CODE-EHR best practice framework for the use of structured electronic healthcare records in clinical research.
Dipak KotechaFolkert W AsselbergsStephan AchenbachStefan D AnkerDan AtarColin BaigentAmitava BanerjeeBirgit BegerGunnar BrobertBarbara CasadeiCinzia CeccarelliMartin R CowieFilippo CreaMaureen CroninSpiros DenaxasAndrea DerixDonna FitzsimonsMartin FredrikssonChris P GaleGeorgios V GkoutosWim GoettschHarry HemingwayMartin IngvarAdrian JonasRobert KazmierskiSusanne LøgstrupR Thomas LumbersThomas F LüscherPaul McGreavyIleana L PiñaLothar RoessigCarl SteinbeisserMats SundgrenBenoît TylGhislaine van ThielKees van BochovePanos E VardasTiago VillanuevaMarilena VranaWim WeberFranz WeidingerStephan WindeckerAngela WoodDiederick E Grobbeenull nullPublished in: European heart journal (2022)
Big data is central to new developments in global clinical science aiming to improve the lives of patients. Technological advances have led to the routine use of structured electronic healthcare records with the potential to address key gaps in clinical evidence. The covid-19 pandemic has demonstrated the potential of big data and related analytics, but also important pitfalls. Verification, validation, and data privacy, as well as the social mandate to undertake research are key challenges. The European Society of Cardiology and the BigData@Heart consortium have brought together a range of international stakeholders, including patient representatives, clinicians, scientists, regulators, journal editors and industry. We propose the CODE-EHR Minimum Standards Framework as a means to improve the design of studies, enhance transparency and develop a roadmap towards more robust and effective utilisation of healthcare data for research purposes.
Keyphrases
- big data
- healthcare
- artificial intelligence
- machine learning
- electronic health record
- end stage renal disease
- ejection fraction
- newly diagnosed
- chronic kidney disease
- public health
- heart failure
- primary care
- mental health
- peritoneal dialysis
- human health
- health information
- risk assessment
- deep learning
- patient reported outcomes
- atrial fibrillation
- quality improvement
- climate change
- patient reported
- affordable care act