Integrating Healthcare Enterprise Research Articles

A National, Semantic-Driven, Three-Pillar Strategy to Enable Health Data Secondary Usage Interoperability for Research Within the Swiss Personalized Health Network: Methodological Study.

BackgroundInteroperability is a well-known challenge in medical informatics. Current trends in interoperability have moved from a data model technocentric approach to sustainable semantics, formal descriptive languages, and processes. Despite many initiatives and investments for decades, the interoperability challenge remains crucial. The need for data sharing for most purposes ranging from patient care to secondary uses, such as public health, research, and quality assessment, faces unmet problems.ObjectiveThis work was performed in the context of a large Swiss Federal initiative aiming at building a national infrastructure for reusing consented data acquired in the health care and research system to enable research in the field of personalized medicine in Switzerland. The initiative is the Swiss Personalized Health Network (SPHN). This initiative is providing funding to foster use and exchange of health-related data for research. As part of the initiative, a national strategy to enable a semantically interoperable clinical data landscape was developed and implemented.MethodsA deep analysis of various approaches to address interoperability was performed at the start, including large frameworks in health care, such as Health Level Seven (HL7) and Integrating Healthcare Enterprise (IHE), and in several domains, such as regulatory agencies (eg, Clinical Data Interchange Standards Consortium [CDISC]) and research communities (eg, Observational Medical Outcome Partnership [OMOP]), to identify bottlenecks and assess sustainability. Based on this research, a strategy composed of three pillars was designed. It has strong multidimensional semantics, descriptive formal language for exchanges, and as many data models as needed to comply with the needs of various communities.ResultsThis strategy has been implemented stepwise in Switzerland since the middle of 2019 and has been adopted by all university hospitals and high research organizations. The initiative is coordinated by a central organization, the SPHN Data Coordination Center of the SIB Swiss Institute of Bioinformatics. The semantics is mapped by domain experts on various existing standards, such as Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT), Logical Observation Identifiers Names and Codes (LOINC), and International Classification of Diseases (ICD). The resource description framework (RDF) is used for storing and transporting data, and to integrate information from different sources and standards. Data transformers based on SPARQL query language are implemented to convert RDF representations to the numerous data models required by the research community or bridge with other systems, such as electronic case report forms.ConclusionsThe SPHN strategy successfully implemented existing standards in a pragmatic and applicable way. It did not try to build any new standards but used existing ones in a nondogmatic way. It has now been funded for another 4 years, bringing the Swiss landscape into a new dimension to support research in the field of personalized medicine and large interoperable clinical data.

SU‐E‐T‐138: Automated Chart Review Module Including Cross‐Vendor Data Transfer Verification Developed for IHE‐RO Initiative

Purpose:To follow the Integrating Healthcare Enterprise ‐ Radiation Oncology (IHE‐RO) initiative of proper cross‐vendor technology integration, an automated chart checker (ACC) was developed. ACC compares extracted data from an approved patient plan in the Eclipse treatment planning system (TPS) against data existing in the Mosaiq treatment management system (TMS). ACC automatically analyzes these parameters using built‐in quality checklists to provide further aid in chart review.Methods:Eclipse TPS data are obtained using Eclipse scripting API (ESAPI) while Mosaiq TMS data are obtained from a radiotherapy‐treatment‐planning (RTP) file. Using this information, ACC identifies TPS‐TMS discrepancies in 18 primary beam parameters including MU, energy, jaw positions, gantry angle, table angle, accessories, and bolus for up to 31 beams. Next, approximately 40 items from traditional quality checklists are evaluated such as prescription consistency, DRR graticule placement, plan approval status, global max dose, and dose tracking coefficients. Parameters were artificially modified to determine if ACC would detect an error in data transfer and to test each component of quality checklists.Results:Using ESAPI scripting and RTP file‐processing, ACC was able to properly aggregate data from TPS and TMS for up to 31 beams. Errors were artificially introduced into each plan parameter, and ACC was able to successfully detect all of them within seconds. Next, ACC was able to successfully detect mistakes in the chart by identifying deviations with its quality checklists, within seconds.Conclusion:ACC effectively addresses the potential issue of faulty cross‐vendor data transfer, as described by IHE‐RO. In addition, ACC was also able to detect deviations from its built‐in quality checklists. ACC is already an invaluable tool for efficient and standardized chart review and will continue to improve as its incorporated checklists become more comprehensive.

The RSNA Image Sharing Network.

