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Large-scale characterization of gender differences in diagnosis prevalence and time to diagnosis.

ABSTRACT: We carry out an analysis of gender differences in patterns of disease diagnosis across four large observational health datasets and find that women are routinely older when first assigned most diagnoses. Among 112 acute and chronic diseases, women experience longer lengths of time between symptom onset and disease diagnosis than men for most diseases regardless of metric used, even when only symptoms common to both genders are considered. These findings are consistent for patients with private as well as government insurance. Our analysis highlights systematic gender differences in patterns of disease diagnosis and suggests that symptoms of disease are measured or weighed differently for women and men. Data and code leverage the open-source common data model and analytic code and results are publicly available.

SUBMITTER: Sun TY

PROVIDER: S-EPMC10592987 | biostudies-literature | 2023 Oct

REPOSITORIES: biostudies-literature

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Large-scale characterization of gender differences in diagnosis prevalence and time to diagnosis.

Sun Tony Yue TY Hardin Jill J Nieva Harry Reyes HR Natarajan Karthik K Cheng Ru-Fong RF Ryan Patrick P Elhadad Noémie N

medRxiv : the preprint server for health sciences 20231016

We carry out an analysis of gender differences in patterns of disease diagnosis across four large observational health datasets and find that women are routinely older when first assigned most diagnoses. Among 112 acute and chronic diseases, women experience longer lengths of time between symptom onset and disease diagnosis than men for most diseases regardless of metric used, even when only symptoms common to both genders are considered. These findings are consistent for patients with private a ...[more]

PMID: 37873224

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