Ethical dilemmas in providing acute medical care at home for children: a survey of health professionals
Bibliographic record
Abstract
OBJECTIVE: Acute care at home is increasing. We aimed to determine the views of healthcare professionals on the ethics of providing home care and compare the impact of situational changes on their opinions. DESIGN: An analysis of opinions of home healthcare professionals. SETTING: The Australasian Hospital-in-the-Home Annual Conference, November 2017. PARTICIPANTS: Eighty physicians, nurses and allied health staff who provide acute care for children and adults at home. METHODS: Clinical scenarios were presented about a 14 years old receiving intravenous antibiotics at home via an established home care pathway, and participants were asked to vote manually on whether providing home care was ethical. MAIN OUTCOMES: The proportions of healthcare professionals who believed that provision of home care was ethical in different situations. RESULTS: For each question the response rate ranged from 71% to 100%. While the provision of acute home care was deemed ethical by the majority (77/80, 96%), this decreased when other factors were involved such as domestic violence (37/63 (59%) OR 0.06, 95% CI 0.02 to 0.20, p<0.001) and parental reluctance (28/67 (42%) OR 0.02, 95% CI 0.008 to 0.09, p<0.001). The age of consent affected the proportion who considered home care ethical against parental wishes: 16 years (48/58, 83%) versus 14 years (33/53, 52%) OR 4.4, 95% CI 1.9 to 10.1, p<0.001. The lowest proportion to consider home care ethical (16%) was when home care was deemed less than hospital care. CONCLUSIONS: Home healthcare providers are supportive of the ethics of providing acute care at home for children, although differ among themselves with situational complexities. Applying the tenets of medical ethics (autonomy, non-maleficence, beneficence and justice) can provide insights into the factors that may influence opinions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".