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Record W2894133014 · doi:10.1200/jgo.18.13800

Acute-Care Hospital Use Patterns Near End-of-Life for Cancer Patients Who Die in Hospital in Canada

2018· article· en· W2894133014 on OpenAlexaffabout
J. Tung, K. DeCaria, Deborah Dudgeon, E. Green, Raquel Shaw Moxam, Jin Niu, Rami Rahal

Bibliographic record

VenueJournal of Global Oncology · 2018
Typearticle
Languageen
FieldMedicine
TopicPalliative Care and End-of-Life Issues
Canadian institutionsCanadian Partnership Against Cancer
Fundersnot available
KeywordsMedicinePalliative careEnd-of-life careEmergency departmentAcute careCancerPlace of deathEmergency medicineAcute hospitalIntensive care unitQuality of life (healthcare)Health careMedical emergencyIntensive care medicineNursingInternal medicine

Abstract

fetched live from OpenAlex

Background: Acute-care hospitals have a role in managing the needs of people with cancer when they are at the end-of-life; however, overutilization of hospital care at the end-of-life results in poorer quality of life and can worsen the patient's experience. Early integration of comprehensive palliative care can greatly reduce unplanned visits to the emergency department, reduce avoidable admissions to hospital, shorten hospital stays, and increase the number of home deaths as well as improve the quality of life of patients with advanced cancer. Aim: To describe the current landscape of acute-care hospital utilization near the end-of-life across Canada and indirectly examine access to palliative care in cancer patients who die in hospital. Methods: Data were obtained from the Canadian Institute for Health Information. The analysis was restricted to adults aged 18+ who died in an acute care hospital in 2014/15 and 2015/16 for nine provinces and three territories. The Discharge Abstract Database was used to extract acute-care cancer death abstracts. Data on intensive care unit (ICU) admissions includes only facilities that report ICU data. Results: Acute care utilization at end-of-life remains commonplace. In Canada (excluding Québec), 43% (48,987) of deaths from cancer occurred in acute-care hospitals, with 70% admitted through the emergency department (ED). In the last six months of life, cancer patients dying in hospital had a median cumulative length of stay ranging from 17 to 25 days, depending on the province. Between 18.1% and 32.8% of patients experienced two or more admissions to the hospital in the last month of life. The proportion of cancer patients admitted to the ICU in the last 14 days of life ranged from 6.4% to 15.1%. Patient demographics (age, sex, place of residence) and clinical factors (cancer type) were often predictors of hospital utilization at end-of-life and likely point to inequities in access to palliative and end-of-life care. Conclusion: Despite previous patient surveys indicating that patients would prefer to receive care and spend their finals days at home or in a hospice, there appears to be overuse of and overreliance on acute care hospital services near the end-of-life in Canada. The high rates of hospital deaths and admissions through the ED at the end-of-life for cancer patients may signal a lack of planning for impeding death and inadequate availability of or access to community- and home-based palliative and end-of-life care services. Acute care hospitals may have a role in managing the health care needs of people affected by cancer; however, end-of-life care should be an option in other settings that align with patient preferences. Standards or practice guidelines to identify, assess and refer patients to palliative care services earlier in their cancer journey should be developed and implemented to ensure optimal quality of life.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.433
Threshold uncertainty score0.772

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.046
GPT teacher head0.394
Teacher spread0.348 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2018
Admission routes2
Has abstractyes

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