“Clearly they are in the circle of care, but . . .”: A qualitative study exploring perceptions of personal health information sharing with community pharmacists in an integrated care model
Bibliographic record
Abstract
BACKGROUND: Ontario's Health Links approach to care is an integrated care model designed to optimize care for patients with complex needs. Currently, community pharmacists have no formalized role. This study aimed to explore stakeholders' perceptions about privacy and its impact on community pharmacists' involvement with integrated care models. METHODS: A qualitative study using semistructured telephone-based interviews was conducted. Participants worked in Ontario as pharmacists, providers in Health Links or team-based models or decision-makers in Health Links or health regions. Thematic analysis followed the Qualitative Analysis Guide of Leuven. RESULTS: Twenty-two participants were interviewed, and all but one commented on privacy or information sharing in integrating community pharmacists with integrated care models. The 4 themes identified were as follows: 1) what does the circle of care look like? 2) value of sharing information, 3) uncertainty of what information to share and 4) perceptions on how to share information. INTERPRETATION: The concerns surrounding privacy of personal health information and who is included in the circle of care represented an important barrier for integration. Enablers to mitigate privacy concerns included relationship building between community pharmacists, patients and other health care professionals and mutual access to information-sharing platforms such as electronic health records. CONCLUSION: Providers' and decision-makers' perceptions about community pharmacists and privacy affect information sharing and are incongruent with Ontario's Personal Health Information Protection Act. Education is needed for health care professionals on legislation, especially as health systems move towards integrated care models to improve care. Can Pharm J (Ott) 2020;153:xx-xx.
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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 | 0.018 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.010 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".