Evidence map›Paper›PMID 37943601›Full record

ArticleJMIR research protocols2023

Clinical Utility Assessment of a Nursing Checklist Identifying Complex Care Needs Due to Inequities Among Ambulatory Patients With Cancer: Protocol for a Mixed Methods Study.

Holly Chung, Amelia Hyatt, Elizabeth Crone, Donna Milne, Sanchia Aranda, Karla Gough, Meinir Krishnasamy

Open access · goldAbstract read
In one paragraph

Article in JMIR research protocols, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact, top 80% 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

2 citing papers in PubMed, 0 citations in OpenAlex.

  1. Social Needs Screening Tools for Clinical Populations in Australia and New Zealand: A Scoping Review and Critical Analysis.Health expectations : an international journal of public participation in health care and health policy · 2026
    Article
  2. Equity in cancer care: mixed methods clinical utility analysis of the Nursing Equity Assessment Tool (NEAT) to identify disadvantage in newly diagnosed cancer patients.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2024
    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

7 authors at 2 institutions in 1 country.

Holly ChungAcademic Nursing Unit, Peter MacCallum Cancer Centre, Melbourne, Australia.ORCID https://orcid.org/0000-0003-1608-4213
Amelia HyattDepartment of Health Services Research and Implementation Science, Peter MacCallum Cancer Centre, Melbourne, Australia.ORCID https://orcid.org/0000-0003-2322-7817
Elizabeth CroneAcademic Nursing Unit, Peter MacCallum Cancer Centre, Melbourne, Australia.ORCID https://orcid.org/0000-0002-2705-7459
Donna MilneDepartment of Nursing, School of Health Sciences, University of Melbourne, Melbourne, Australia.ORCID https://orcid.org/0000-0002-9874-2023
Sanchia ArandaDepartment of Nursing, School of Health Sciences, University of Melbourne, Melbourne, Australia.ORCID https://orcid.org/0000-0003-4170-9799
Karla Gough *Department of Health Services Research and Implementation Science, Peter MacCallum Cancer Centre, Melbourne, Australia.ORCID https://orcid.org/0000-0003-2819-4217
Meinir Krishnasamy *Academic Nursing Unit, Peter MacCallum Cancer Centre, Melbourne, Australia.ORCID https://orcid.org/0000-0002-3050-4213
The University of Melbourne · AUPeter MacCallum Cancer Centre · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDisparities in cancer incidence, complex care needs, and poor health outcomes are largely driven by structural inequities stemming from social determinants of health. To date, no evidence-based clinical tool has been developed to identify newly diagnosed patients at risk of poorer outcomes. Specialist cancer nurses are well-positioned to ameliorate inequity of opportunity for optimal care, treatment, and outcomes through timely screening, assessment, and intervention. We designed a nursing complexity checklist (the "Checklist") to support these activities, with the ultimate goal of improving equitable experiences and outcomes of care. This study aims to generate evidence regarding the clinical utility of the Checklist.

objectiveThe primary objectives of this study are to provide qualitative evidence regarding key aspects of the Checklist's clinical utility (appropriateness, acceptability, and practicability), informed by Smart's multidimensional model of clinical utility. Secondary objectives explore the predictive value of the Checklist and concordance between specific checklist items and patient-reported outcome measures.

methodsThis prospective mixed methods case series study will recruit up to 60 newly diagnosed patients with cancer and 10 specialist nurses from a specialist cancer center. Nurses will complete the Checklist with patient participants. Within 2 weeks of Checklist completion, patients will complete 5 patient-reported outcome measures with established psychometric properties that correspond to specific checklist items and an individual semistructured interview to explore Checklist clinical utility. Interviews with nurses will occur 12 and 24 weeks after they first complete a checklist, exploring perceptions of the Checklist's clinical utility including barriers and facilitators to implementation. Data describing planned and unplanned patient service use will be collected from patient follow-up interviews at 12 weeks and the electronic medical record at 24 weeks after Checklist completion. Descriptive statistics will summarize operational, checklist, and electronic medical record data. The predictive value of the Checklist and the relationship between specific checklist items and relevant patient-reported outcome measures will be examined using descriptive statistics, contingency tables, measures of association, and plots as appropriate. Qualitative data will be analyzed using a content analysis approach.

resultsThis study was approved by the institution's ethics committee. The enrollment period commenced in May 2022 and ended in November 2022. In total, 37 patients with cancer and 7 specialist cancer nurses were recruited at this time. Data collection is scheduled for completion at the end of May 2023.

conclusionsThis study will evaluate key clinical utility dimensions of a nursing complexity checklist. It will also provide preliminary evidence on its predictive value and information to support its seamless implementation into everyday practice including, but not limited to, possible revisions to the Checklist, instructions, and training for relevant personnel. Future implementation of this Checklist may improve equity of opportunity of access to care for patients with cancer. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/48432.

Indexed as

barriercancercancer carecancer nursingcaregiverchecklistclinical utilitydisparityequitynursenursingnursing checklistoncologypatient outcomesocial determinants of healthspecialist nurse

Identifiers

PMID37943601
PMCPMC10667971
OpenAlexW4386206391

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.