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An Innovative Enterostomal Therapy Nurse Model of Community Wound Care Delivery

2008· article· en· W2059378316 on OpenAlexaffabout
Connie Harris, Ronald J. Shannon

Bibliographic record

VenueJournal of Wound Ostomy and Continence Nursing · 2008
Typearticle
Languageen
FieldMedicine
TopicStoma care and complications
Canadian institutionsCARE Canada
Fundersnot available
KeywordsMedicineReimbursementNursingSpecialtyWound careAuditAcute carePsychological interventionNursing careNursing managementHealth careIntensive care medicineFamily medicine

Abstract

fetched live from OpenAlex

PURPOSE: A Canadian specialty nursing association identified the necessity to examine the role and impact of enterostomal (ET) nursing in Canada. We completed a retrospective analysis of the cost-effectiveness and benefits of ET nurse-driven resources for the treatment of acute and chronic wounds in the community. DESIGN: This was a multicenter retrospective pragmatic chart audit of 3 models of nursing care utilizing 4 community nursing agencies and 1 specialty company owned and operated by ET nurses. An analysis was completed using quantitative methods to evaluate healing outcomes, nursing costs, and cost-effectiveness. MAIN OUTCOME MEASURES: Kaplan-Meier estimates were calculated to determine the average time to 100% healing of acute and chronic wounds and total nursing visit costs for treatment in a community setting. Average direct nursing costs related to management of each wound were determined by number of nursing visits and related reimbursement for each visit. A Monte Carlo simulation method was used to help account for costs and benefits in determination of cost-effectiveness between caring groups and the uncertainty from variation between patients and wounds. RESULTS: Three hundred sixty chronic wounds and 54 acute surgical wound charts were audited. Involvement of a registered nurse (RN) with ET or advanced wound ostomy skills (AWOS) in community-level chronic and acute wound care was associated with lower overall costs mainly due to reduced time to 100% closure of the wound and reduced number of nursing visits. The differences in health benefits and total costs of nursing care between the ET/AWOS and a hybrid group that includes interventions developed by an ET nurse and followed by general visiting nurses that could include both RNs and registered practical nurses is an expected reduction in healing times of 45 days and an expected cost difference of $5927.00 per chronic wound treated. When outcomes were broken into ET/AWOS involvement categories for treatment of chronic wounds, there was a significantly faster time to 100% closure at a lower mean cost as the ET/AWOS involvement increased in the case. For acute wound treatment, the differences in health benefits and total costs between the ET/AWOS and a hybrid nursing care model were an expected reduction in healing times of 95 days and an expected cost difference of $9578.00 per acute wound treated. Again, there was a significant difference in healing times and reduced mean cost as the ET/AWOS became more involved in the treatment. The financial benefit to the Ontario Ministry of Health and Long-Term Care is estimated to increase as the involvement of nurses with ET/AWOS specialty training increases. CONCLUSIONS: The greater the involvement both directly and indirectly of an ET/AWOS nurse in the management of wounds, the greater the savings and the shorter the healing times.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.117
Threshold uncertainty score0.233

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.049
GPT teacher head0.324
Teacher spread0.276 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations23
Published2008
Admission routes2
Has abstractyes

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