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Record W2952840127 · doi:10.1093/ndt/gfz103.sp677

SP677IMPLEMENTING A PATIENT-REPORTED OUTCOME MEASURE FOR HEMODIALYSIS PATIENTS IN ROUTINE CLINICAL CARE: PERSPECTIVES OF PATIENTS AND CLINICIANS

2019· article· en· W2952840127 on OpenAlexaffabout
Jenna M. Evans, Alysha Glazer, Rebecca Lum, Esti Heale, Marnie MacKinnon, Peter G. Blake, Michael Walsh

Bibliographic record

VenueNephrology Dialysis Transplantation · 2019
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicPharmaceutical Economics and Policy
Canadian institutionsMcMaster UniversityLondon Health Sciences CentreOntario Stroke Network
Fundersnot available
KeywordsMedicineHemodialysisIntensive care medicinePatient-reported outcomeMEDLINEMeasure (data warehouse)Quality of life (healthcare)SurgeryNursing

Abstract

fetched live from OpenAlex

INTRODUCTION: The Edmonton Symptom Assessment System Revised: Renal (ESAS-r:Renal) is a patient reported outcome measure (PROM) used to assess physical and psychological symptom burden in patients living with chronic kidney disease. The use of PROMs in clinical care is frequently recommended but there is little information on how to best implement their use. We studied patient and clinician perspectives of the implementation process and impact of using the ESAS-r:Renal during routine clinical care of hemodialysis patients in Ontario, Canada. METHODS: Eight in-facility hemodialysis units assessed 1,459 patients with the ESAS-r:Renal every 4 to 6 weeks from April 2017 to June 2018. Pre- and post-implementation surveys and semi-structured interviews were conducted with patients and clinicians from the participating units. The results were used to identify implementation enablers and barriers, and to examine the perceived influence of ESAS-r:Renal on symptom management, patient-clinician communication, and interdisciplinary teamwork. RESULTS: 727 of patients participated in the pre-implementation survey and 579 participated in teh post-implementation survey. 518 (71%) of clinicians participated in the pre- and 323 (54%) participated in the post-implementation survey. Nine patients from three units participated in an individual interview and 48 clinicians from the eight units participated in group interviews (e.g., nephrologists, nurses, allied health professionals). Both patients and clinicians highly valued ESAS-r:Renal for ensuring symptoms are acknowledged by the care team, particularly psychosocial symptoms such as anxiety and depression, and for standardizing the symptom assessment process. Eighty-six percent of clinicians agreed that ESAS-r:Renal ensures symptoms are not missed and serves as a useful starting point to assess patients’ symptoms. Seventy-seven percent of patients reported that completing ESAS-r:Renal helped them feel more satisfied with their visit. Key inter-related barriers to the routine use of ESAS-r:Renal among clinicians included time/workload, high screening frequency, a lack of confidence to manage select symptoms and limited awareness of or access to external services for referrals. Notably, only 55% of clinicians reported they are very or moderately confident managing anxiety or depression. The survey and interview data suggests that the implementation of ESAS-r:Renal had limited influence on patient-clinician communication and interdisciplinary teamwork. The lack of impact on patient-clinician communication may be explained by a ceiling effect due to relatively high ratings at baseline (i.e., on average 70% of patients provided positive ratings pre-implementation versus 68% post-implementation). CONCLUSIONS: It is feasible to incorporate a PROM into routine care for patients on hemodialysis with appropriate education, integration into existing clinical workflows, and strong clinical and administrative leadership support. Further evaluation is required to understand the impact of ESAS-r:Renal on clinical processes and outcomes.

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)0.013
metaresearch head score (Gemma)0.024
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.065
Threshold uncertainty score0.129

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.024
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.053
GPT teacher head0.325
Teacher spread0.272 · 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".

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Citations1
Published2019
Admission routes2
Has abstractyes

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