MétaCan
Menu
Back to cohort
Record W2009682256 · doi:10.1097/mlr.0b013e3180ca95e9

Cost and Quality

2007· article· en· W2009682256 on OpenAlexafffund
Walter P. Wodchis, Gary Teare, Geoff Anderson

Bibliographic record

VenueMedical Care · 2007
Typearticle
Languageen
FieldHealth Professions
TopicGeriatric Care and Nursing Homes
Canadian institutionsSaskatchewan Health Quality CouncilInstitute for Clinical Evaluative SciencesToronto Rehabilitation InstituteUniversity of Toronto
FundersInstitute for Clinical Evaluative Sciences
KeywordsQuality costsQuality (philosophy)IncentiveMedicineQuality managementQuality assuranceControl (management)Operations managementBusinessEnvironmental healthCost controlRisk analysis (engineering)MarketingManagement systemEconomics

Abstract

fetched live from OpenAlex

BACKGROUND: Although both quality and cost are important concerns for long term care (LTC) facility management and policy, the relationship between cost and quality is poorly understood. Such knowledge is necessary to guide facility management and policy action. OBJECTIVE: We sought to determine the net effect of quality on cost in LTC hospital settings. STUDY SAMPLE: A 4-year panel dataset from April 1997 through March 2002 comprising observations from 99 LTC hospitals were included in this analysis. METHODS: We examined the relationship between direct resident costs and 7 indicators of quality for long-stay residents. We used panel data methods to control for unobserved facility-level characteristics. RESULTS: We found that increases in restraint use and incident pressure/skin ulcers were associated with lower per diem costs, whereas incontinence prevalence was associated with higher per diem costs. CONCLUSIONS: Our results point to different implications regarding cost and quality for different quality indicators. Although facilities have a strong internal business case to improve quality in incontinence, policy-makers may need to provide financial incentives to encourage reductions in restraint use and incident skin ulcers so as to defray potential higher costs associated with improving quality in these areas.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.502
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0010.000

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 head0.116
GPT teacher head0.510
Teacher spread0.394 · 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

Citations15
Published2007
Admission routes2
Has abstractyes

Explore more

Same venueMedical CareSame topicGeriatric Care and Nursing HomesFrench-language works237,207