ReviewPragmatic and observational research2024
UK Electronic Healthcare Records for Research: A Scientometric Analysis of Respiratory, Cardiovascular, and COVID-19 Publications.
Review in Pragmatic and observational research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled 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.
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.
Who cites it
4 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A Systematic Review of Codelists to Identify Chronic Bronchitis and Emphysema in Routine Electronic Healthcare Record Data and Derivation of a Standardized Codelist for Future Research.International journal of chronic obstructive pulmonary disease · 2025Pooled it
- Academic impact and research data utilisation of the clinical practice research datalink: scientometric analyses.European journal of epidemiology · 2026Article
- Validity of Using Prescription Medications to Classify Disease - A Retrospective Observational Study Using Routinely Collected Electronic Health Records from the UK.Pragmatic and observational research · 2026Article
- Using Routinely Collected Electronic Healthcare Record Data to Investigate Fibrotic Multimorbidity in England [Response to Letter].Clinical epidemiology · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Routinely collected electronic healthcare records (EHRs) document many details of a person's health, including demographics, preventive services, symptoms, tests, disease diagnoses and prescriptions. Although not collected for research purposes, these data provide a wealth of information which can be incorporated into epidemiological investigations, and records can be analysed to understand a range of important health questions. We aimed to understand the use of routinely collected health data in epidemiological studies relating to three of the most common chronic respiratory conditions, namely: asthma, chronic obstructive pulmonary disease (COPD) and interstitial lung disease (ILD). We also characterised studies using EHR data to investigate respiratory diseases more generally, relative to cardiovascular disease and COVID-19, to understand trends in the use of these data. Methods: We conducted a search of the Scopus database, to identify original research articles (irrespective of date) which used data from one of the following most frequently used UK EHR databases: Clinical Practice Research Datalink (including General Practice Research Database (CPRD's predecessor)), The Health Improvement Network and QResearch, defined through the presence of keywords. These databases were selected as they had been previously included in the works of Vezyridis and Timmons. Findings: A total of 716 manuscripts were included in the analysis of the three chronic respiratory conditions. The majority investigated either asthma or COPD, whilst only 28 manuscripts investigated ILD. The number of publications has increased for respiratory conditions over the past 10 years (888% increase from 2000 to 2022) but not as much as for cardiovascular diseases (1105%). These data have been used to investigate comorbidities, off-target effects of medication, as well as assessing disease incidence and prevalence. Most papers published across all three domains were in journals with an impact factor less than 10.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.