Implementing a patient engagement framework in the primary healthcare system in Qatar
Bibliographic record
Abstract
The healthcare system in Qatar has acknowledged the need for patient-centered care (PCC) in its strategic intentions. The primary care system in Qatar consists of 31 health centers located throughout the country, managed by the Primary Health Care Corporation (PHCC). PHCC sought accreditation through Accreditation Canada, which in 2018 included a priority for PCC, including engaging patients in all aspects of the organization. A formal patient engagement (PE) framework was developed and fully implemented in the primary health care system. The framework involved patients in strategic and operational aspects of all organizational activities at national and health center levels, including participating in committees and activities such as quality improvement projects. Engaging patients in their own direct care was seen as part of the clinical process by our healthcare professional staff. Development of our patient engagement framework included recruiting a significant number of patients, outlining governance for implementation and oversight, documenting all the processes involved, and then implementing the PE framework. The outcomes of implementation of the PE framework include evidence of benefits for the organization, staff, and patient advisors. Although more patients responded to requests to provide feedback on their care, the patient experience data has not shown significant improvement in patients’ perceptions of their care experiences in our health centers as a result of engaging patient at service design level. Our experience demonstrates the intricacy of engaging patients in a healthcare system. Implementation of patient engagement in the clinical care process needs to be given equivalent weight in a patient engagement framework. Experience Framework This article is associated with the Patient, Family & Community Engagement lens of The Beryl Institute Experience Framework (https://theberylinstitute.org/experience-framework/). Access other PXJ articles related to this lens. Access other resources related to this lens.
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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 | 0.071 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.013 |
| Scholarly communication | 0.010 | 0.006 |
| Open science | 0.003 | 0.015 |
| Research integrity | 0.004 | 0.009 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".