Evidence map›Paper›PMID 33158824›Full record

ArticleBMJ open2020

Feasibility and acceptability of e-PROMs data capture and feedback among patients receiving haemodialysis in the Symptom monitoring WIth Feedback Trial (SWIFT) pilot: protocol for a qualitative study in Australia.

Emily Duncanson, Paul N Bennett, Andrea Viecelli, Kathryn Dansie, William Handke, Allison Tong, Suetonia Palmer, Shilpanjali Jesudason, Stephen P McDonald, Rachael L Morton and 1 more

Registry-linked trialAbstract read
In one paragraph

Article in BMJ open, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05221697 (Effect of an Electronic Alert Management System Using Caregivers' Observations and Machine Learning Algorithm to Reduce the Use of Emergency Department Visits and Unplanned Hospitalizations Among Older People), which is not on this map. Cited by 21 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed, 3 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT05221697 naunknown statusnot on this map

Effect of an Electronic Alert Management System Using Caregivers' Observations and Machine Learning Algorithm to Reduce the Use of Emergency Department Visits and Unplanned Hospitalizations Among Older People

TypeinterventionalSponsorPresageRan2020 to 2024Enrolled800ConditionsEmergenciesArmsPRESAGE CARE
3 · Its place in the literature

Who cites it

21 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
  2. Interventions for fatigue in people with kidney failure requiring dialysis.The Cochrane database of systematic reviews · 2023
    Pooled it
  3. Pooled it
  4. Trial
  5. Trial
  6. Article
  7. Psychometric properties of the Chinese version of PROMIS-29 in patients receiving kidney replacement therapy.Zhong nan da xue xue bao. Yi xue ban = Journal of Central South University. Medical sciences · 2026
    Article
  8. Article
  9. Article
  10. Review
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Review
  17. Five-Year Symptom Trajectories in Nondialysis-Dependent CKD Patients.Clinical journal of the American Society of Nephrology : CJASN · 2022
    Article
  18. Article
  19. Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Emily DuncansonAustralia and New Zealand Dialysis and Transplant (ANZDATA) Registry, South Australian Health and Medical Research Institute, Adelaide, South Australia, Australia.
Paul N BennettFaculty of Health Medicine Nursing and Behavioural Sciences, Deakin University, Burwood, Victoria, Australia.
Andrea ViecelliSchool of Medicine, Princess Alexandra Hospital, Woolloongabba, Queensland, Australia.
Kathryn DansieAustralia and New Zealand Dialysis and Transplant (ANZDATA) Registry, South Australian Health and Medical Research Institute, Adelaide, South Australia, Australia.
William HandkeConsumer representative, Private citizen, Canberra, ACT, Australia.
Allison TongSydney School of Public Health, The University of Sydney, Sydney, New South Wales, Australia.
Suetonia PalmerDepartment of Medicine, University of Otago, Christchurch, New Zealand.
Shilpanjali JesudasonCentral and Northern Adelaide Renal and Transplantation Services (CNARTS), Royal Adelaide Hospital, Adelaide, South Australia, Australia.
Stephen P McDonaldAustralia and New Zealand Dialysis and Transplant (ANZDATA) Registry, South Australian Health and Medical Research Institute, Adelaide, South Australia, Australia.
Rachael L MortonNHMRC Clinical Trials Centre, The University of Sydney, Camperdown, New South Wales, Australia Rachael.morton@ctc.usyd.edu.au.ORCID 0000-0001-7834-0572
Symptom monitoring WIth Feedback Trial (SWIFT) Investigators

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionPeople receiving haemodialysis experience a high symptom burden and impaired quality of life. The use of patient-reported outcome measures (PROMs) is increasing in nephrology care, however their acceptability, utility and impacts are not well understood. METHODS AND ANALYSIS: We describe a protocol for a qualitative study to evaluate the feasibility and acceptability of electronic-PROMs (e-PROMs) data capture and feedback in haemodialysis following the pilot ETHICS AND DISSEMINATION: Ethics approval was obtained from the relevant hospital Human Research Ethics Committees (HREC/18/CALHN/481; HREC/MML/54599). The findings from the SWIFT pilot and qualitative evaluation will inform the implementation of the SWIFT main trial, and more broadly, the use of e-PROMs in clinical settings and registries. TRIAL REGISTRATION NUMBER: ANZCTRN12618001976279.

Indexed as

Quality of LifeRenal DialysisAustraliaFeasibility StudiesFeedbackHumansNew ZealandPatient Reported Outcome MeasuresPilot ProjectsQualitative Researchadult nephrologychronic renal failuredialysisnephrologyqualitative research

Identifiers

PMID33158824
PMCPMC7651719

What OpenQuestion holds

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Registered trials

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.