One Step Away from Technology but One Step Towards Domain Experts-MDRBridge: A Template-Based ISO 11179-Compliant Metadata Processing Pipeline.

BACKGROUND: Secondary use of routine medical data relies on a shared understanding of given information. This understanding is achieved through metadata and their interconnections, which can be stored in metadata repositories (MDRs). The necessity of an MDR is well understood, but the local work on metadata is a time-consuming and challenging process for domain experts. OBJECTIVE: To support the identification, collection, and provision of metadata in a predefined structured manner to foster consolidation. A particular focus is placed on user acceptance. METHODS: We propose a software pipeline MDRBridge as a practical intermediary for metadata capture and processing, based on MDRSheet, an ISO 11179-3 compliant template using popular spreadsheet software. It serves as a practical mediator for metadata acquisition and processing in a broader pipeline. Due to the different origins of the metadata, both manual entry and automatic extractions from application systems are supported. To enable the export of collected metadata into external MDRs, a mapping of ISO 11179 to Clinical Data Interchange Standards Consortium (CDISC) Operational Data Model (ODM) was developed. RESULTS: MDRSheet is embedded in the processing pipeline MDRBridge and delivers metadata in the CDISC ODM format for further use in MDRs. This approach is used to interactively unify core datasets, import existing standard datasets, and automatically extract all defined data elements from source systems. The involvement of clinical domain experts improved significantly due to minimal changes within their usual work routine. CONCLUSION: A high degree of acceptance was achieved by adapting the working methods of clinical domain experts. The designed process is capable of transforming all relevant data elements according to the ISO 11179-3 format. MDRSheet is used as an intermediate format to present the information at a glance and to allow editing or supplementing by domain experts.

QL4MDR: a GraphQL query language for ISO 11179-based metadata repositories.

BACKGROUND: Heterogeneous healthcare instance data can hardly be integrated without harmonizing its schema-level metadata. Many medical research projects and organizations use metadata repositories to edit, store and reuse data elements. However, existing metadata repositories differ regarding software implementation and have shortcomings when it comes to exchanging metadata. This work aims to define a uniform interface with a technical interlingua between the different MDR implementations in order to enable and facilitate the exchange of metadata, to query over distributed systems and to promote cooperation. To design a unified interface for multiple existing MDRs, a standardized data model must be agreed on. The ISO 11179 is an international standard for the representation of metadata, and since most MDR systems claim to be at least partially compliant, it is suitable for defining an interface thereupon. Therefore, each repository must be able to define which parts can be served and the interface must be able to handle highly linked data. GraphQL is a data access layer and defines query techniques designed to navigate easily through complex data structures. RESULTS: We propose QL4MDR, an ISO 11179-3 compatible GraphQL query language. The GraphQL schema for QL4MDR is derived from the ISO 11179 standard and defines objects, fields, queries and mutation types. Entry points within the schema define the path through the graph to enable search functionalities, but also the exchange is promoted by mutation types, which allow creating, updating and deleting of metadata. QL4MDR is the foundation for the uniform interface, which is implemented in a modern web-based interface prototype. CONCLUSIONS: We have introduced a uniform query interface for metadata repositories combining the ISO 11179 standard for metadata repositories and the GraphQL query language. A reference implementation based on the existing Samply.MDR was implemented. The interface facilitates access to metadata, enables better interaction with metadata as well as a basis for connecting existing repositories. We invite other ISO 11179-based metadata repositories to take this approach into account.

Design, implementation, and evaluation of a mobile application for patient empowerment and management of long-term follow-up after childhood cancer.

In Germany, about 1,800 new cases of childhood cancer are diagnosed every year. The chances of survival have increased significantly over the last 40 years due to the continuous improvement of treatment strategies. The number of childhood cancer survivors in Germany thus ranges around 30,000 nowadays. But their treatment with surgery, chemotherapy, and radiation has certain side-effects. In addition to the acute effects during the treatment phase, the disease- and treatment-related late effects can occur even decades after the end of therapy. These late effects draw attention as the survival rate constantly increases. Two-thirds of the former patients retain long-term consequences, nearly a fifth with a resulting diminished quality of life. Early detection of these late effects can help to reduce or even to prevent serious health damage. Therefore, the study group LESS supplies long-term follow-up recommendations for former patients. The project described in this paper was to design and implement a mobile application to increase the compliance for this aftercare program. This application provides information about the patient's individual aftercare plan and supports appointment management as well as a reminding functionality. A prototype for former osteosarcoma patients was tested and evaluated in two university hospitals. First results show the application's very high potential for patient empowerment.

