Prioritization of patients access to outpatient augmentative and alternative communication services in Quebec: a decision tool
Bibliographic record
Abstract
A large number of people living with a chronic disability wait a long time to access publicly funded rehabilitation services such as Augmentative and Alternative Communication (AAC) services, and there is no standardized tool to prioritize these patients. We aimed to develop a prioritization tool to improve the organization and access to the care for this population. In this sequential mixed methods study, we began with a qualitative phase in which we conducted semi-structured interviews with 14 stakeholders including patients, their caregivers, and AAC service providers in Quebec City, Canada to gather their ideas about prioritization criteria. Then, during a half-day consensus group meeting with stakeholders, using a consensus-seeking technique (i.e. Technique for Research of Information by Animation of a Group of Experts), we reached consensus on the most important prioritization criteria. These criteria informed the quantitative phase in which used an electronic questionnaire to collect stakeholders’ views regarding the relative weights for each of the selected criteria. We analyzed these data using a hybrid quantitative method called group based fuzzy analytical hierarchy process, to obtain the importance weights of the selected eight criteria. Analyses of the interviews revealed 48 criteria. Collectively, the stakeholders reached consensus on eight criteria, and through the electronic questionnaire they defined the selected criteria’s importance weights. The selected eight prioritization criteria and their importance weights are: person’s safety (weight: 0.274), risks development potential (weight: 0.144), psychological well-being (weight: 0.140), physical well-being (weight: 0.124), life prognosis (weight: 0.106), possible impact on social environment (weight: 0.085), interpersonal relationships (weight: 0.073), and responsibilities and social role (weight: 0.054). In this study, we co-developed a prioritization decision tool with the key stakeholders for prioritization of patients who are referred to AAC services in rehabilitation settings.IMPLICATIONS FOR REHABILIATIONStudies in Canada have shown that people in Canada with a need for rehabilitation services are not receiving publicly available services in a timely manner.There is no standardized tool for the prioritization of AAC patients.In this mixed methods study, we co-developed a prioritization tool with key stakeholders for prioritization of patients who are referred to AAC services in a rehabilitation center in Quebec, Canada. Studies in Canada have shown that people in Canada with a need for rehabilitation services are not receiving publicly available services in a timely manner. There is no standardized tool for the prioritization of AAC patients. In this mixed methods study, we co-developed a prioritization tool with key stakeholders for prioritization of patients who are referred to AAC services in a rehabilitation center in Quebec, Canada.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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 teacher head, 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".