Evidence map›Paper›PMID 37974137›Full record

ArticleBMC pulmonary medicine2023

Assessing, updating and utilising primary care smoking records for lung cancer screening.

Grace McCutchan, Jean Engela-Volker, Philip Anyanwu, Kate Brain, Nicole Abel, Sinan Eccles

Open access · goldAbstract read
In one paragraph

Article in BMC pulmonary medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.8field-weighted citation impact, top 13% 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

6 citing papers in PubMed, 7 citations in OpenAlex.

  1. Article
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  4. Enhancing Post-Discharge Care for People Who Have Had an Acute Myocardial Infarction in Portugal: Insights From Patient Journey Mapping.Health expectations : an international journal of public participation in health care and health policy · 2025
    Article
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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

6 authors at 2 institutions in 1 country.

Grace McCutchanDivision of Population Medicine, School of Medicine, Cardiff University, Cardiff, Wales, UK. mccutchanGM@cardiff.ac.uk.
Jean Engela-VolkerDivision of Population Medicine, School of Medicine, Cardiff University, Cardiff, Wales, UK.
Philip AnyanwuDivision of Population Medicine, School of Medicine, Cardiff University, Cardiff, Wales, UK.
Kate BrainDivision of Population Medicine, School of Medicine, Cardiff University, Cardiff, Wales, UK.
Nicole AbelDivision of Population Medicine, School of Medicine, Cardiff University, Cardiff, Wales, UK.
Sinan EcclesWales Cancer Network, NHS Wales Executive, Cardiff, UK.
Cardiff University · GBNational Health Service Wales · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundLung cancer screening with low-dose computed tomography for high-risk populations is being implemented in the UK. However, inclusive identification and invitation of the high-risk population is a major challenge for equitable lung screening implementation. Primary care electronic health records (EHRs) can be used to identify lung screening-eligible individuals based on age and smoking history, but the quality of EHR smoking data is limited. This study piloted a novel strategy for ascertaining smoking status in primary care and tested EHR search combinations to identify those potentially eligible for lung cancer screening.

methodsSeven primary care General Practices in South Wales, UK were included. Practice-level data on missing tobacco codes in EHRs were obtained. To update patient EHRs with no tobacco code, we developed and tested an algorithm that sent a text message request to patients via their GP practice to update their smoking status. The patient's response automatically updated their EHR with the relevant tobacco code. Four search strategies using different combinations of tobacco codes for the age range 55-74

resultsTobacco codes were not recorded for 3.3% of patients (n = 724/21,956). Of those with no tobacco code and a validated mobile telephone number (n = 333), 55% (n = 183) responded via text message with their smoking status. Of the 183 patients who responded, 43.2% (n = 79) had a history of smoking and were potentially eligible for lung cancer screening. Applying the BROAD search strategy was projected to result in an additional 148,522 patients eligible to receive an invitation for lung cancer screening when compared to the RECENT strategy.

conclusionAn automated text message system could be used to improve the completeness of primary care EHR smoking data in preparation for rolling out a national lung cancer screening programme. Varying the search strategy for tobacco codes may have profound implications for the size of the population eligible for lung-screening invitation.

Indexed as

Lung NeoplasmsAgedEarly Detection of CancerHumansMiddle AgedPrimary Health CareRisk FactorsSmokingElectronic healthcare recordsLow-dose CTLung cancerLung cancer screeningPrimary careSmoking

Identifiers

PMID37974137
PMCPMC10655268
OpenAlexW4388728872

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.