Assessing applicability of ontological principles to different types of biomedical vocabularies.

OBJECTIVES: Recently, ontological principles have been applied to numerous biomedical vocabularies, with the intention to identify mistakes and poor modeling decisions. No doubt, such applications are useful and necessary for terminological systems like SNOMEDCT based on an axiomatic logical formalism. METHODS: In the following review, ontology is dealt with by focussing on particularly two aspects: the problem of ISA-overloading and the intrusion of epistemology-loaded terms in biomedical vocabularies. Both aspects are considered with respect to three types of biomedical vocabularies. RESULTS: Opposed to concept-oriented terminological systems, the purpose-specific organization of descriptors in thesauri and classes in statistical classifications on an extra aggregation level make it impossible to apply ontological principles. On the contrary, their intended purpose presupposes specific mechanisms that are in conflict with those principles. CONCLUSIONS: Interestingly, for thesauri and classifications there are rather similar initiatives linking the extra level of descriptors and classes on the one hand and an intermediate concept level on the other hand. Such an approach proved beneficial for maintaining and translating thesauri and classifications.

[Terminologies or classifications. What does the future hold?]. / Terminologien oder Klassifikationen: Was bringt die Zukunft?

Classifications like ICD-10 are always purpose-dependent reconstructions of a domain. The strong hierarchical, mutually exclusive divisions of classes are necessarily the result of a compromise, i.e. by using residual classes. Below the aggregation level of classes a machine manipulable level of concepts is needed to enable knowledge-based decision support or semantic integration of patient data. A set of concepts with their meanings and descriptions is provided by terminologies like LOINC. For large specialty areas, terminologies can be no longer realized by enumeration. Similar to human beings using language according to the "LEGO principle", i.e. decomposing in primitive building blocks (vocabulary) and rule-compliant composing to meaningful sentences (grammar), in almost the same manner complex concepts are dealt with in compositional terminologies like SNOMED CT by using logical approaches. Those terminologies enable a sophisticated machine-supported interpretation of exchanged patient data, e.g. for decision support modules in drug therapy.

Standardized terminological services enabling semantic interoperability between distributed and heterogeneous systems.

The interconnection of heterogeneous computer applications in medicine raises the issue of semantic interoperability, going beyond traditional approaches of terminological standardization in basically three aspects. First, the variety of medical vocabularies that currently coexist in different domains is a major barrier for the integration of autonomously developed applications. Fortunately, with the Unified Medical Language System (UMLS) there are machine-readable terminological sources that cover and integrate most of the existing medical vocabularies. Second, the exchanged data need to be processed by a machine for different purposes like patient data integration, access to literature and knowledge bases as well as clinical audit and research. Medical vocabularies provided as passive dictionaries are no longer sufficient. Software system developers should take advantage of terminological services for refining user queries, for mapping the user's terms to appropriate medical vocabularies etc. Third, the services should be accessible uniformly and transparently. In the CORBAmed initiative a proposal for a standardized interface for querying and accessing computerized medical terminology resources was created. Based on the mentioned principles the MUSTANG system (Medical UMLS based Terminology Server for Authoring, Navigating and Guiding the Retrieval to Heterogeneous Knowledge Sources) has been developed. It is implemented on a Windows NT platform using the ORACLE database management and development software. The terminological services are accessible via multiple interfaces. The MUSTANG-System and the experiences with using terminological services in practice are described. Opposed to other levels of standardization like syntactical message standards there is much more a hesitation in the use of standardized terminology.

Telemedicine and terminology: different needs of context information.

