ReviewDiabetologia2018
Promises and pitfalls of electronic health record analysis.
Review in Diabetologia, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 64 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
64 citing papers in PubMed.
- Article
- Integrating social determinants of health and genetic risk in disease risk models.American journal of human genetics · 2026Article
- Genetic and sociodemographic factors associated with trajectories of physical and mental health multimorbidity in a South Asian cohort in the UK: A multistate modelling analysis.PLoS medicine · 2026Article
- Methods for incorporating test result information within the high-dimensional propensity score framework: application in UK electronic health record data.BMC medical research methodology · 2026Article
- Article
- Combining polygenic risk scores to understand genetic liability to physical-mental health multimorbidity in UK Biobank.Human molecular genetics · 2026Article
- Rising obesity and shifting disease patterns in Saudi Arabia: a nine-year population-based analysis of chronic disease burden and multimorbidity profiles.BMC public health · 2026Article
- Harmonizing self-reported and free text medication data: a reproducible pipeline for gerontological research.BMC medical informatics and decision making · 2025Article
- Unmeasured confounding and misclassification in studies estimating vaccine effectiveness against hospitalisation and death using electronic health records (EHRs): an evaluation of a multi-country European retrospective cohort study.BMC medical research methodology · 2025Article
- Defining quality indicators for atherosclerotic cardiovascular diseases in primary care, extractable from the electronic health record: a RAND-modified Delphi method.BMC primary care · 2025Article
- Simultaneously Dealing With Immortal Time Bias and Residual Confounding: A Case Study of a High-Dimensional Propensity Score Approach With a Nested Case-Control Framework in Multiple Sclerosis Research.Pharmacoepidemiology and drug safety · 2025Article
- Integrating Misclassified EHR Outcomes With Validated Outcomes From a Non-Probability Sample.Statistics in medicine · 2025Article
- Utility of long-term systolic blood pressure variability for predicting the development of type 2 diabetes mellitus.Nagoya journal of medical science · 2025Article
- Comment on "Associations of semaglutide with first-time diagnosis of Alzheimer's disease in patients with type 2 diabetes: Target trial emulation using nationwide real-world data in the US".Alzheimer's & dementia : the journal of the Alzheimer's Association · 2025Article
- Article
- Association of handgrip strength with aortic stenosis among adults aged 60 years and older: evidence from the 157097 UK Biobank participants.Journal of geriatric cardiology : JGC · 2024Article
- The role and limitations of electronic medical records versus patient interviews for determining symptoms of, underlying comorbidities of, and medication use by patients with COVID-19.American journal of epidemiology · 2024Article
- Usability evaluation of electronic health records at the trauma and emergency directorates at the Komfo Anokye teaching hospital in the Ashanti region of Ghana.BMC medical informatics and decision making · 2024Article
- Clinical coding of long COVID in primary care 2020-2023 in a cohort of 19 million adults: an OpenSAFELY analysis.EClinicalMedicine · 2024Article
- Temporal Risk of Nonfatal Cardiovascular Events After Chronic Obstructive Pulmonary Disease Exacerbation: A Population-based Study.American journal of respiratory and critical care medicine · 2024Article
4 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
Routinely collected electronic health records (EHRs) are increasingly used for research. With their use comes the opportunity for large-scale, high-quality studies that can address questions not easily answered by randomised clinical trials or classical cohort studies involving bespoke data collection. However, the use of EHRs generates challenges in terms of ensuring methodological rigour, a potential problem when studying complex chronic diseases such as diabetes. This review describes the promises and potential of EHRs in the context of diabetes research and outlines key areas for caution with examples. We consider the difficulties in identifying and classifying diabetes patients, in distinguishing between prevalent and incident cases and in dealing with the complexities of diabetes progression and treatment. We also discuss the dangers of introducing time-related biases and describe the problems of inconsistent data recording, missing data and confounding. Throughout, we provide practical recommendations for good practice in conducting EHR studies and interpreting their results.
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.