A plurality of terms and expressions has been established within the domain of healthcare and medicinal terminologies. For example, there are many different names for one and the same disease. While someone prefers the Latin expression for a disease, someone else may use the English expression for the same disease. Although these two persons would understand each other, a computer system needs to know that those expressions define the same disease. The same problem occurs in the field of medicinal products, such as drugs, apparatuses or instruments. For this and other reasons, standardizations of healthcare and medicinal terminologies have been established. For instance, the Systematized Nomenclature of Medicine (SNOMED) was designed as a comprehensive nomenclature of clinical medicine. This nomenclature has the function of accurately storing and retrieving records of clinical care. It provides a common language enabling a consistent manner of communicating and storing healthcare and medicinal terms.
A further standard which has been developed is the so called Health Level Seven (HL7), which provides a framework for the exchange, integration, sharing and retrieval of electronic health information. The HL7 standard allows different computer systems to communicate and exchange healthcare or medicinal information on a standardized platform. A particular conceptual standard of HL7 is the Reference Information Model (RIM) that expresses the data content needed in a specific clinical or administrative context. RIM also provides an explicit representation of the semantic and lexical connections that exist between the information carried in the fields of HL7 messages.
Although standardization of terminologies has been established in recent years, a plethora of terms is in use, where some of the terms have an identical meaning. In addition, different countries may have different standards. Thus, the plurality of different concepts and terminologies used in the healthcare and medicinal domain requires a system that accounts for these difficulties. Thus, there is a need for an application providing semantic interoperability between different standards.
Further to the above, huge volumes of healthcare information are locked in islands divided by disparate technologies, disparate representations, such as format or syntax, disparate semantics and levels of semantic richness. On the other hand, there is a need for the effective exchange of healthcare information. For example Electronic Health Record data needs to be exchanged to support effective treatment of mobile patients that see multiple providers, such as when suffering chronic co-morbidities, such as diabetes or heart disease. A further aspect is the order management of laboratories, radiology etc. and the referral processing that would profit from an effective exchange of healthcare information.
Moreover, current healthcare information systems do not provide for analytic aggregation, such as for disease registries, for treatment efficiency, signal detection, clinical protocol improvement and real-time feedback into evidence based medicine. A further aspect is the regulatory reporting, which suffers from the disadvantages of current systems.
For instance, a great deal of medical processes and information are currently still paper based. However, even when healthcare information is captured in an electronic form, it is often textual or at best in a very basic syntactic format or the same information is represented in many different ways. The work to extract information and transform in a meaningful way to make it useful for disease management, drug efficiency analysis, signal detection and real-time clinical decision making is huge.
As mentioned above, technology and syntactic interoperability challenges have been solved using integration engines and horizontal and vertical integration standards. Such industry standards include common domain models, such as HL7 RIM and BRIDG, and clinical terminologies, such as SNOMED, and have provided some improvement to the understanding.
However, there are many competing and overlapping standards and standards organizations. The standards themselves are typically consensus-based cooperative efforts resulting in the least common denominator and often leave a great deal of room for interpretation. Moreover, the architectural and technical quality of standards is often driven and influenced by people and organizations with their own commercial agendas or carriers at heart. Thus, in some cases the standard itself becomes the goal rather than the real improvement in healthcare.