Views of diagnosis distribution in primary care in 2.5 million encounters in Stockholm: a comparison between ICD-10 and SNOMED CT

Background Primary care (PC) in Sweden provides ambulatory and home health care outside hospitals. Within the County Council of Stockholm, coding of diagnoses in PC is mandatory and is done by general practitioners (GPs) using a Swedish primary care version of the International Statistical Classification of Diseases, version 10 (ICD-10). ICD-10 has amono-hierarchical structure. SNOMED CT is poly-hierarchical and belongs to a new generation of terminology systems with attributes (characteristics) that connect concepts in SNOMED CT and build relationships. Mapping terminologies and classifications has been pointed out as a way to attain additional advantages in describing and documenting healthcare data. A poly-hierarchical system supports the representation and aggregation of healthcare data on the basis of specific medical aspects and various levels of clinical detail. Objective To describe and compare diagnoses and health problems in KSH97-P/ICD-10 and SNOMED CT using primary care diagnostic data, and to explore and exemplify complementary aggregations of diagnoses and health problems generated from a mapping to SNOMED CT. Methods We used diagnostic data collected throughout 2006 and coded in electronic patient records (EPRs), and a mapping from KSH97-P/ ICD-10 to SNOMED CT, to aggregate the diagnostic data with SNOMED CT defining hierarchical relationship Is a and selected attribute relationships. Results The chapter level comparison between ICD-10 and SNOMED CT showed minor differences except for infectious and digestive system disorders. The relationships chosen aggregated the diagnostic data to 2861 concepts, showing a multidimensional view on different medical and specific levels and also including clinically relevant characteristics through attribute relationships. Conclusions SNOMED CT provides a different view of diagnoses and health problems on a chapter level, and adds significant new views of the clinical data with aggregations generated fromSNOMED CT Is a and attribute relationships. A broader use of SNOMED CT is therefore of importance when describing and developing primary care