Italy has 60 millions inhabitants, and a universal healthcare system. Every Italian inhabitant is entitled to choose a General Practitioner (GP), who dispenses primary care and provides access to secondary and inpatient care. Administrative databases collect information on healthcare of the whole population: hospital admissions, drug utilization, execution of diagnostic and rehabilitation procedures. However, diagnostic codes are only recorded when a patient is admitted to hospital for inpatient care, or when she is declared exempt from copayment of healthcare for some specific chronic disease. However, as older inhabitants are exempt anyway, exemtions are only informative for younger patients. Notably, no diagnosis is recorded when the patient sees her GP. This limitation of administrative databases makes it challenging to detect whether a subject has a chronic disease. The objective of this study was to identify optimal case-finding strategies for type 2 diabetes (T2DM), hypertension and ischaemic heart disease (IHD).
Identifying Chronic Conditions from Data Sources with Incomplete Diagnostic Information: The Case of Italian Administrative Databases
Dazzi Patrizio;Carlini Emanuele;Coppola Massimo;
2015
Abstract
Italy has 60 millions inhabitants, and a universal healthcare system. Every Italian inhabitant is entitled to choose a General Practitioner (GP), who dispenses primary care and provides access to secondary and inpatient care. Administrative databases collect information on healthcare of the whole population: hospital admissions, drug utilization, execution of diagnostic and rehabilitation procedures. However, diagnostic codes are only recorded when a patient is admitted to hospital for inpatient care, or when she is declared exempt from copayment of healthcare for some specific chronic disease. However, as older inhabitants are exempt anyway, exemtions are only informative for younger patients. Notably, no diagnosis is recorded when the patient sees her GP. This limitation of administrative databases makes it challenging to detect whether a subject has a chronic disease. The objective of this study was to identify optimal case-finding strategies for type 2 diabetes (T2DM), hypertension and ischaemic heart disease (IHD).I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
