Toward a National Information Model for Medication Orders in Sweden

Abstract

Background Semantic interoperability among health information systems (HISs), in particular electronic health records (EHRs), is crucial for informed healthcare decisions and access to vital health data by the patient. However, inconsistent medication information and limited health data exchange contribute to medication errors worldwide. Although Sweden offers various solutions for health information exchange, there is a limitation in the exchange of medication orders and a lack of understanding the structure of medication orders among EHRs, highlighting the need for further exploration of the structure of medication orders. Objectives This study aims to develop a common information model of medication orders for EHRs to be used in the Swedish context. Methods An explorative qualitative design study was conducted. Documents and reference models of how medication orders are structured were collected, and semi-structured interviews were conducted with five purposefully selected participants with insight into how medication orders are structured in EHRs in Sweden. Data were analyzed using information needs analysis, information structure analysis, and code systems, classifications, and terminology analysis. Results The following information areas were identified for a medication order: medication, medication indication, way of administration, medication order details, and dosage. These information areas were conceptualized into a Unified Modeling Language Class Diagram information model with defined classes, attributes, and data types. The resulting information model provides a representation of how medication orders are depicted in EHRs in Sweden and is aligned with existing national information models such as the National Medication List, while still providing additional information related to medication order details. Conclusion The developed information model could potentially provide a national standardized model for medication orders, contributing to enhanced semantic interoperability and improving data exchange across various HISs. This could enhance data consistency, reducing the risk of medication errors and thereby improving patient safety.