Evidence map›Paper›PMID 37434192›Full record

ArticleBMC pulmonary medicine2023

Validation of the recording of idiopathic pulmonary fibrosis in routinely collected electronic healthcare records in England.

Ann Morgan, Rikisha Shah Gupta, Peter M George, Jennifer K Quint

Abstract 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 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.

Ann Morgan *School of Public Health, Imperial College London, Level 9, Sir Michael Uren Hub, White City Campus, 86 Wood Lane, W12 0BZ, London, UK.
Rikisha Shah Gupta *School of Public Health, Imperial College London, Level 9, Sir Michael Uren Hub, White City Campus, 86 Wood Lane, W12 0BZ, London, UK.
Peter M GeorgeNational Heart and Lung Institute, Imperial College London, Level 9, Sir Michael Uren Hub, White City Campus, 86 Wood Lane, W12 0BZ, London, UK.
Jennifer K QuintSchool of Public Health, Imperial College London, Level 9, Sir Michael Uren Hub, White City Campus, 86 Wood Lane, W12 0BZ, London, UK. j.quint@imperial.ac.uk.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundRoutinely-collected healthcare data provide a valuable resource for epidemiological research. Validation studies have shown that for most conditions, simple lists of clinical codes can reliably be used for case finding in primary care, however, studies exploring the robustness of this approach are lacking for diseases such as idiopathic pulmonary fibrosis (IPF) which are largely managed in secondary care.

methodUsing the UK's Clinical Practice Research Datalink (CPRD) Aurum dataset, which comprises patient-level primary care records linked to national hospital admissions and cause-of-death data, we compared the positive predictive value (PPV) of eight diagnostic algorithms. Algorithms were developed based on the literature and IPF diagnostic guidelines using combinations of clinical codes in primary and secondary care (SNOMED-CT or ICD-10) with/without additional information. The positive predictive value (PPV) was estimated for each algorithm using the death record as the gold standard. Utilization of the reviewed codes across the study period was observed to evaluate any change in coding practices over time.

resultA total of 17,559 individuals had a least one record indicative of IPF in one or more of our three linked datasets between 2008 and 2018. The PPV of case-finding algorithms based on clinical codes alone ranged from 64.4% (95%CI:63.3-65.3) for a "broad" codeset to 74.9% (95%CI:72.8-76.9) for a "narrow" codeset comprising highly-specific codes. Adding confirmatory evidence, such as a CT scan, increased the PPV of our narrow code-based algorithm to 79.2% (95%CI:76.4-81.8) but reduced the sensitivity to under 10%. Adding evidence of hospitalisation to the standalone code-based algorithms also improved PPV, (PPV = 78.4 vs. 64.4%; sensitivity = 53.5% vs. 38.1%). IPF coding practices changed over time, with the increased use of specific IPF codes.

conclusionHigh diagnostic validity was achieved by using a restricted set of IPF codes. While adding confirmatory evidence increased diagnostic accuracy, the benefits of this approach need to be weighed against the inevitable loss of sample size and convenience. We would recommend use of an algorithm based on a broader IPF code set coupled with evidence of hospitalisation.

Indexed as

Idiopathic Pulmonary FibrosisSecondary Health CareAlgorithmsElectronicsEnglandHumansCPRDDiagnostic codesHESIdiopathic pulmonary fibrosisInterstitial lung diseasePulmonary fibrosisValidation

Identifiers

PMID37434192
PMCPMC10337174

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Registered trials

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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.