community and in hospital settings. Methods A qualitative study using a phenomenological analysis was undertaken to depict the lived experiences of Ontario (Canada) healthcare providers who have interacted with a patient navigator. Semi-structured interviews were conducted with 42 healthcare professionals, including frontline care providers ( n = 25) and administrators ( n = 16) from hospital ( n = 21) and community care settings ( n = 21). Results Participants’ experiences were reflected in one overarching theme: role clarity and three emergent themes related to the overarching theme: (i) concerns over accountability of patient care (ii) trust (iii) attainable-but-not. Participants described an inconsistent understanding of the role of patient navigators which led to uncertainty regarding their role in patient care. The current nature of the healthcare system influenced participants’ belief in the sustainability of patient navigation model of care. Despite these experiences, participants felt that patient navigators could help healthcare providers care for patients by preventing potential crises from developing and enhancing their knowledge about services. Discussion This study expands our understanding of patient navigation programs by exploring the experiences and perceptions of healthcare professionals, thereby providing new perspectives into components that support the successful health outcomes of older adults being supported by a patient navigator. The implications of findings for research, clinical practice, and policy are described.
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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 | 0.007 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.010 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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".