Kirstine Rosenbeck Gøeg1, Rong Chen2, Anne Randorff Højen3, Pia Elberg3. 1. Aalborg University, Department of Health Science and Technology, Fredrik Bajers Vej 7D2, 9220 Aalborg, Denmark. Electronic address: kirse@hst.aau.dk. 2. Cambio Healthcare Systems, Ringvägen 100, 118 60 Stockholm, Sweden; Health Informatics Centre, Karolinska Institutet, Stockholm, Sweden. 3. Aalborg University, Department of Health Science and Technology, Fredrik Bajers Vej 7D2, 9220 Aalborg, Denmark.
Abstract
OBJECTIVES: Most electronic health record (EHR) systems are built on proprietary information models and terminology, which makes achieving semantic interoperability a challenge. Solving interoperability problems requires well-defined standards. In contrast, the need to support clinical work practice requires a local customization of EHR systems. Consequently, contrasting goals may be evident in EHR template design because customization means that local EHR organizations can define their own templates, whereas standardization implies consensus at some level. To explore the complexity of balancing these two goals, this study analyzes the differences and similarities between templates in use today. METHODS: A similarity analysis was developed on the basis of SNOMED CT. The analysis was performed on four physical examination templates from Denmark and Sweden. The semantic relationships in SNOMED CT were used to quantify similarities and differences. Moreover, the analysis used these identified similarities to investigate the common content of a physical examination template. RESULTS: The analysis showed that there were both similarities and differences in physical examination templates, and the size of the templates varied from 18 to 49 fields. In the SNOMED CT analysis, exact matches and terminology similarities were represented in all template pairs. The number of exact matches ranged from 7 to 24. Moreover, the number of unrelated fields differed a lot from 1/18 to 22/35. Cross-country comparisons tended to have more unrelated content than within-country comparisons. On the basis of identified similarities, it was possible to define the common content of a physical examination. Nevertheless, a complete view on the physical examination required the inclusion of both exact matches and terminology similarities. CONCLUSIONS: This study revealed that a core set of items representing the physical examination templates can be generated when the analysis takes into account not only exact matches but also terminology similarities. This core set of items could be a starting point for standardization and semantic interoperability. However, both unmatched terms and terminology matched terms pose a challenge for standardization. Future work will include using local templates as a point of departure in standardization to see if local requirements can be maintained in a standardized framework.
OBJECTIVES: Most electronic health record (EHR) systems are built on proprietary information models and terminology, which makes achieving semantic interoperability a challenge. Solving interoperability problems requires well-defined standards. In contrast, the need to support clinical work practice requires a local customization of EHR systems. Consequently, contrasting goals may be evident in EHR template design because customization means that local EHR organizations can define their own templates, whereas standardization implies consensus at some level. To explore the complexity of balancing these two goals, this study analyzes the differences and similarities between templates in use today. METHODS: A similarity analysis was developed on the basis of SNOMED CT. The analysis was performed on four physical examination templates from Denmark and Sweden. The semantic relationships in SNOMED CT were used to quantify similarities and differences. Moreover, the analysis used these identified similarities to investigate the common content of a physical examination template. RESULTS: The analysis showed that there were both similarities and differences in physical examination templates, and the size of the templates varied from 18 to 49 fields. In the SNOMED CT analysis, exact matches and terminology similarities were represented in all template pairs. The number of exact matches ranged from 7 to 24. Moreover, the number of unrelated fields differed a lot from 1/18 to 22/35. Cross-country comparisons tended to have more unrelated content than within-country comparisons. On the basis of identified similarities, it was possible to define the common content of a physical examination. Nevertheless, a complete view on the physical examination required the inclusion of both exact matches and terminology similarities. CONCLUSIONS: This study revealed that a core set of items representing the physical examination templates can be generated when the analysis takes into account not only exact matches but also terminology similarities. This core set of items could be a starting point for standardization and semantic interoperability. However, both unmatched terms and terminology matched terms pose a challenge for standardization. Future work will include using local templates as a point of departure in standardization to see if local requirements can be maintained in a standardized framework.
Authors: B de Bono; M Helvensteijn; N Kokash; I Martorelli; D Sarwar; S Islam; P Grenon; P Hunter Journal: Interface Focus Date: 2016-04-06 Impact factor: 3.906