A5048645102- Machine Learning in Healthcare
- COVID-19 Clinical Research Studies
- Health Systems, Economic Evaluations, Quality of Life
- Chronic Disease Management Strategies
- Cardiac electrophysiology and arrhythmias
- Artificial Intelligence in Healthcare
- Biomedical Text Mining and Ontologies
- ECG Monitoring and Analysis
- Asthma and respiratory diseases
- Heparin-Induced Thrombocytopenia and Thrombosis
- Advanced Causal Inference Techniques
- Long-Term Effects of COVID-19
- Statistical Methods in Clinical Trials
- SARS-CoV-2 and COVID-19 Research
- COVID-19 diagnosis using AI
- Chronic Obstructive Pulmonary Disease (COPD) Research
- Heart Rate Variability and Autonomic Control
- Venous Thromboembolism Diagnosis and Management
- Rheumatoid Arthritis Research and Therapies
- COVID-19 and healthcare impacts
- Platelet Disorders and Treatments
- Blood Pressure and Hypertension Studies
- Artificial Intelligence in Healthcare and Education
- Electronic Health Records Systems
- Dementia and Cognitive Impairment Research
Erasmus MC
2016-2025
Erasmus University Rotterdam
2015-2025
Zealand University Hospital
2023
Janssen (United States)
2020
King's College London
2017
Aarhus University Hospital
2017
Leibniz Institute for Prevention Research and Epidemiology - BIPS
2017
University of Bologna
2017
Società Italiana di Medicina Generale
2017
University of Messina
2017
The vision of creating accessible, reliable clinical evidence by accessing the clincial experience hundreds millions patients across globe is a reality. Observational Health Data Sciences and Informatics (OHDSI) has built on learnings from Medical Outcomes Partnership to turn methods research insights into suite applications exploration tools that move field closer ultimate goal generating about all aspects healthcare serve needs patients, clinicians other decision-makers around world.
Non-alcoholic fatty liver disease (NAFLD) is a common condition that progresses in some patients to steatohepatitis (NASH), cirrhosis and hepatocellular carcinoma (HCC). Here we used healthcare records of 18 million adults estimate risk acquiring advanced diagnoses with NAFLD or NASH compared individually matched controls. Data were extracted from four European primary care databases representing the UK, Netherlands, Italy Spain. Patients recorded diagnosis (NAFLD/NASH) followed up for...
Non-alcoholic fatty liver disease (NAFLD) is the most common cause of worldwide. It affects an estimated 20% general population, based on cohort studies varying size and heterogeneous selection. However, prevalence incidence recorded NAFLD diagnoses in unselected real-world health-care records unknown. We harmonised health from four major European territories assessed age- sex-specific point over past decade.Data were extracted The Health Improvement Network (UK), Search Database (Italy),...
To estimate the risk of acute myocardial infarction (AMI) or stroke in adults with non-alcoholic fatty liver disease (NAFLD) steatohepatitis (NASH).Matched cohort study.Population based, electronic primary healthcare databases before 31 December 2015 from four European countries: Italy (n=1 542 672), Netherlands (n=2 225 925), Spain (n=5 488 397), and UK (n=12 695 046).120 795 a recorded diagnosis NAFLD NASH no other diseases, matched at time (index date) by age, sex, practice site, visit,...
Abstract Objective To quantify the background incidence rates of 15 prespecified adverse events special interest (AESIs) associated with covid-19 vaccines. Design Multinational network cohort study. Setting Electronic health records and claims data from eight countries: Australia, France, Germany, Japan, Netherlands, Spain, United Kingdom, States, mapped to a common model. Participants 126 661 070 people observed for at least 365 days before 1 January 2017, 2018, or 2019 13 databases. Main...
Abstract Objective To develop a conceptual prediction model framework containing standardized steps and describe the corresponding open-source software developed to consistently implement across computational environments observational healthcare databases enable sharing reproducibility. Methods Based on existing best practices we propose 5 step for: (1) transparently defining problem; (2) selecting suitable datasets; (3) constructing variables from data; (4) learning predictive model; (5)...
Hydroxychloroquine, a drug commonly used in the treatment of rheumatoid arthritis, has received much negative publicity for adverse events associated with its authorisation emergency use to treat patients COVID-19 pneumonia. We studied safety hydroxychloroquine, alone and combination azithromycin, determine risk routine care arthritis.
