Evidence map›Paper›PMID 29206884›Full record

ArticlePloS one2017

Rapid research and implementation priority setting for wound care uncertainties.

Trish A Gray, Jo C Dumville, Janice Christie, Nicky A Cullum

Abstract read
In one paragraph

Article in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–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.

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

8 citing papers in PubMed.

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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

4 authors.

Trish A GrayDivision of Nursing, Midwifery and Social Work, School of Health Sciences, University of Manchester, Manchester, United Kingdom.ORCID http://orcid.org/0000-0002-8088-0698
Jo C DumvilleDivision of Nursing, Midwifery and Social Work, School of Health Sciences, University of Manchester, Manchester, United Kingdom.
Janice ChristieDivision of Nursing, Midwifery and Social Work, School of Health Sciences, University of Manchester, Manchester, United Kingdom.
Nicky A CullumDivision of Nursing, Midwifery and Social Work, School of Health Sciences, University of Manchester, Manchester, United Kingdom.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionPeople with complex wounds are more likely to be elderly, living with multimorbidity and wound related symptoms. A variety of products are available for managing complex wounds and a range of healthcare professionals are involved in wound care, yet there is a lack of good evidence to guide practice and services. These factors create uncertainty for those who deliver and those who manage wound care. Formal priority setting for research and implementation topics is needed to more accurately target the gaps in treatment and services. We solicited practitioner and manager uncertainties in wound care and held a priority setting workshop to facilitate a collaborative approach to prioritising wound care-related uncertainties.

methodsWe recruited healthcare professionals who regularly cared for patients with complex wounds, were wound care specialists or managed wound care services. Participants submitted up to five wound care uncertainties in consultation with their colleagues, via an on-line survey and attended a priority setting workshop. Submitted uncertainties were collated, sorted and categorised according professional group. On the day of the workshop, participants were divided into four groups depending on their profession. Uncertainties submitted by their professional group were viewed, discussed and amended, prior to the first of three individual voting rounds. Participants cast up to ten votes for the uncertainties they judged as being high priority. Continuing in the professional groups, the top 10 uncertainties from each group were displayed, and the process was repeated. Groups were then brought together for a plenary session in which the final priorities were individually scored on a scale of 0-10 by participants. Priorities were ranked and results presented. Nominal group technique was used for generating the final uncertainties, voting and discussions.

resultsThirty-three participants attended the workshop comprising; 10 specialist nurses, 10 district nurses, seven podiatrists and six managers. Participants had been qualified for a mean of 20.7 years with a mean of 16.8 years of wound care experience. One hundred and thirty-nine uncertainties were submitted electronically and a further 20 were identified on the day of the workshop following lively, interactive group discussions. Twenty-five uncertainties from the total of 159 generated made it to the final prioritised list. These included six of the 20 new uncertainties. The uncertainties varied in focus, but could be broadly categorised into three themes: service delivery and organisation, patient centred care and treatment options. Specialist nurses were more likely to vote for service delivery and organisation topics, podiatrists for patient centred topics, district nurses for treatment options and operational leads for a broad range.

conclusionsThis collaborative priority setting project is the first to engage front-line clinicians in prioritising research and implementation topics in wound care. We have shown that it is feasible to conduct topic prioritisation in a short time frame. This project has demonstrated that with careful planning and rigor, important questions that are raised in the course of clinicians' daily decision making can be translated into meaningful research and implementation initiatives that could make a difference to service delivery and patient care.

Indexed as

Health PersonnelTriageUncertaintyFemaleHumansMaleWounds and Injuries

Identifiers

PMID29206884
PMCPMC5716549

What OpenQuestion holds

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LicenceCC BY
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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.