Interoperability in Healthcare Information Systems
Miguel‐Ángel Sicilia, Pablo Serrano Balazote · Advances in healthcare information systems and administration book series · 2013
Semantic interoperability facilitates Health Care and Life Sciences (HCLS) systems in connecting stakeholders (e.g., patient, physician, pharmacy) at various levels as well as ensure seamless use of healthcare resources (e.g., data, schema, applications).Their scope ranges from local (within, e.g., hospitals or hospital networks) to regional, national and cross-border.The use of semantics in delivering interoperable solution for HCLS systems is weakened by fact that an Ontology Based Information System (OBIS) has restrictions in modeling, aggregating, and interpreting global knowledge (e.g., terminologies for disease, drug, clinical event) in conjunction with local information (e.g., policy, profiles).This chapter presents an example-scenario that shows such limitations and recognizes that enabling two key features, namely the type and scope of knowledge, within a knowledge base could enhance the overall effectiveness of an OBIS.We provide the idea of separating knowledge bases in types (e.g., general or constraint knowledge) with scope (e.g., global or local) of applicability.Then, we propose two concrete solutions on this general notion.Finally, we describe open research issues that may be of interest to knowledge system developers and broader research community.This chapter discusses how to formally represent information in use in electronic patient records (EPR) and related knowledge bases, where the data are distributed, heterogeneous and multi-contextual.We especially explore how existing formalisms are able to deal with the difficult issues provoked by heterogeneity in a globalized information system.To do this, we present in a plausible use case scenario where two hospitals in different countries are involved, as well as labs and clinics.This serves to identify essential issues arising in such environment.We then show that Semantic Web technologies can help solving these issues and consolidate interoperability.Yet, these technologies fail at several levels in this multi-scoped situation.Therefore, we investigate formal approaches that have been proposed on top of Semantic Web technologies to deal with these crucial aspects of world-wide knowledge base systems.As a result of this investigation, we classify the approaches according to five essential features that are meaningful to dealing with our example scenario.We conclude that no approach fully solve the issues but some can be combined to improve the overall formalism.Especially, we notice that those issues eventually amount to delimiting the scope and type of a knowledge base or its subparts.Subsequently, we detail how to define an extension of existing work to treat more appropriately the identified features.Finally, we discuss the remaining foundational problems that are still not addressed by the presented approaches but are critical to the interoperability of these systems.This way we hope to offer a roadmap and directions for future research in semantic-enabled HCLS system at Web-scale.We start the chapter with background information about semantics in HCLS systems (Section 2).We then describe our use-case scenario (Section 3).We show how to apply various formalisms to this scenario in four sections overviewing the state of the art: first, we present two general theories of reasoning with context (Section 4); second, we detail some instanciation of one of the model of context (Section 5); third, we present more concrete formalisms for the description of context on the Semantic Web (Section 6); fourth, we provide other formal approaches built on top of semantic technologies that deals with the identified problems of our scenario (Section 7).After this extensive state of the art, we provide a summary and analysis of the studied approaches (Section 8).Then, we present our proposal for combining existing approaches to better deal with scopes and types of knowledge (Section 9).Finally, we discuss the remaining open research issues that we deem crucial to enable interoperability (Section 10). Semantics for HCLSAn overwhelming amount of HCLS knowledge is represented in natural language, information models, clinical repositories (databases), ontologies for terminologies, vocabularies, etc.Additionally, the involvement of various stakeholders, such as hospitals, healthcare standards, pharmacy, patients, multiplies the integration complexity of this domain.Intelligent processing, logical aggregation of information, synthesis and analysis, and the development of knowledge systems that can serve purposeful ends are needed.HCLS has been one of the primary field of application for knowledge representation and reasoning systems.In the past researchers have tried to formalize and integrate the knowledge bases in HCLS systems and many of the successful systems in earlier times were centralized and limited to sub domain or particular application of a HCLS domain (Szolovits, 1982;Kashyap & Sheth, 1996).Current HCLS systems are much more open and available to global society where stakeholders mobility and seamless use of the overall system is of prime concern.As discuss above, ontology based information systems (OBISs) offer greater flexibility and automation for the management and integration of very complex intertwined HCLS data and schemas.HCLS specialists increasingly argue in favor of Semantic Web technologies for representing medical and clinical knowledge (Rector, Qamar, & Marley, 2006) in a well formalized way.However, current Semantic Web technologies alone are still too limited to provide a unified framework for all the varieties of applications and sub-domains of life sciences.Also, they show their limits when integrating and exchanging data between different systems.The W3C HCLS Interest Group 1 and various research projects have taken initiatives for the ontological representation of healthcare information models and their integration with HCLS terminologies and vocabularies (Bicer, Laleci, Dogac, & Kabak, 2005;Rector et al., 2006;Sahay, Akhtar, & Fox, 2008;Fox, Sahay, & Hauswirth, 2008).This integration is crucial to effectively achieve a unified-view of electronic health records (EHR).However, this approach is still facing core integration issues such as ontological heterogeneity, ambiguous separation between global and local healthcare knowledge (Jahnke, Bychkov, Dahlem, & Kawasme, 2005).