Coming to terms with datasets for diabetes care.
The development of datasets for the recording, transfer, monitoring and improvement of diabetes care has to take into account the perspectives of different stakeholders. Success of a dataset is dependent on shared ownership, professional support, clear objectives and development by consensus. Different types of concepts are discernible that share similar features, including the classes of disease, qualitative observations, quantitative observations, procedures and record specific concepts. The identification of these types assists the development of a dataset by clarifying the characteristics that need to be defined. The specification of the component data items ideally requires adherence to established terminology principles where each concept is uniquely labelled by an unambiguous term. These identified concepts should also be exclusive, stable over time, defined, reusable and relevant. Attention should also be given to the scope of each concept and consistency in handling additional detail. The dataset overall should adhere to principles of time representation and be manageable, implementable, regulated, extendible, piloted and ethical. Consideration of these principles should improve the likelihood that a dataset will be widely adopted, integrated and be further developed in existing patterns care.
Brown
P J
PJ
NHS Centre for Coding and Classification, Loughborough, Leicestershire, UK. Phil.Brown@nhsccc.exec.nhs.uk
D003195:Computer Communication Networks; D003625:Data Collection / Q000592:standards*; D003628:Database Management Systems; D003920:Diabetes Mellitus / Q000628:therapy*; D006801:Humans; D009626:Terminology as Topic