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Browse normalized, publication-ready research with direct links to its evidence and source.
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Readable research linked to original sources
Browse normalized, publication-ready research with direct links to its evidence and source.
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Readable research linked to original sources
Browse normalized, publication-ready research with direct links to its evidence and source.
52 articles
Newest firstMOTIVATION: Opioid use disorder (OUD) often emerges following prescription opioid exposure and follows a dynamic clinical course characterized by onset, remission, and relapse. Large-scale cohorts linking electronic health records (EHR) with rich longitudinal survey data, such as the All of Us Research Program, enable computational modeling of stage-specific risk and provide an opportunity to connect predictive fa…
Open article record in new tab ↗People with narcolepsy experience delays in diagnosis and inconsistent post-diagnosis care, but the pattern and scale of their healthcare use is poorly described. In this population-based cohort study, we used primary care and linked hospital activity data to compare healthcare use in people with narcolepsy (n=2,772) and a matched comparison group in England (n=13,860). Narcolepsy was defined by a first coded reco…
Open article record in new tab ↗Background Prenatal substance exposure (PSE) occurs when an individual is exposed to substances in utero. PSEs may have lasting effects on mental health. We tested whether PSEs show threshold, cumulative, or individual substance associations with childhood psychiatric diagnoses. Methods Clinical variables (demographics, ICD-9/10 diagnoses, PSE history) were extracted from electronic health records from the Univers…
Background Prenatal substance exposure (PSE) occurs when an individual is exposed to substances in utero. PSEs may have lasting effects on mental health. We tested whether PSEs show threshold, cumulative, or individual substance associations with childhood psychiatric diagnoses. Methods Clinical variables (demographics, ICD-9/10 diagnoses, PSE history) were extracted from electronic health records from the Univers…
ObjectiveThis study aimed to train and evaluate supervised machine learning walgorithms using electronic health record (EHR) data to accurately estimate gestational age at delivery. Materials and MethodsWe trained random forest, gradient boosting, and ensemble models on EHR data of mother-infant dyads from Vanderbilt University Medical Center(VUMC) and replicated the analyses at University of Michigan (UMich). We…
BackgroundElectronic health records (EHRs) with clinical decision support tools are now ubiquitous in healthcare organizations. Clinical foundation models (CFMs) pretrained on large-scale, heterogeneous structured EHR data have emerged as a powerful approach to improve predictive performance and generalizability. Meanwhile, large language models (LLMs) pretrained on broad data sources are being applied to an expan…
Open article record in new tab ↗OBJECTIVEAnthropometric data are critical in paediatric care, routinely assessed during clinical visits, and available in electronic health records (EHRs). We describe the feasibility of extracting anthropometric data from heterogeneous EHR systems of Swiss childrens hospitals, evaluate their availability and quality, and assess the cohorts representativeness of the general population. METHODSIn this multicentre s…
Open article record in new tab ↗Healthcare system performance evaluation is constrained by episodic performance indicators and process mining techniques that fail to accommodate the scale, heterogeneity, and temporal complexity of real-world clinical pathways. Electronic health records enable reconstructing patient journeys that capture how care processes unfold across fragmented healthcare services. Here we present ClinicalTAAT, a time-aware tr…
We describe the harmonisation of five UK electronic birth cohorts to the Observational Medical Outcomes Partnership (OMOP) Common Data Model, creating a large-scale, standardised resource for maternal and child health research. The Mother and Infant Research Data Analysis (MIREDA) partnership developed and implemented reproducible guidelines for mapping maternal-infant relationships and identifying pregnancy episo…
IntroductionHealthcare organizations have begun incorporating screening procedures for social determinants of health (SDOH) into care, recognizing the impact these factors can have on health outcomes. We aimed to present methods for evaluating redundancy in the risk information gained across SDOH questions and for evaluating whether demographic biases are present in whether patients were asked SDOH questions and w…
Open article record in new tab ↗Background Cannabis use is elevated in youth with depression and attention-deficit/hyperactivity disorder (ADHD), but drivers of this increase remain underexplored. The self-medication hypothesis suggests cannabis is used by patients for mood regulation, a common difficulty in ADHD and depression. This study aimed to examine associations between mood instability and cannabis use in a large, representative clinical…
Modelling the prodrome to severe mental disorders (SMD), including unipolar mood disorders (UMD), bipolar mood disorders (BMD) and psychotic disorders (PSY), should consider both the evolution and interactions of symptoms and substance use (prodromal features) over time. Temporal network analysis can detect causal dependence between and within prodromal features by representing prodromal features as nodes, with th…
Background The study of the trigeminal autonomic cephalalgias (TAC) has been limited by difficulty aggregating sufficient numbers of patients. We used the Epic Cosmos electronic health record research platform to harness nationwide data from health care systems across the United States using the Epic electronic health record to analyze the prevalence, demographics, comorbid conditions and treatments for the TACs.…
Open article record in new tab ↗Clinical codes are unique identifiers used in electronic health records to document specific information, such as diagnoses, procedures or medications. Because of their structured and systematic nature, they are often used for research, audit and service evaluation. Knowing how frequently certain codes are recorded can be invaluable in planning such work. For example, not all events are recorded with equal frequen…
Open article record in new tab ↗ImportanceSleep-disordered breathing (SDB) is preventable but underdiagnosed, with disparities among sociodemographic groups with limited material and social resources, partly driven by community-level environmental and social conditions along with healthcare-related factors. ObjectivesWe sought to investigate associations between multifactorial community-level environmental, social, and health burdens and SDB pre…
Intensive care units (ICUs) manage critically ill patients whose clinical outcomes rely on timely and accurate decision-making. Predictive modeling using electronic health records (EHRs) has shown promise in forecasting adverse events such as in-hospital mortality. However, constructing robust and generalizable models typically requires large-scale, multi-institutional datasets. Privacy regulations such as HIPAA a…
Open article record in new tab ↗BACKGROUNDDepression is a disabling disorder with variable outcomes. In severe cases treatment is provided by specialist mental health care services, yet there is a lack of real-world evidence demonstrating how depression is managed within these settings, and consequently, a limited understanding of how to improve care for this population. AIMSWe examine the characteristics of patients receiving secondary mental h…
ObjectiveEvaluate how often encounter diagnoses of self-harm soon after an emergency department visit for self-harm represent new self-harm events. MethodsElectronic health records (EHR) and insurance claims data from a large integrated health system identified emergency department encounters for injury or poisoning coded as self-harm and then selected those with another encounter diagnosis of self-harm occurring…
Open article record in new tab ↗Electronic healthcare records (EHR) use codes from different vocabularies to describe medical occurrences, often varying by type of care and country. Common data models (CDM) such as the Observational Medical Outcomes Partnership (OMOP) have been developed to enable the combination and comparison of heterogeneous datasets. We use the OMOP Standard Vocabularies to standardise two English EHR datasets and assess the…
Open article record in new tab ↗ObjectiveElectronic Health Records (EHRs) provide information to explore those at risk of various diseases, though studying entire populations is limited by data availability, potentially introducing biases. We compared different samples, varied by type of hospital contact, to assess the impact on missing data and model results. Materials and MethodsUsing Escherichia coli bloodstream infections as a case study, we…
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