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Record W4389142968 · doi:10.1177/20543581231215858

Alignment Among Patient, Caregiver, and Health Care Provider Perspectives on Hemodialysis Vascular Access Decision-Making: A Qualitative Study

2023· article· en· W4389142968 on OpenAlexafffundabout
Angela Schneider, Pietro Ravani, Kathryn King‐Shier, Robert R. Quinn, Jennifer M. MacRae, Shannan Love, Matthew J. Oliver, Swapnil Hiremath, Matthew T. James, Mia Ortiz, Braden Manns, Meghan J. Elliott

Bibliographic record

VenueCanadian Journal of Kidney Health and Disease · 2023
Typearticle
Languageen
FieldHealth Professions
TopicCentral Venous Catheters and Hemodialysis
Canadian institutionsUniversity of OttawaUniversity of TorontoUniversity of Calgary
FundersKidney Foundation of Canada
KeywordsMedicineThematic analysisQualitative researchNursingHemodialysisHealth carePreparednessFamily medicine

Abstract

fetched live from OpenAlex

Background: Updates to the Kidney Disease Outcomes Quality Initiative Clinical Practice Guideline for Vascular Access emphasize the "right access, in the right patient, at the right time, for the right reasons." Although this implies a collaborative approach, little is known about how patients, their caregivers, and health care providers engage in vascular access (VA) decision-making. Objective: To explore how the perspectives of patients receiving hemodialysis, their caregivers, and hemodialysis care team align and diverge in relation to VA selection. Design: Qualitative descriptive study. Setting: Five outpatient hemodialysis centers in Calgary, Alberta. Participants: Our purposive sample included 19 patients receiving maintenance hemodialysis, 2 caregivers, and 21 health care providers (7 hemodialysis nurses, 6 VA nurses, and 8 nephrologists). Methods: We conducted semi-structured interviews with consenting participants. Using an inductive thematic analysis approach, we coded transcripts in duplicate and characterized themes addressing our research objective. Results: While participants across roles shared some perspectives related to VA decision-making, we identified areas where views diverged. Areas of alignment included (1) optimizing patient preparedness-acknowledging decisional readiness and timing, and (2) value placed on trusting relationships with the kidney care team-respecting decisional autonomy with guidance. Perspectives diverged in the following aspects: (1) differing VA priorities and preferences-patients' emphasis on minimizing disruptions to normalcy contrasted with providers' preferences for fistulas and optimizing biomedical parameters of dialysis; (2) influence of personal and peer experience-patients preferred pragmatic, experiential knowledge, whereas providers emphasized informational credibility; and (3) endpoints for VA review-reassessment of VA decisions was prompted by access dissatisfaction for patients and a medical imperative to achieve a functioning access for health care providers. Limitations: Participation was limited to individuals comfortable communicating in English and from urban, in-center hemodialysis units. Few informal caregivers of people receiving hemodialysis and younger patients participated in this study. Conclusions: Although patients, caregivers, and healthcare providers share perspectives on important aspects of VA decisions, conflicting priorities and preferences may impact the decisional outcome. Findings highlight opportunities to bridge knowledge and readiness gaps and integrate shared decision-making in the VA selection process.

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)0.027
metaresearch head score (Gemma)0.033
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.984
Threshold uncertainty score0.141

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0270.033
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0130.011
Scholarly communication0.0050.006
Open science0.0020.007
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0030.000

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 head0.044
GPT teacher head0.414
Teacher spread0.370 · 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 designQualitative
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

Citations2
Published2023
Admission routes3
Has abstractyes

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