ArticleJournal of clinical epidemiology2016
Improved incidence estimates from linked vs. stand-alone electronic health records.
Article in Journal of clinical epidemiology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
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
24 citing papers in PubMed, 46 citations in OpenAlex.
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- Comparative Analysis of the Incidence, Prevalence, and Survival of 8 Types of Parkinsonism in a Population-Based Study with 367 Million Person Years of Observation over 21 Years.Movement disorders clinical practice · 2026Observational
- Accuracy of the recording of pneumonia events in English electronic healthcare record data in patients with chronic obstructive pulmonary disease.Pneumonia (Nathan Qld.) · 2024Article
- Analysis of incidence of motor neuron disease in England 1998-2019: use of three linked datasets.Amyotrophic lateral sclerosis & frontotemporal degeneration · 2022Article
- Do routine hospital data accurately record comorbidity in advanced kidney disease populations? A record linkage cohort study.BMC nephrology · 2021Article
- Non-benzodiazepine hypnotic use for sleep disturbance in people aged over 55 years living with dementia: a series of cohort studies.Health technology assessment (Winchester, England) · 2021Article
- Predicting incident delirium diagnoses using data from primary-care electronic health records.Age and ageing · 2020Article
- Article
- Primary care risk stratification in COPD using routinely collected data: a secondary data analysis.NPJ primary care respiratory medicine · 2019Article
- Approach to record linkage of primary care data from Clinical Practice Research Datalink to other health-related patient data: overview and implications.European journal of epidemiology · 2019Article
- Performing studies using the UK Clinical Practice Research Datalink: to link or not to link?European journal of epidemiology · 2018Article
- Incidence and antibiotic prescribing for clinically diagnosed urinary tract infection in older adults in UK primary care, 2004-2014.PloS one · 2018Observational
- Underrecording of osteoarthritis in United Kingdom primary care electronic health record data.Clinical epidemiology · 2018Article
- Big Data's Role in Precision Public Health.Frontiers in public health · 2018Review
- Article
- Population trends in the incidence and initial management of osteoarthritis: age-period-cohort analysis of the Clinical Practice Research Datalink, 1992-2013.Rheumatology (Oxford, England) · 2017Article
- Trends in the burden of varicella in UK general practice.Epidemiology and infection · 2017Article
- Using a linked database for epidemiology across the primary and secondary care divide: acute kidney injury.BMC medical informatics and decision making · 2017Article
- Improved outcomes in ex-smokers with COPD: a UK primary care observational cohort study.The European respiratory journal · 2017Observational
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 2 institutions in 1 country.
Funding
Abstract
objectiveElectronic health records are widely used for public health research, and linked data sources are increasingly available. The added value of using linked records over stand-alone data has not been quantified for common conditions such as community-acquired pneumonia (CAP). STUDY DESIGN AND
settingOur cohort comprised English patients aged ≥65 years from the Clinical Practice Research Datalink, eligible for record linkage to Hospital Episode Statistics. Stand-alone general practice (GP) records were used to calculate CAP incidence over time using population-averaged Poisson regression. Incidence was then recalculated for the same patients using their linked GP-hospital admission data. Results of the two analyses were compared.
resultsOver 900,000 patients were included in each analysis. Population-averaged CAP incidence was 39% higher using the linked data than stand-alone data. This difference grew over time from 7% in 1997 to 83% by 2010. An increasingly larger number of pneumonia events were recorded in the hospital admission data compared to the GP data over time.
conclusionUse of primary or secondary care data in isolation may not give accurate incidence estimates for important infections in older populations. Further work is needed to establish the extent of this finding in other diseases, age groups, and populations.
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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.