BackgroundThere are few data on the incidence of thrombosis among COVID-19 cases, with most research concentrated hospitalised patients. We aimed to estimate venous thromboembolism, arterial and death cases assess impact these events risks hospitalisation death.MethodsWe conducted a distributed network cohort study using primary care records from Netherlands, Italy, Spain, UK, outpatient specialist Germany. The Spanish database was linked hospital admissions. Participants were followed up...
Abstract Background There is currently no consensus on the impact of class imbalance methods performance clinical prediction models. We aimed to empirically investigate random oversampling and undersampling, two commonly used methods, internal external validation models developed using observational health data. Methods externally validated for various outcomes interest within a target population people with pharmaceutically treated depression across four large databases. three different...
Previous studies that determined the normal limits for paediatric ECG had their imperfections: ECGs were recorded at a relatively low sampling rate, measurements conducted manually, or presented only limited set of parameters. The aim this study was to establish an up-to-date and complete clinically relevant ECG.ECGs from 1912 healthy Dutch children (age 11 days 16 years) rate 1200 Hz. digitally stored analysed using well-validated computer program. all nine age groups. Clinically...
ABSTRACT Background Hydroxychloroquine has recently received Emergency Use Authorization by the FDA and is currently prescribed in combination with azithromycin for COVID-19 pneumonia. We studied safety of hydroxychloroquine, alone azithromycin. Methods New user cohort studies were conducted including 16 severe adverse events (SAEs). Rheumatoid arthritis patients aged 18+ initiating hydroxychloroquine compared to those sulfasalazine followed up over 30 days. Self-controlled case series...
Abstract Comorbid conditions appear to be common among individuals hospitalised with coronavirus disease 2019 (COVID-19) but estimates of prevalence vary and little is known about the prior medication use patients. Here, we describe characteristics adults COVID-19 compare them influenza We include 34,128 (US: 8362, South Korea: 7341, Spain: 18,425) patients, summarising between 4811 11,643 unique aggregate characteristics. patients have been majority male in US Spain, predominantly female...
Both sudden cardiac death (SCD) and chronic obstructive pulmonary disease (COPD) are common conditions in the elderly. Previous studies have identified an association between COPD cardiovascular disease, with SCD specific patient groups. Our aim was to investigate whether there is general population. The Rotterdam study a population-based cohort among 14 926 subjects aged 45 years older up 24 of follow-up. Analyses were performed (time dependent) Cox proportional hazard model adjusted for...
Purpose: Heart-rate variability (HRV) measured on standard 10-second electrocardiograms (ECGs) has been associated with increased risk of cardiac and all-cause mortality, but age- sex-dependent normal values have not established. Since heart rate strongly affects HRV, its effect should be taken into account. We determined a comprehensive set heart-rate corrected HRV derived from ECGs for both children adults, covering sexes. Methods: Five population studies in the Netherlands (Pediatric...
There is growing interest in using observational data to assess the safety, effectiveness, and cost effectiveness of medical technologies, but operational, technical, methodological challenges limit its more widespread use. Common models federated networks offer a potential solution many these problems. The open-source Observational Medical Outcomes Partnerships (OMOP) common model standardises structure, format, terminologies otherwise disparate datasets, enabling execution analytical code...
Abstract Objective Advances in standardization of observational healthcare data have enabled methodological breakthroughs, rapid global collaboration, and generation real-world evidence to improve patient outcomes. Standardizations structure, such as use common models, need be coupled with standardized approaches for quality assessment. To ensure confidence generated from the analysis data, one must first itself. Materials Methods We describe implementation check types across a framework...
Abstract Objective To investigate the use of repurposed and adjuvant drugs in patients admitted to hospital with covid-19 across three continents. Design Multinational network cohort study. Setting Hospital electronic health records from United States, Spain, China, nationwide claims data South Korea. Participants 303 264 January 2020 December 2020. Main outcome measures Prescriptions or dispensations any drug on 30 days after date admission for covid-19. Results Of included, 290 131 were...
Data resource basics Dutch primary care data for researchAccessibility of health is very good in The Netherlands.More than 99% the population has insurance 1 and almost all citizens are registered with a general practitioner (GP).People free to choose their GP.Enrolment at practice can be rejected because capacity limitations or too great distance between patient's address.The GP forms point acts as gatekeeper accessing secondary care.Over 12 months, around 78% least one contact GP. 2...
The Health-Analytics Data to Evidence Suite (HADES) is an open-source software collection developed by Observational Health Sciences and Informatics (OHDSI). It executes directly against healthcare data such as electronic health records administrative claims, that have been converted the Medical Outcomes Partnership (OMOP) Common Model. Using advanced analytics, HADES performs characterization, population-level causal effect estimation, patient-level prediction, potentially across a...