Adult Occupational Therapy and Physiotherapy Services in the Kivalliq Region of Nunavut: Feasibility of Mapping the Client Journey
Bibliographic record
Abstract
Since 2000, following a community needs assessment, the Government of Nunavut has funded and Ongomiizwin – Health Services has coordinated Occupational Therapy (OT) and Physiotherapy (PT) services in the Kivalliq Region of Nunavut. There has been no formal evaluation since the inception. The student researcher conducted a feasibility study on client journey mapping with adult Inuit OT and PT clients. Using program utilization data, descriptive statistics were used to identify adult OT and PT clients with high utilization of services to determine clients for journey mapping. Client journey mapping is a methodology that can help us to understand a series of health care events by exploring the patient experience from their perspective and looks for opportunities to make improvements. The Managing Two Worlds Together Patient Journeys workbook (Kelly, Dwyer, et al., 2016) was adapted to focus on OT and PT services, and for use in Nuanvut with Inuit OT and PT clients. Relevant areas of focus for feasibility studies were selected as the method to determine feasibility of client journey mapping with OT and PT clients in the region. The adapted client journey mapping tool was found to be feasible for ongoing program evaluation and could be considered for use in other regions of Nunavut. Further suggestions to adapt the tool incorporating Inuit Qaujimajatuqangit (IQ) principles (Inuit traditional knowledge) and aspects of cultural safety and decolonization frameworks were proposed. Program utilization data and the adapted client journey mapping tool can provide additional knowledge on OT and PT adult services for program improvement.
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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 | 0.011 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| 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".