Critical Analysis of Palliative Homecare Using the $\mathrm{i}^{\ast}$ Framework's Strategic and Social Requirements Modelling Applied to a Cancer Care Organisation
Bibliographic record
Abstract
Home Health Care (HHC) is an essential and critical part of palliative care and especially for terminal cancer patients. This research is aimed as a first attempt to align with the research gap in modelling the social requirements of palliative care processes and the HHC process in particular. Consequently, this research is a first attempt at developing an$\mathbf{i}^{\ast}$framework visual goal-oriented and social requirements models of the HHC process of the domain of palliative care with a reflected application using a case study from a leading regional cancer centre in the Middle East, namely KHCC. Furthermore, this research has made it possible for palliative care domain experts in the HHC process and using the associated$\mathbf{i}^{\ast}$framework strategic dependency and strategic rationale models to visually trace the most critical and strategic actors in the HHC process along with the highly interacting dependers and dependees. Finally, the HHC$\mathbf{i}^{\ast}$strategic models contribute to bridging the gap between the world of palliative care requirements and their reflective computer-based information systems and$\mathbf{IoT}$smart devices. Hence, this sheds light towards the realisation of the field of palliative care as being a “systems of systems” virtual organisation with the respective socio-technical systems involvement, for the best care of the palliative patient and especially terminal cancer patients. A further corollary of this research is the insufficiency and less representativeness of palliative care process models to utilise in guiding the development of the HHC$\mathbf{i}^{\ast}$framework strategic models without linking to the full associated strategic and policy documents of palliative care.
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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 | 0.016 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.003 | 0.007 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.003 | 0.003 |
| 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".