Evidence map›Paper›PMID 30990460›Full record

ArticleJMIR human factors2019

Uptake and Scalability of a Peritoneal Dialysis Virtual Care Solution: Qualitative Study.

Lianne Jeffs, Trevor Jamieson, Marianne Saragosa, Geetha Mukerji, Arsh K Jain, Rachel Man, Laura Desveaux, James Shaw, Payal Agarwal, Jennifer M Hensel and 4 more

Open access · goldAbstract read
In one paragraph

Article in JMIR human factors, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.3field-weighted citation impact, top 44% of its field
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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 3 citations in OpenAlex.

  1. Review
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

14 authors at 4 institutions in 1 country.

Lianne JeffsLunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, ON, Canada.ORCID http://orcid.org/0000-0002-6845-459X
Trevor JamiesonSt. Michael's Hospital, Toronto, ON, Canada.ORCID http://orcid.org/0000-0002-1050-3918
Marianne SaragosaInstitute for Health System Solutions and Virtual Care, Women's College Hospital, Toronto, ON, Canada.ORCID http://orcid.org/0000-0002-9261-5971
Geetha MukerjiInstitute of Health Policy Management and Evaluation, University of Toronto, Toronto, ON, Canada.ORCID http://orcid.org/0000-0002-6477-9848
Arsh K JainLondon Health Sciences Centre, London, ON, Canada.ORCID http://orcid.org/0000-0003-0048-2401
Rachel ManLondon Health Sciences Centre, London, ON, Canada.ORCID http://orcid.org/0000-0001-5324-287X
Laura DesveauxInstitute of Health Policy Management and Evaluation, University of Toronto, Toronto, ON, Canada.ORCID http://orcid.org/0000-0003-3429-1865
James ShawInstitute of Health Policy Management and Evaluation, University of Toronto, Toronto, ON, Canada.ORCID http://orcid.org/0000-0002-9522-0756
Payal AgarwalInstitute for Health System Solutions and Virtual Care, Women's College Hospital, Toronto, ON, Canada.ORCID http://orcid.org/0000-0001-5625-7532
Jennifer M Hensel *Institute for Health System Solutions and Virtual Care, Women's College Hospital, Toronto, ON, Canada.ORCID http://orcid.org/0000-0003-4194-6049
Maria MaioneSt. Michael's Hospital, Toronto ON, ON, Canada.ORCID http://orcid.org/0000-0003-0057-9094
Nike OnabajoInstitute for Health System Solutions and Virtual Care, Women's College Hospital, Toronto, ON, Canada.ORCID http://orcid.org/0000-0001-9817-0275
Megan NguyenInstitute for Health System Solutions and Virtual Care, Women's College Hospital, Toronto, ON, Canada.ORCID http://orcid.org/0000-0002-2413-1406
R BhatiaInstitute of Health Policy Management and Evaluation, University of Toronto, Toronto, ON, Canada.ORCID http://orcid.org/0000-0001-6206-5318
University of Toronto · CAWomen's College Hospital · CALondon Health Sciences Centre · CASt. Michael's Hospital · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundEarly research in the area of virtual care solutions with peritoneal dialysis (PD) patients has focused on evaluating the outcomes and impact of these solutions. There has been less attention focused on understanding the factors influencing the uptake, usability, and scalability of virtual care for chronic kidney disease (CKD) patients receiving PD at home.

objectiveIn this context, a study was undertaken to (1) assess and understand the factors influencing the uptake of a virtual care solution and (2) provide recommendations for the scalability of a virtual care solution aimed at enhancing CKD patients' outcomes and experiences.

methodsThis study used a qualitative design with semistructured interviews and a thematic analysis approach. A total of 25 stakeholders-6 patients and 3 caregivers, 6 health care providers, 2 vendors, and 8 health system decision makers-participated in this study.

resultsThe following three primary mechanisms emerged to influence the usability of the virtual care solution: (1) receiving hands-on training and ongoing communication from a supportive team, (2) adapting to meet user needs and embedding them into workflow, and (3) being influenced by patient and caregiver characteristics. Further, two overarching recommendations were developed for considerations around scalability: (1) co-design locally, embed into the daily workflow, and deploy over time and (2) share the benefits and build the case.

conclusionsStudy findings can be used by key stakeholders in their future efforts to enhance the implementation, uptake, and scalability of virtual care solutions for CKD and managing PD at home.

Indexed as

chronic kidney diseasepatient-centric careperitoneal dialysisqualitative researchvirtual care solutions

Identifiers

PMID30990460
PMCPMC6488957
OpenAlexW2906695223

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.