Qatar Interprofessional Health Council: IPE for Qatar
Bibliographic record
Abstract
Abstract Qatar has grown rapidly over the past 10 years particularly in the areas of healthcare needs and provisioning. The population has grown from 617,000 in 2000 to over 1.7 million in 2010. The number of hospitals both private and public has nearly doubled with the number of healthcare workers surpassing 11,000 in 2011. To help meet the demand for trained healthcare professionals there are now 4 educational institutions in Qatar addressing medicine, nursing, pharmacy, and allied healthcare (School of Health Sciences at the College of the North Atlantic – Qatar, College of Pharmacy at Qatar University, University of Calgary – Qatar, and Weill-Cornell Medical College in Qatar). The World Health Organization (WHO) has identified a need to integrate all areas of healthcare and to foster team-based collaborative models to help improve healthcare service delivery. Interprofessional Education (IPE) provides a framework to facilitate such a model. A truly comprehensive and inclusive IPE program would include agreement on IPE competencies (shared competencies) amongst and between all healthcare educational providers (pre- and post-licensure) accompanied by collaborative models that promote and facilitate working together as teams. Measures of success include meeting the shared IPE competencies. This paper describes the formation of the Qatar Interprofessional Health Council (QIHC) to help address healthcare needs in Qatar and their efforts to move IPE forward in the state and in the region. The QIHC consists of members from the 4 healthcare educational institutions in Qatar as well as members from Sidra Medical and Research Center and Hamad Medical Corporation (HMC). A discussion of barriers and solutions is included as well as the efforts of the member institutions to provide IPE support and integration into their programs. The QIHC has recently been awarded a National Priorities Research Program (NPRP) research grant to help provide a solid and contextually appropriate framework for IPE in Qatar.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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; both teacher heads agree on what is shown here.
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".