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Record W4283691053 · doi:10.1002/hsr2.715

Managing the delivery of venous leg ulcer services: A willingness to pay study

2022· article· en· W4283691053 on OpenAlexaff
Nyantara Wickramasekera, Simon Palfreyman, Elizabeth Lumley, Arvind Dosanjh, Phil Shackley

Bibliographic record

VenueHealth Science Reports · 2022
Typearticle
Languageen
FieldMedicine
TopicDiagnosis and Treatment of Venous Diseases
Canadian institutionsUniversity of Alberta
FundersNational Institute for Health and Care Research
KeywordsWillingness to payVenous leg ulcerBusinessLeg ulcerMedicineSurgeryEconomics

Abstract

fetched live from OpenAlex

Background and Aims: There is widespread variation in venous leg ulcer (VLU) wound care contributing to inadequate service provision resulting in poor outcomes to patients. Little has been published on the perspectives of where treatments should be carried out. The aim of the study was to quantify respondents' preferences for the preferred place of treatment for VLU. Methods: A UK general population sample was interviewed to elicit preferences for clinic or home care treatment using the willingness to pay elicitation method. Participants were presented with two vignettes describing clinic or home care of VLU, and were asked to select the treatment process that they preferred and provide a detailed explanation for selecting that choice. Then they were asked to state their maximum hypothetical amounts that they were willing to pay for the treatment processes. Results: One hundred fifty-four participants completed the interviews. Respondents were willing to pay £498.96 to receive VLU treatment at a clinic and £505.60 to receive care at home. This difference between the clinic compared to home care was not statistically significant. Advantages of clinic care include being able to book an appointment allowing participants to plan events around the booking and for home care the convenience for those with impaired mobility who may have difficulty traveling. Conclusions: The results show that respondents placed an equal valuation on the place of treatment suggesting no strong preference for either home or clinic care. However, qualitative findings emphasized that impaired mobility may be a barrier to accessing VLU services for some therefore, individuals should be given the choice to select their preferred setting to receive treatment where 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)0.001
metaresearch head score (Gemma)0.000
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 score0.021
Threshold uncertainty score0.693

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
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 head0.025
GPT teacher head0.338
Teacher spread0.313 · 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

Citations3
Published2022
Admission routes1
Has abstractyes

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