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Record W2415474193 · doi:10.1177/082585970001600106

Home versus Hospice Inpatient Care: Discharge Characteristics of Palliative Care Patients in an Acute Care Hospital

2000· article· en· W2415474193 on OpenAlexaff
Robin L. Fainsinger, Donna deMoissac, Janet C. Cole, Kathy Mead-Wood, Ellen Lee

Bibliographic record

VenueJournal of Palliative Care · 2000
Typearticle
Languageen
FieldMedicine
TopicPalliative Care and End-of-Life Issues
Canadian institutionsRoyal Alexandra HospitalUniversity of Alberta
Fundersnot available
KeywordsMedicinePalliative careDemographicsHospital dischargeProspective cohort studyEmergency medicineFamily medicineNursingIntensive care medicineInternal medicine

Abstract

fetched live from OpenAlex

This prospective survey was initiated to identify factors that helped and hindered home discharge for 100 consecutive patients who did not require further specialist palliative or acute care. Information was collected on demographics, functional ability (using the Palliative Performance Scale [PPS] and Karnofsky Performance Scale [KPS]), cognitive function at discharge as measured by the Mini-Mental State Examination (MMSE), home support circumstances, and patient and family preference for discharge. 59 patients were discharged home and 41 were transferred to a hospice. Younger patients with younger caregivers were discharged home more often. Patients with better MMSE and better functional ability (PPS and KPS) were also more likely to go home. Patients going home were more likely to be married. Preference for site of discharge was met for 76% of patients and 90% of families. Of the patients going to a hospice, 24% of patients and 7% of families preferred a home discharge. More physical support at home could have facilitated a home discharge for 13 patients. Functionally dependent and cognitively impaired patients were generally unable to return home. To support patients and their families in an environment of their choice, access to increased physical support in the home must be addressed.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.065
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.041
GPT teacher head0.370
Teacher spread0.329 · 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.

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

Citations41
Published2000
Admission routes1
Has abstractyes

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