INTRODUCTION: This is a survey to identify what clinical coding systems are currently in use across the European Union, and the states seeking membership to it. We sought to identify what systems are currently used and to what extent they were subject to local adaptation. BACKGROUND: Clinical coding should facilitate identifying key medical events in a computerised medical record, and aggregating information across groups of records. The emerging new driver is as the enabler of the life-long computerised medical record. A prerequisite for this level of functionality is the transfer of information between different computer systems. This transfer can be facilitated either by working on the interoperability problems between disparate systems or by harmonising the underlying data. This paper examines the extent to which the latter has occurred across Europe. METHOD: Literature and Internet search. Requests for information via electronic mail to pan-European mailing lists of health informatics professionals. RESULTS: Coding systems are now a de facto part of health information systems across Europe. There are relatively few coding systems in existence across Europe. ICD9 and ICD 10, ICPC and Read were the most established. However the local adaptation of these classification systems either on a by country or by computer software manufacturer basis; significantly reduces the ability for the meaning coded with patients computer records to be easily transferred from one medical record system to another. CONCLUSIONS: There is no longer any debate as to whether a coding or classification system should be used. Convergence of different classifications systems should be encouraged. Countries and computer manufacturers within the EU should be encouraged to stop making local modifications to coding and classification systems, as this practice risks significantly slowing progress towards easy transfer of records between computer systems.
INTRODUCTION: This is a survey to identify what clinical coding systems are currently in use across the European Union, and the states seeking membership to it. We sought to identify what systems are currently used and to what extent they were subject to local adaptation. BACKGROUND: Clinical coding should facilitate identifying key medical events in a computerised medical record, and aggregating information across groups of records. The emerging new driver is as the enabler of the life-long computerised medical record. A prerequisite for this level of functionality is the transfer of information between different computer systems. This transfer can be facilitated either by working on the interoperability problems between disparate systems or by harmonising the underlying data. This paper examines the extent to which the latter has occurred across Europe. METHOD: Literature and Internet search. Requests for information via electronic mail to pan-European mailing lists of health informatics professionals. RESULTS: Coding systems are now a de facto part of health information systems across Europe. There are relatively few coding systems in existence across Europe. ICD9 and ICD 10, ICPC and Read were the most established. However the local adaptation of these classification systems either on a by country or by computer software manufacturer basis; significantly reduces the ability for the meaning coded with patients computer records to be easily transferred from one medical record system to another. CONCLUSIONS: There is no longer any debate as to whether a coding or classification system should be used. Convergence of different classifications systems should be encouraged. Countries and computer manufacturers within the EU should be encouraged to stop making local modifications to coding and classification systems, as this practice risks significantly slowing progress towards easy transfer of records between computer systems.
Authors: A Ruigómez; R Brauer; L A García Rodríguez; C Huerta; G Requena; M Gil; Francisco de Abajo; G Downey; A Bate; M Feudjo Tepie; M de Groot; R Schlienger; R Reynolds; O Klungel Journal: Eur J Clin Pharmacol Date: 2014-07-29 Impact factor: 2.953
Authors: Carolyn De Coster; Hude Quan; Alan Finlayson; Min Gao; Patricia Halfon; Karin H Humphries; Helen Johansen; Lisa M Lix; Jean-Christophe Luthi; Jin Ma; Patrick S Romano; Leslie Roos; Vijaya Sundararajan; Jack V Tu; Greg Webster; William A Ghali Journal: BMC Health Serv Res Date: 2006-06-15 Impact factor: 2.655
Authors: Benedikt F H Becker; Paul Avillach; Silvana Romio; Erik M van Mulligen; Daniel Weibel; Miriam C J M Sturkenboom; Jan A Kors Journal: Pharmacoepidemiol Drug Saf Date: 2017-06-28 Impact factor: 2.890