Traditionally, communication between healthcare providers, including the provision of physicians with information and knowledge, works quite well because there are implicitly common conventions and assumptions in the collaboration of all involved actors. The basic prerequisite of the communication process between humans is a mutual agreement on syntax and semantics of oral and written language, i.e., of the medical sublanguage. With telemedicine, i.e., the use of telecommunication and informatics in medicine, this prerequisite is no longer sufficient. First, various professionals from different clinical communities, characterized by specialty, nationality, school, etc., share the management of the patient's health. Second, electronically communicated information is more and more intended for processing by computer applications rather than for direct interpretation by human users. Third, the interconnection of distributed heterogeneous software systems in medicine raises the issue of semantic interoperability, especially the problem of data integration. A faithful communication in such a scenario must be based on explicit assumptions "behind" a message. Interpreting an usually highly context-dependent utterance demands for mechanisms on a pragmatic level in natural language processing. The need for additional processing and integration of the transferred data by the receiving system demands for standardization and mediation, taking into consideration contextual knowledge that cannot entirely be explained and processed with linguistic and terminological approaches. This paper describes different categories of contexts and also different needs of applications concerning "context awareness."

Concept-oriented standardization and statistics-oriented classification: continuing the classification versus nomenclature controversy.

Nowadays, most activities on controlled medical vocabularies focus on the provision of a sufficient atomic-level granularity for representing clinical data. Amongst others, clinical vocabularies should be concept oriented, compositional and should also reject "Not Elsewhere Classified". We strongly share the opinion that there is a need to deal with serious deficits of existing manually created vocabularies and with new demands for computer-based advanced processing and exchange of medical language data. However, we do not share the opinion that methodological requirements like observational and structural comparability needed for sound statistics should not be included in desiderata of controlled medical vocabularies. Statistical-oriented classifications are not developed for representing detailed clinical data but for providing purpose-dependent classes where cases of interest are assigned uniquely. Either statistical classifications are not included into the set of controlled medical vocabularies in the sense of Cimino, or his desiderata are misleading. We argue that statistical classifications should be linked to (formal) concept systems, but again this linkage does not change their different natures. With this article we continue the "classification versus nomenclature" controversy referring to Coté.

SAM: speech-aware applications in medicine to support structured data entry.

In the last two years, improvement in speech recognition technology has directed the medical community's interest to porting and using such innovations in clinical systems. The acceptance of speech recognition systems in clinical domains increases with recognition speed, large medical vocabulary, high accuracy, continuous speech recognition, and speaker independence. Although some commercial speech engines approach these requirements, the greatest benefit can be achieved in adapting a speech recognizer to a specific medical application. The goals of our work are first, to develop a speech-aware core component which is able to establish connections to speech recognition engines of different vendors. This is realized in SAM. Second, with applications based on SAM we want to support the physician in his/her routine clinical care activities. Within the STAMP project (STAndardized Multimedia report generator in Pathology), we extend SAM by combining a structured data entry approach with speech recognition technology. Another speech-aware application in the field of Diabetes care is connected to a terminology server. The server delivers a controlled vocabulary which can be used for speech recognition.

A formal model of diabetological terminology and its application for data entry.

This paper summarises the developmental activities for an electronic patient record system in diabetology based on GALEN technologies. It focusses on the modelling of primarily terminological medical knowledge of this subspecialty and describes its application for predictive data entry.

Taxonomic vocabularies in medicine: the intention of usage determines different established structures.

This paper deals with the reasons for distinguishing taxonomic vocabularies for standardizing terminology according to their different dedicated purposes. Different kinds of vocabularies are defined and then characterized using criteria like purposes, semiotic bases, principles for establishing hierarchical relations, mechanisms for guaranteeing reproducibility, and underlying representation formats. Furthermore, the kinds of taxonomic vocabularies worked out so far are named by preferred terms and assigned to proper places within the whole context of medical routine and research. Finally, it is argued that there must be a careful distinction between a conceptual level on one hand and a purpose-dependent non-conceptual level on the other. Unfortunately, both levels are crucially intertwined in existing vocabularies. Efforts on conceptually linking the vocabularies can help to share and re-use information evolving from different sources due to their common conceptual core. However, one must be aware of the effects resulting from special structural features on a non-conceptual level.