Decision making in the end-of-life care of patients who are terminally ill with cancer – a qualitative descriptive study with a phenomenological approach from the experience of healthcare workers
Bibliographic record
Abstract
BACKGROUND: In Colombia, recent legislation regarding end-of-life decisions includes palliative sedation, advance directives and euthanasia. We analysed which aspects influence health professionals´ decisions regarding end-of-life medical decisions and care for cancer patients. METHODS: Qualitative descriptive-exploratory study based on phenomenology using semi-structured interviews. We interviewed 28 oncologists, palliative care specialists, general practitioners and nurses from three major Colombian institutions, all involved in end-of-life care of cancer patients: Hospital Universitario San Ignacio and Instituto Nacional de Cancerología in Bogotá and Hospital Universitario San José in Popayan. RESULTS: When making decisions regarding end-of-life care, professionals consider: 1. Patient's clinical condition, cultural and social context, in particular treating indigenous patients requires special skills. 2. Professional skills and expertise: training in palliative care and experience in discussing end-of-life options and fear of legal consequences. Physicians indicate that many patients deny their imminent death which hampers shared decision-making and conversations. They mention frequent ambiguity regarding who initiates conversations regarding end-of-life decisions with patients and who finally takes decisions. Patients rarely initiate such conversations and the professionals normally do not ask patients directly for their preferences. Fear of confrontation with family members and lawsuits leads healthcare workers to carry out interventions such as initiating artificial feeding techniques and cardiopulmonary resuscitation, even in the absence of expected benefits. The opinions regarding the acceptability of palliative sedation, euthanasia and use of medications to accelerate death without the patients´ explicit request vary greatly. 3. Conditions of the insurance system: limitations exist in the offer of oncology and palliative care services for important proportions of the Colombian population. Colombians have access to opioid medications, barriers to their application are largely in delivery by the health system, the requirement of trained personnel for intravenous administration and ambulatory and home care plans which in Colombia are rare. CONCLUSIONS: To improve end-of-life decision making, Colombian healthcare workers and patients need to openly discuss wishes, needs and care options and prepare caregivers. Promotion of palliative care education and development of palliative care centres and home care plans is necessary to facilitate access to end-of-life care. Patients and caregivers' perspectives are needed to complement physicians' perceptions and practices.
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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 | 0.008 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.010 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".