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Record W3213442700 · doi:10.12968/jowc.2021.30.11.940

Costing pressure ulcer care in an Irish acute care setting: a feasibility study

2021· article· en· W3213442700 on OpenAlexaff
Aoife Reilly, Jan Sørensen, Helen Strapp, Declan Patton, Amy Blair, Pınar Avşar, Jane Burns, Zena Moore

Bibliographic record

VenueJournal of Wound Care · 2021
Typearticle
Languageen
FieldHealth Professions
TopicPressure Ulcer Prevention and Management
Canadian institutionsSKiN Health
Fundersnot available
KeywordsMedicineActivity-based costingAcute careRetrospective cohort studyNursing careEmergency medicineHealth careTotal costSurgeryNursing

Abstract

fetched live from OpenAlex

OBJECTIVE: To test the feasibility of using a standardised data collection tool to estimate the cost of stage 2-4 pressure ulcer (PU) care within an acute care setting. METHOD: Data on resource use and cost were obtained through a retrospective survey of nursing and medical notes collecting cost data for individual patients who received care for stage 2-4 PUs. RESULTS: Data for 20 patients (12 male/8 female) were analysed. The average patient age was 69 years (range: 37-95 years). Of this sample, seven patients had hospital-acquired PUs (HAPUs) and 14 patients had community-acquired PUs (CAPU) (one patient had both-in different anatomical areas). Over half of the total sample (55%; n=11) had a stage 2 PU. The average length of stay was 31.8 days (range: 5-119 days). Most of the patients (70%; n=14) had a CAPU. The average cost per patient with PU care was €878 (range: €39-2393). The mean cost for patients with a HAPU was €866 (SD: €1313) versus €911 (SD: €567) for patients with a CAPU. The majority of the cost related to equipment and staff time for treatment. CONCLUSION: Overall, the application of the standardised data collection tool to obtain cost data from retrospective inspection of nursing and medical notes is feasible. The cost of PU care in this sample was high, indicating that these wounds may impose a substantial burden on health systems. The costs varied greatly between patients in the sample, reflecting the complexity of PU care. Furthermore, given that costs increased with the higher PU stages, there is a potential to reduce costs by preventing the development of higher stage PUs. Larger-scale studies are required to understand the cost variation and full economic impact of PU care. DECLARATION OF INTEREST: The authors have no conflicts of interest.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.466
Threshold uncertainty score0.789

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.052
GPT teacher head0.451
Teacher spread0.399 · 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

Citations8
Published2021
Admission routes1
Has abstractyes

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