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Older people, prescribed drug consumption and the general practitioner contract

2007· article· en· W2069701215 on OpenAlexaff
Barbara Wade

Bibliographic record

VenueHealth & Social Care in the Community · 2007
Typearticle
Languageen
FieldMedicine
TopicHealth Promotion and Cardiovascular Prevention
Canadian institutionsRoyal Ottawa Mental Health Centre
Fundersnot available
KeywordsMedicineConsumption (sociology)Family medicineMental healthMultivariate analysisNursingPsychologyPsychiatry

Abstract

fetched live from OpenAlex

This paper draws on data obtained in the first year of a longitudinal study designed to monitor the effect of the general practitioner contract and the 1990 NHS and Community Care Act. The study focuses on the care received by people over the age of 75 living in areas covered by four first wave community trusts. One objective of the first year of this study was to examine the impact of the general practitioner (GP) contract particularly with regard to drug consumption and nursing input. Random samples of older people were obtained from family health services authorities in the four trust areas. Health visitors were recruited in each locality and were trained to conduct the interviews. A total of 775 people were interviewed and assessed for functional, physical, mental, emotional and social status. Each person was asked whether they had been given a health check, who had been involved and where this was carried out. They were also asked to show those medicines they had taken in the 24 h before they were interviewed. Multivariate analysis showed that after controlling for physical symptoms, functional ability, pathology, admission to hospital in the previous 12 months, socio-economic class, self-health ratings and consultations with their doctor, those who had been given a health check had consumed fewer drugs. The implications of these findings for the drugs budget are calculated. The results of the study suggest that savings on the drugs budget may offset to a large extent the additional costs of employing practice nurses to undertake health checks but further research is indicated.

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)0.022
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.939
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0220.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.041
GPT teacher head0.390
Teacher spread0.349 · 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

Citations0
Published2007
Admission routes1
Has abstractyes

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