ArticlePLOS digital health2023
Real-world evidence from the first online healthcare analytics platform-Livingstone. Validation of its descriptive epidemiology module.
Article in PLOS digital health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 3 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
3 citing papers in PubMed.
- Correction: Real-world evidence from the first online healthcare analytics platform-Livingstone: Validation of its descriptive epidemiology module.PLOS digital health · 2025Article
- Real-World Research on Retinal Diseases Using Health Claims Database: A Narrative Review.Diagnostics (Basel, Switzerland) · 2024Review
- Automating incidence and prevalence analysis in open cohorts.BMC medical research methodology · 2024Article
Corrections and comments
- Erratum issued
Authors and funding
18 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Incidence and prevalence are key epidemiological determinants characterizing the quantum of a disease. We compared incidence and prevalence estimates derived automatically from the first ever online, essentially real-time, healthcare analytics platform-Livingstone-against findings from comparable peer-reviewed studies in order to validate the descriptive epidemiology module. The source of routine NHS data for Livingstone was the Clinical Practice Research Datalink (CPRD). After applying a general search strategy looking for any disease or condition, 76 relevant studies were first retrieved, of which 10 met pre-specified inclusion and exclusion criteria. Findings reported in these studies were compared with estimates produced automatically by Livingstone. The published reports described elements of the epidemiology of 14 diseases or conditions. Lin's concordance correlation coefficient (CCC) was used to evaluate the concordance between findings from Livingstone and those detailed in the published studies. The concordance of incidence values in the final year reported by each study versus Livingstone was 0.96 (95% CI: 0.89-0.98), whilst for all annual incidence values the concordance was 0.93 (0.91-0.94). For prevalence, concordance for the final annual prevalence reported in each study versus Livingstone was 1.00 (0.99-1.00) and for all reported annual prevalence values, the concordance was 0.93 (0.90-0.95). The concordance between Livingstone and the latest published findings was near perfect for prevalence and substantial for incidence. For the first time, it is now possible to automatically generate reliable descriptive epidemiology from routine health records, and in near-real time. Livingstone provides the first mechanism to rapidly generate standardised, descriptive epidemiology for all clinical events from real world data.
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.