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Record W2100303403 · doi:10.1017/s0266462306051026

Evaluation of the ambulatory and home care record: Agreement between self-reports and administrative data

2006· article· en· W2100303403 on OpenAlexaff
Denise N. Guerriere, Wendy J. Ungar, Mary Corey, Ruth Croxford, Jennifer E. Tranmer, Elizabeth Tullis, Peter C. Coyte

Bibliographic record

VenueInternational Journal of Technology Assessment in Health Care · 2006
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealth Systems, Economic Evaluations, Quality of Life
Canadian institutionsSt. Michael's HospitalHealth Sciences CentreSunnybrook Health Science CentreUniversity of TorontoSickKids FoundationHospital for Sick Children
Fundersnot available
KeywordsAmbulatoryAgreementMedicineLimits of agreementAmbulatory careFamily medicineMedical emergencyPolitical scienceHealth careLawInternal medicinePhilosophyNuclear medicine

Abstract

fetched live from OpenAlex

OBJECTIVES: Although measuring the utilization of ambulatory and home-based healthcare resources is an essential component of economic analyses, very little methodological attention has been devoted to the development and evaluation of resource costing tools. This study evaluated a newly developed tool, the Ambulatory and Home Care Record (AHCR), which comprehensively evaluates costs incurred by the health system and care recipients and their unpaid caregivers. METHODS: The level of agreement between self-reports from 110 cystic fibrosis care recipients and administrative data was assessed for four categories of health services: home-based visits with healthcare professionals, ambulatory visits with healthcare professionals, laboratory and diagnostic tests, and prescription medications. RESULTS: Agreement between care recipients' reports on the AHCR and administrative data ranged from moderate (kappa = 0.41; 95 percent confidence interval, 0.16-0.61) for physician specialist visits to perfect (kappa = 1.0) for physiotherapy visits. CONCLUSIONS: By evaluating and standardizing a resource and costing tool, such as the AHCR, economic evaluations may be improved and comparisons of the resource implications for different services and for diverse populations are possible.

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)0.012
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.048
Threshold uncertainty score0.464

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0120.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.262
GPT teacher head0.502
Teacher spread0.240 · 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.

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

Citations92
Published2006
Admission routes1
Has abstractyes

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