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Record W2032455354 · doi:10.1136/bmjspcare-2013-000444

Advance care planning discussions among residents of long term care and designated assisted living: experience from Calgary, Alberta

2013· article· en· W2032455354 on OpenAlexafffundabout
Claire Dyason, Jessica Simon, Tracy Lynn Wityk Martin

Bibliographic record

VenueBMJ Supportive & Palliative Care · 2013
Typearticle
Languageen
FieldMedicine
TopicPalliative Care and End-of-Life Issues
Canadian institutionsAlberta Health Services
FundersAlberta Health Services
KeywordsAdvance care planningAutonomyLong-term careAssisted livingGerontologyPopulationHealth careTracking (education)MedicineAssisted Living FacilityBaseline (sea)NursingPsychologyFamily medicinePalliative careEnvironmental health

Abstract

fetched live from OpenAlex

OBJECTIVES: Patients, physicians and the healthcare system are faced with the challenge of determining, and respecting, the medical wishes of an aging population. Our study sought to describe who participates in advance care planning (ACP) and decision-making for patients in long-term care and designated assisted living. METHODS: In 2008, Alberta Health Services initiated its 'Advance Care Planning: Goals of Care Designation' (Adult) policy in the Calgary zone. This policy encouraged discussions about goals of care and used a tracking form to capture these conversations. A postpolicy implementation chart review was performed at 3 time points: at baseline, at 6 months and at 18 months post implementation in long term care (LTC) and designated assisted living sites. RESULTS: 166 charts were reviewed and 90% had a documented goals of care order. Less than half of residents (47%) were documented as participating in conversations and they were less likely to participate if they had cognitive impairment and were living in LTC. Documented family participation was more prevalent in LTC (51% vs 11%). Nurses participated in 67% of documented conversations with only 34% of discussions documenting physician involvement. CONCLUSIONS: This study identifies the lack of documented resident participation in ACP in LTC. While this finding may be explained by the high prevalence of cognitive impairment in our population, it raises questions about the optimal approach to ACP in LTC. In this setting, ACP appears to be more about relational autonomy than it is about patient autonomy.

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)0.002
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 score0.033
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.078
GPT teacher head0.420
Teacher spread0.342 · 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

Citations8
Published2013
Admission routes3
Has abstractyes

Explore more

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