Evidence map›Paper›PMID 35925656›Full record

ArticleJMIR formative research2022

Optimization of a Quality Improvement Tool for Cancer Diagnosis in Primary Care: Qualitative Study.

Sophie Chima, Javiera Martinez-Gutierrez, Barbara Hunter, Jo-Anne Manski-Nankervis, Jon Emery

Open access · goldAbstract read
In one paragraph

Article in JMIR formative research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 4 pooled it
4.2field-weighted citation impact, top 6% 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

11 citing papers in PubMed, 4 syntheses or guidelines pooled it, 15 citations in OpenAlex.

  1. Why aren't they used? Systematic review of barriers to implementation of clinical decision support systems for early cancer detection in primary care.The British journal of general practice : the journal of the Royal College of General Practitioners · 2026
    Pooled it
  2. Diagnostic Risk Prediction Models for Upper Gastrointestinal Cancers: A Systematic Review.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2025
    Pooled it
  3. Pooled it
  4. Pooled it
  5. Trial
  6. Article
  7. The Educational Value of the Missed Opportunity.Journal of cancer education : the official journal of the American Association for Cancer Education · 2026
    Article
  8. Article
  9. Article
  10. Article
  11. 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

5 authors at 2 institutions in 2 countries.

Sophie ChimaCentre for Cancer Research, Victorian Comprehensive Cancer Centre, University of Melbourne, Melbourne, Australia.ORCID https://orcid.org/0000-0003-1746-5851
Javiera Martinez-GutierrezCentre for Cancer Research, Victorian Comprehensive Cancer Centre, University of Melbourne, Melbourne, Australia.ORCID https://orcid.org/0000-0002-2493-9974
Barbara HunterDepartment of General Practice, University of Melbourne, Melbourne, Australia.ORCID https://orcid.org/0000-0002-1268-3166
Jo-Anne Manski-NankervisDepartment of General Practice, University of Melbourne, Melbourne, Australia.ORCID https://orcid.org/0000-0003-2153-3482
Jon EmeryCentre for Cancer Research, Victorian Comprehensive Cancer Centre, University of Melbourne, Melbourne, Australia.ORCID https://orcid.org/0000-0002-5274-6336
The University of Melbourne · AUPontificia Universidad Católica de Chile · CL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe most common route to a diagnosis of cancer is through primary care. Delays in diagnosing cancer occur when an opportunity to make a timely diagnosis is missed and is evidenced by patients visiting the general practitioner (GP) on multiple occasions before referral to a specialist. Tools that minimize prolonged diagnostic intervals and reduce missed opportunities to investigate patients for cancer are therefore a priority.

objectiveThis study aims to explore the usefulness and feasibility of a novel quality improvement (QI) tool in which algorithms flag abnormal test results that may be indicative of undiagnosed cancer. This study allows for the optimization of the cancer recommendations before testing the efficacy in a randomized controlled trial.

methodsGPs, practice nurses, practice managers, and consumers were recruited to participate in individual interviews or focus groups. Participants were purposively sampled as part of a pilot and feasibility study, in which primary care practices were receiving recommendations relating to the follow-up of abnormal test results for prostate-specific antigen, thrombocytosis, and iron-deficiency anemia. The Clinical Performance Feedback Intervention Theory (CP-FIT) was applied to the analysis using a thematic approach.

resultsA total of 17 interviews and 3 focus groups (n=18) were completed. Participant themes were mapped to CP-FIT across the constructs of context, recipient, and feedback variables. The key facilitators to use were alignment with workflow, recognized need, the perceived importance of the clinical topic, and the GPs' perception that the recommendations were within their control. Barriers to use included competing priorities, usability and complexity of the recommendations, and knowledge of the clinical topic. There was consistency between consumer and practitioner perspectives, reporting language concerns associated with the word cancer, the need for more patient-facing resources, and time constraints of the consultation to address patients' worries.

conclusionsThere was a recognized need for the QI tool to support the diagnosis of cancer in primary care, but barriers were identified that hindered the usability and actionability of the recommendations in practice. In response, the tool has been refined and is currently being evaluated as part of a randomized controlled trial. Successful and effective implementation of this QI tool could support the detection of patients at risk of undiagnosed cancer in primary care and assist in preventing unnecessary delays.

Indexed as

cancerclinical decision support toolClinical Performance Feedback Intervention Theorydiagnosisfeasibilitygeneral practicepilotprimary health carequality improvement

Identifiers

PMID35925656
PMCPMC9389376
OpenAlexW4289836640

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.