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Record W2076072468 · doi:10.1017/s0266462303000424

HEALTH-RELATED QUALITY OF LIFE MEASURE BASED ON THE MINIMUM DATA SET

2003· article· en· W2076072468 on OpenAlexaffabout
Walter P. Wodchis, John P. Hirdes, David Feeny

Bibliographic record

VenueInternational Journal of Technology Assessment in Health Care · 2003
Typearticle
Languageen
FieldHealth Professions
TopicGeriatric Care and Nursing Homes
Canadian institutionsUniversity of AlbertaHomewood Research InstituteInstitute for Clinical Evaluative SciencesUniversity of WaterlooToronto Rehabilitation Institute
Fundersnot available
KeywordsMinimum Data SetQuality of life (healthcare)Health Utilities IndexGerontologyMedicineHealth carePopulationSet (abstract data type)Long-term careIndex (typography)Environmental healthHealth related quality of lifeNursingNursing homesComputer science

Abstract

fetched live from OpenAlex

Objectives: To introduce a health-related quality of life measure for home care and institutional long-term care settings based on the Minimum Data Set (MDS) and the Health Utilities Index Mark 2 (HUI2).Methods: Health attributes of Health Related Quality of Life (HRQOL) were identified, and suitable constructs were determined. Items from the MDS were mapped to the HUI2. Scores for the Minimum Data Set Health Status Index (MDS-HSI) were calculated using the HUI2 scoring function. Measurement properties are examined and reported. HRQOL scores were compared across study populations and to an external reference population. Random samples were drawn from long-term care clients in private households (n=377), supportive housing apartments (n=80), two residential care facilities (n=166), and a chronic care hospital (n=274) in Ontario, Canada. All sampled residents were assessed for health-related items using the MDS.Results: The MDS-HSI results provide preliminary evidence of good validity. Institutional populations had lower overall HRQOL scores than community populations. Comparisons to existing Canadian national data support construct validity.Conclusions: The MDS-HSI provides a summary outcome measure and an indicator of health status in the six supporting attributes. Longitudinal research is required to assess the sensitivity of the measure to changes over time. Further research is also required to establish the consistency between the preference weights used in this application of the HUI2 and those that would be derived from a frail elderly population.This research was supported by the Seniors Independence Program (grant 4687-06-93-458) and the Providence Centre Foundation. Thanks to Copernicus Lodge, Providence Centre, and the Red Cross Homemaker Program for participating in this study. Also thanks to Roger Roberge and Dan Dekoker from Statistics Canada for their help in obtaining and analyzing the NPHS data. International copyright for the MDS-NH and MDS-HC is held by interRAI. International copyright for HUI2 and HUI3 materials are held by Health Utilities, Inc.

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 imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.028
Threshold uncertainty score0.056

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.129
GPT teacher head0.498
Teacher spread0.369 · 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 source (direct Gemma or distilled Codex), 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

Citations45
Published2003
Admission routes2
Has abstractyes

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