In the era of health information exchanges, there are trade-offs to consider when sharing a patient's medical record among all providers that a patient might choose. Exchange among in-network partners on the same electronic medical records (EMR) and other integrated information systems is trivial. The patient identifier is common, as are the relevant departmental systems, to all providers. Difficulties arise when patient records including images (and reports) must be shared among different networks and even with the patients themselves. The National Institutes of Health (NIH) challenged Radiological Society of North America (RSNA) to develop a transport method that could supersede the need for physical media (for patients or other providers), replace point-to-point private networks among providers, and enable image exchange on an ad hoc basis between arbitrary health networks without long legal delays. In concert with the evolving US health care paradigm, patient engagement was to be fundamental. With Integrating Healthcare Enterprise's (IHE's) help, the challenge has been met with an operational system.

Secure P2P Cross-Community Health Record Exchange in IHE Compatible Systems

This paper investigates a secure mechanism for Electronic Health Records (EHR) exchange over a Peer to Peer (P2P) agent based coordination framework. Our study is based on the SemHealthCoord framework, a platform for the exchange of EHR between autonomous health organisations that extends the existing interoperability standards as proposed by the Integrating Healthcare Enterprise (IHE). Every health organisation in SemHealthCoord represents a community within a P2P network. Communities use a set of autonomous agents and a set of distributed coordination rules to coordinate the agents in the search of specific health records. To enable secure interactions among communities, we propose the use of asymmetric keys and digital certificates. We specify the interaction protocols to provide integrity and authenticity between the communities, and, to illustrate the scalability of our approach, we evaluate the proposed solution in distributed settings by comparing the performance between secured and unsecured data exchange. The contribution of this work is that enables IHE based health communities to dynamically exchange EHR of patients with a secure P2P agent coordination framework.

A semantic publish-subscribe coordination framework for IHE based cross-community health record exchange

This paper presents a semantic agent coordination framework for the automatic exchange of Electronic Health Records (EHR). The framework enables health organizations that comply with the existing interoperability standards, as proposed by the Integrating Healthcare Enterprise (IHE), to dynamically connect in a P2P network. A set of autonomous agents and a set of distributed coordination rules are used to coordinate the agents in the search of specific health records. The framework models the interactions among the communities as a combination of the tuple centre agent communication model with the publish-subscribe paradigm and semantic web technologies. In order to illustrate the scalability of our approach, we evaluate the proposed solution in distributed settings. The contribution of this work is that it proposes the coordination mechanisms for IHE compliant communities to dynamically connect and share EHR of patients.

Ambient Intelligence for Monitoring and Research in Clinical Neurophysiology and Medicine

Ambient Intelligence (AmI) provides extended but unobtrusive sensing and computing devices and ubiquitous networking for human/environment interaction. It is a new paradigm in information technology compliant with the international Integrating Healthcare Enterprise board (IHE) and eHealth HL7 technological standards in the functional integration of biomedical domotics and informatics in hospital and home care. AmI allows real-time automatic recording of biological/medical information and environmental data. It is extensively applicable to patient monitoring, medicine and neuroscience research, which require large biomedical data sets; for example, in the study of spontaneous or condition-dependent variability or chronobiology. In this respect, AML is equivalent to a traditional laboratory for data collection and processing, with minimal dedicated equipment, staff, and costs; it benefits from the integration of artificial intelligence technology with traditional/innovative sensors to monitor clinical or functional parameters. A prototype AmI platform (MIMERICA*) has been implemented and is operated in a semi-intensive unit for the vegetative and minimally conscious states, to investigate the spontaneous or environment-related fluctuations of physiological parameters in these conditions.

Standardization Efforts of Digital Pathology in Europe

Background: EURO-TELEPATH is a European COST Action IC0604. It started in 2007 and will end in November 2011. Its main objectives are evaluating and validating the common technological framework and communication standards required to access, transmit, and manage digital medical records by pathologists and other medical specialties in a networked environment.Business Modelling: Working Group 1, “Business Modelling in Pathology,” has designed main pathology processes – Frozen Study, Formalin Fixed Specimen Study, Telepathology, Cytology, and Autopsy – using Business Process Modelling Notation (BPMN).Informatics Standards in Pathology: Working Group 2 has been dedicated to promoting the application of informatics standards in pathology, collaborating with Integrating Healthcare Enterprise (IHE), Digital Imaging and Communications in Medicine (DICOM), Health Level Seven (HL7), and other standardization bodies.Conclusion: Health terminology standardization research has become a topic of great interest. Future research work should focus on standardizing automatic image analysis and tissue microarrays imaging.

Standardization efforts of digital pathology in Europe.

