ArticleClinical epidemiology2015
A common data model to assess cardiovascular hospitalization and mortality in atrial fibrillation patients using administrative claims and medical records.
Article in Clinical epidemiology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.
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Who cites it
9 citing papers in PubMed, 1 synthesis or guideline pooled it, 15 citations in OpenAlex.
- Bidirectional association between COPD and AF: a systematic review and meta-analysis.Frontiers in cardiovascular medicine · 2026Pooled it
- Assessment of Inter-Institutional Post-Operative Hypoparathyroidism Status Using a Common Data Model.Journal of clinical medicine · 2021Article
- The in-ear region as a novel anatomical site for ECG signal detection: validation study on healthy volunteers.Journal of interventional cardiac electrophysiology : an international journal of arrhythmias and pacing · 2021Article
- Article
- Intensified ambulatory cardiology care: effects on mortality and hospitalisation-a comparative observational study.Scientific reports · 2020Observational
- Incidence of lower extremity amputations among patients with type 1 and type 2 diabetes in the United States from 2010 to 2014.Diabetes, obesity & metabolism · 2020Article
- Effect of Age on the Initiation of Biologic Agent Therapy in Patients With Inflammatory Bowel Disease: Korean Common Data Model Cohort Study.JMIR medical informatics · 2020Article
- Emergency Department, Hospital Inpatient, and Mortality Burden of Atrial Fibrillation in the United States, 2006 to 2014.The American journal of cardiology · 2017Article
- Multimorbidity and the risk of hospitalization and death in atrial fibrillation: A population-based study.American heart journal · 2017Article
Corrections and comments
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Authors and funding
8 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeAtrial fibrillation/flutter (AF) is frequently associated with cardiovascular comorbidities. Observational health care databases are commonly used for research purposes in studies of quality of care, health economics, outcomes research, drug safety, and epidemiology. This retrospective cohort study applied a common data model to administrative claims data (Truven Health Analytics MarketScan(®) claims databases [MS-Claims]) and electronic medical records data (Geisinger Health System's MedMining electronic medical record database [MG-EMR]) to examine the risk of cardiovascular hospitalization and all-cause mortality in relation to clinical risk factors in recent-onset AF and to assess the consistency of analyses for each data source.
methodsCohorts of patients with newly diagnosed AF (n=105,262 [MS-Claims] and n=3,919 [MG-EMR]) and demographically similar patients without AF (n=105,262 [MS-Claims] and n=3,872 [MG-EMR]) were followed from the qualifying AF diagnosis until cardiovascular hospitalization, death, database disenrollment, or study completion. A common data model standardized the data in structure, format, content, and nomenclature to allow for systematic assessment and comparison of outcomes from two disparate data sets.
resultsIn both databases, AF patients had greater overall baseline comorbidity and higher incidence rates of cardiovascular hospitalization (threefold higher) and all-cause mortality (46% higher) than non-AF patients. For AF patients, incidence rates of cardiovascular hospitalization and all-cause mortality were increased by the concomitant presence of coronary disease, chronic obstructive pulmonary disease, and stroke at baseline. Overall, the pattern of cardiovascular hospitalization in the MS-Claims database was similar to that in the MG-EMR database. Compared with the MS-Claims database, the use of cardiovascular medications and the capture of certain comorbidities among AF patients appeared to be higher in the MG-EMR data set.
conclusionSimilar standardized analyses across EMR and Claims databases were consistent in the association of AF with acute morbidity and an increased risk of all-cause mortality. Areas of inconsistency were due to differences in underlying population demographics and cardiovascular risks and completeness of certain data fields.
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