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Record W2019637276 · doi:10.1108/13660750110391520

Measures of quality in long‐term care facilities

2001· article· en· W2019637276 on OpenAlex
Kevin J. Leonard, Doreen Wilson, Olga W. Malott

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueLeadership in Health Services · 2001
Typearticle
Languageen
FieldHealth Professions
TopicPatient Satisfaction in Healthcare
Canadian institutionsUniversity of WaterlooUniversity of Toronto
Fundersnot available
KeywordsQuality (philosophy)Health carePatient satisfactionTerm (time)Health care qualityNursingChristian ministryMarketingSet (abstract data type)Long-term careBusinessMedicineComputer sciencePolitical science

Abstract

fetched live from OpenAlex

Although marketing does not play a large role in the Canadian health‐care system, acute care facilities have been conducting patient satisfaction surveys as a quality measurement tool for a number of years. More recently those in the long‐term care system have expressed an interest in this concept. This study set out to determine if long‐term care facilities in the Ministry of Health, Ontario Central West Region, conduct consumer satisfaction surveys. If they do, the study asked how the information is utilized and, if they do not, why not. This paper will highlight issues of service quality, health‐care quality and health‐care consumer satisfaction. This study is focused on long‐term care; however, the majority of the available research and information pertains to the acute care system. Although the principles of quality measurement and consumer satisfaction are the same for acute and long‐term care, our findings will identify the unique ways in which these principles apply to the long‐term care system.

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.

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)0.002
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 score0.285
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
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 head0.449
GPT teacher head0.486
Teacher spread0.037 · 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