| アブストラクト | 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. |
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| ジャーナル名 | PLOS digital health |
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| 投稿日 | 2023/7/25 |
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| 投稿者 | Heywood, Benjamin R; Morgan, Christopher Ll; Berni, Thomas R; Summers, Darren R; Jones, Bethan I; Jenkins-Jones, Sara; Holden, Sarah E; Riddick, Lauren D; Fisher, Harry; Bateman, James D; Bannister, Christian A; Threlfall, John; Buxton, Aron; Shepherd, Christopher P; Mathias, Elgan R; Thomason, Rhiannon K; Hubbuck, Ellen; Currie, Craig J |
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| 組織名 | Human Data Sciences, Cardiff, United Kingdom.;School of Mathematics, Cardiff University, Cardiff, United Kingdom.;Human Data Sciences, North Carolina, United States of America.;School of Computing, Cardiff University, Cardiff, United Kingdom.;Division of Population Medicine, School of Medicine, Cardiff University, Cardiff,;United Kingdom. |
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| Pubmed リンク | https://www.ncbi.nlm.nih.gov/pubmed/37490430/ |
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