Co-designing person-centred quality indicator implementation for primary care in Alberta: a consensus study
Bibliographic record
Abstract
Abstract Background We aimed to contribute to developing practical guidance for implementing person-centred quality indicators (PC-QIs) for primary care in Alberta, Canada. As a first step in this process, we conducted stakeholder-guided prioritization of PC-QIs and implementation strategies. Stakeholder engagement is necessary to ensure PC-QI implementation is adapted to the context and local needs. Methods We used an adapted nominal group technique (NGT) consensus process. Panelists were presented with 26 PC-QIs, and implementation strategies. Both PC-QIs and strategies were identified from our extensive previous engagement of patients, caregivers, healthcare providers, and quality improvement leaders. The NGT objectives were to: 1. Prioritize PC-QIs and implementation strategies; and 2. Facilitate the participation of diverse primary care stakeholders in Alberta, including patients, healthcare providers, and quality improvement staff. Panelists participated in three rounds of activities. In the first, panelists individually ranked and commented on the PC-QIs and strategies. The summarized results were discussed in the second-round face-to-face group meeting. For the last round, panelists provided their final individual rankings, informed by the group discussion. Finally, we conducted an evaluation of the consensus process from the panelists’ perspectives. Results Eleven primary care providers, patient partners, and quality improvement staff from across Alberta participated. The panelists prioritized the following PC-QIs: ‘Patient and caregiver involvement in decisions about their care and treatment’; ‘Trusting relationship with healthcare provider’; ‘Health information technology to support person-centred care’; ‘Co-designing care in partnership with communities’; and ‘Overall experience’. Implementation strategies prioritized included: ‘Develop partnerships’; ‘Obtain quality improvement resources’; ‘Needs assessment (stakeholders are engaged about their needs/priorities for person-centred measurement)’; ‘Align measurement efforts’; and ‘Engage champions’. Our evaluation suggests that panelists felt that the process was valuable for planning the implementation and obtaining feedback, that their input was valued, and that most would continue to collaborate with other stakeholders to implement the PC-QIs. Conclusions Our study demonstrates the value of co-design and participatory approaches for engaging stakeholders in adapting PC-QI implementation for the primary care context in Alberta, Canada. Collaboration with stakeholders can promote buy-in for ongoing engagement and ensure implementation will lead to meaningful improvements that matter to patients and providers.
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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 | 0.280 | 0.206 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.011 | 0.004 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.007 | 0.009 |
| Research integrity | 0.003 | 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".