Background: EURO-TELEPATH is a European COST Action IC0604. It started in 2007 and will end in November 2011. Its main objectives are evaluating and validating the common technological framework and communication standards required to access, transmit, and manage digital medical records by pathologists and other medical specialties in a networked environment. Business Modelling: Working Group 1, “Business Modelling in Pathology,” has designed main pathology processes – Frozen Study, Formalin Fixed Specimen Study, Telepathology, Cytology, and Autopsy – using Business Process Modelling Notation (BPMN). Informatics Standards in Pathology: Working Group 2 has been dedicated to promoting the application of informatics standards in pathology, collaborating with Integrating Healthcare Enterprise (IHE), Digital Imaging and Communications in Medicine (DICOM), Health Level Seven (HL7), and other standardization bodies. Conclusion: Health terminology standardization research has become a topic of great interest. Future research work should focus on standardizing automatic image analysis and tissue microarrays imaging.

History of PACS in Asia

First, history of PACS (picture archiving and communication system for medical use) in Japan is described in two parts: in part 1, the early stage of PACS development from 1984 to 2002, and in part 2 the matured stage from 2002 to 2010. PACS in Japan has been developed and installed by local manufacturers by their own technology and demand from domestic hospitals. Part 1 mainly focuses on quantitative growth and part 2 on qualitative change. In part 2, integration of PACS into RIS (radiology information system), HIS (hospital information system), EPR (electronic patient record), teleradiology and IHE (integrating healthcare enterprise) is reported. Interaction with other elements of technology such as moving picture network system and three dimensional display is also discussed. Present situation of main 4 large size hospitals is presented. Second, history of PACS in Korea is reported. Very acute climbing up of filmless PACS diffusion was observed from 1997 to 2000. The reasons for such evolution are described and discussed. Also changes of PACS installation and system integration with other systems such as HIS and role of them in radiological diagnoses in Korea since 2002 are described. Third, history in China is investigated by checking international academic journals in English and described as far as events are logically linked and consistently meaningful.

Collaborative Business Process Support in eHealth: Integrating IHE Profiles Through ebXML Business Process Specification Language

Integrating healthcare enterprise (IHE) specifies integration profiles describing selected real world use cases to facilitate the interoperability of healthcare information resources. While realizing a complex real-world scenario, IHE profiles are combined by grouping the related IHE actors. Grouping IHE actors implies that the associated business processes (IHE profiles) that the actors are involved must be combined, that is, the choreography of the resulting collaborative business process must be determined by deciding on the execution sequence of transactions coming from different profiles. There are many IHE profiles and each user or vendor may support a different set of IHE profiles that fits to its business need. However, determining the precedence of all the involved transactions manually for each possible combination of the profiles is a very tedious task. In this paper, we describe how to obtain the overall business process automatically when IHE actors are grouped. For this purpose, we represent the IHE profiles through a standard, machine-processable language, namely, Organization for the Advancement of Structured Information Standards (OASIS) ebusiness eXtensible Markup Language (ebXML) Business Process Specification (ebBP) Language. We define the precedence rules among the transactions of the IHE profiles, again, in a machine-processable way. Then, through a graphical tool, we allow users to select the actors to be grouped and automatically produce the overall business process in a machine-processable format.

Considerations for Setting Up an Order Entry System for Nuclear Medicine Tests

Integrating the Healthcare Enterprise-Japan (IHE-J) was established in Japan in 2001 and has been working to standardize health information and make it accessible on the basis of the fundamental Integrating Healthcare Enterprise (IHE) specifications. However, because specialized operations are used in nuclear medicine tests, online sharing of patient information and test order information from the order entry system as shown by the scheduled workflow (SWF) is difficult, making information inconsistent throughout the facility and uniform management of patient information impossible. Therefore, we examined the basic design (subsystem design) for order entry systems, which are considered an important aspect of information management for nuclear medicine tests and needs to be consistent with the system used throughout the rest of the facility. There are many items that are required by the subsystem when setting up an order entry system for nuclear medicine tests. Among these items, those that are the most important in the order entry system are constructed using exclusion settings, because of differences in the conditions for using radiopharmaceuticals and contrast agents and appointment frame settings for differences in the imaging method and test items. To establish uniform management of patient information for nuclear medicine tests throughout the facility, it is necessary to develop an order entry system with exclusion settings and appointment frames as standard features. Thereby, integration of health information with the Radiology Information System (RIS) or Picture Archiving Communication System (PACS) based on Digital Imaging Communications in Medicine (DICOM) standards and real-time health care assistance can be attained, achieving the IHE agenda of improving health care service and efficiently sharing information.