Evidence map›Paper›PMID 28103848›Full record

ArticleBMC medical informatics and decision making2017

The CRISP colorectal cancer risk prediction tool: an exploratory study using simulated consultations in Australian primary care.

Jennifer G Walker, Adrian Bickerstaffe, Nadira Hewabandu, Sanjay Maddumarachchi, James G Dowty, CRECRC, Mark Jenkins, Marie Pirotta, Fiona M Walter, Jon D Emery

Abstract read
In one paragraph

Article in BMC medical informatics and decision making, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed, 2 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.

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

23 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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  17. A risk-stratified approach to colorectal cancer prevention and diagnosis.Nature reviews. Gastroenterology & hepatology · 2020
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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

10 authors.

Jennifer G WalkerCentre for Cancer Research, Department of General Practice, VCCC, University of Melbourne, Level 10, 305 Grattan Street, Melbourne, VIC, 3010, Australia. walker@unimelb.edu.au.
Adrian BickerstaffeCentre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, Australia.
Nadira HewabanduCentre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, Australia.
Sanjay MaddumarachchiCentre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, Australia.
James G DowtyCentre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, Australia.
CRECRC
Mark JenkinsCentre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, Australia.
Marie PirottaCentre for Cancer Research, Department of General Practice, VCCC, University of Melbourne, Level 10, 305 Grattan Street, Melbourne, VIC, 3010, Australia.
Fiona M WalterCentre for Cancer Research, Department of General Practice, VCCC, University of Melbourne, Level 10, 305 Grattan Street, Melbourne, VIC, 3010, Australia.
Jon D EmeryCentre for Cancer Research, Department of General Practice, VCCC, University of Melbourne, Level 10, 305 Grattan Street, Melbourne, VIC, 3010, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIn Australia, screening for colorectal cancer (CRC) with colonoscopy is meant to be reserved for people at increased risk, however, currently there is a mismatch between individuals' risk of CRC and the type of CRC screening they receive. This paper describes the development and optimisation of a Colorectal cancer RISk Prediction tool ('CRISP') for use in primary care. The aim of the CRISP tool is to increase risk-appropriate CRC screening.

methodsCRISP development was informed by previous experience with developing risk tools for use in primary care and a systematic review of the evidence. A CRISP prototype was used in simulated consultations by general practitioners (GPs) with actors as patients. GPs were interviewed to explore their experience of using CRISP, and practice nurses (PNs) and practice managers (PMs) were interviewed after a demonstration of CRISP. Transcribed interviews and video footage of the 'consultations' were qualitatively analyzed. Themes arising from the data were mapped onto Normalization Process Theory (NPT).

resultsFourteen GPs, nine PNs and six PMs were recruited from 12 clinics. Results were described using the four constructs of NPT: 1) Coherence: Clinicians understood the rationale behind CRISP, particularly since they were familiar with using risk tools for other conditions; 2) Cognitive participation: GPs welcomed the opportunity CRISP provided to discuss healthy and unhealthy behaviors with their patients, but many GPs challenged the screening recommendation generated by CRISP; 3) Collective Action: CRISP disrupted clinician-patient flow if the GP was less comfortable with computers. GP consultation time was a major implementation barrier and overall consensus was that PNs have more capacity and time to use CRISP effectively; 4) Reflexive monitoring: Limited systematic monitoring of new interventions is a potential barrier to the sustainable embedding of CRISP.

conclusionsCRISP has the potential to improve risk-appropriate CRC screening in primary care but was considered more likely to be successfully implemented as a nurse-led intervention.

Indexed as

Medical Informatics ApplicationsAdultAgedAustraliaColorectal NeoplasmsComputer SimulationDiagnosis, Computer-AssistedFemaleGeneral PractitionersHumansMaleMiddle AgedNursesPrimary Health CareRisk AssessmentBowel cancer screeningCancer screeningColorectal cancerColorectal cancer risk assessmentColorectal cancer risk predictionGeneral practitionersPrimary care

Identifiers

PMID28103848
PMCPMC5248518

What OpenQuestion holds

Textmetadata
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.