Remote Management for Peritoneal Dialysis: A Qualitative Study of Patient, Care Partner, and Clinician Perceptions and Priorities in the United States and the United Kingdom
Bibliographic record
Abstract
RATIONALE & OBJECTIVE: Peritoneal dialysis (PD) is a home-based kidney replacement therapy used by a growing number of patients with kidney failure. This qualitative study explores the impact of remote management technologies on PD treatment priorities of patients, their care partners, and clinicians. STUDY DESIGN: Qualitative study, designed and conducted in collaboration with a stakeholder panel that included patients, patient advocates, care partners, and health care professionals. SETTING & PARTICIPANTS: 13 health care providers, 13 patients, and 4 care partners with at least 3 months experience with PD were recruited from the United States and United Kingdom through postings in PD clinics, websites, and social media. METHODOLOGY: Semi-structured telephone interviews with a purposive sample of participants. ANALYTICAL APPROACH: Inductive thematic development adapted from a grounded theory approach through analysis of interview transcripts by 3 independent coders. RESULTS: 4 main themes about PD treatments emerged that enabled evaluation of remote management: (1) impact of PD on everyday life, (2) simplifying treatment processes, (3) awareness and visibility of at-home treatments, and (4) support for managing treatments. The relative importance of these themes differed between patients/care partners and health care providers and by use of remote management cyclers. LIMITATIONS: Remote management is new to PD, mirrored in the limited penetration of use in the study sample, suggestive of findings reflecting early adoption. CONCLUSIONS: Participants welcomed technological advances such as remote management for PD, although priorities differed by stakeholder group. Remote management could potentially influence health care provider decisions about patient suitability for PD, while patients/care partners prioritized pre-emptive and early treatment adjustments. Currently, decisions about access to remote management are outside the control of patients and families, but this may change with more widespread use.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.014 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.012 | 0.009 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".