Jesus Bisbal

Legacy information systems: issues and directions

A legacy information system represents a massive, long-term business investment. Unfortunately, such systems are often brittle, slow and non-extensible. Capturing legacy system data in a way that can support organizations into the future is an important but relatively new research area. The authors offer an overview of existing research and present two promising methodologies for legacy information system migration.

The Butterfly Methodology: a gateway-free approach for migrating legacy information systems

The problems posed by mission-critical legacy systems-e.g., brittleness, inflexibility, isolation, non-extensibility, lack of openness-are well known, but practical solutions have been slow to emerge. Generally, organisations attempt to keep their legacy systems operational, while developing mechanisms which allow the legacy systems to interoperate with new, modern systems which provide additional functionality. The most mature approach employs gateways to provide this interoperability. However, gateways introduce considerable complexity in their attempt to maintain consistency between the legacy and target systems. This paper presents an innovative gateway-free approach to migrating legacy information systems in a mission-critical environment: the Butterfly Methodology. The fundamental premise of this methodology is to question the need for the parallel operation of the legacy and target systems during migration.

An Analysis Framework for Electronic Health Record Systems

BACKGROUND The timely provision of complete and up-to-date patient data to clinicians has for decades been one of the most pressing objectives to be fulfilled by information technology in the healthcare domain. The so-called electronic health record (EHR), which provides a unified view of all relevant clinical data, has received much attention in this context from both research and industry. This situation has given rise to a large number of research projects and commercial products that aim to address this challenge. Different projects and initiatives have attempted to address this challenge from various points of view, which are not easily comparable. OBJECTIVES This paper aims to clarify the challenges, concepts, and approaches involved, which is essential in order to consistently compare existing solutions and objectively assess progress in the field. METHODS This is achieved by two different means. Firstly, the paper will identify the most significant issues that differentiate the points of view and intended scope of existing approaches. As a result, a framework for analysis of EHR systems will be produced. Secondly, the most representative EHR-related projects and initiatives will be described and compared within the context of this framework. RESULTS The main result of the present paper is an analysis framework for EHR systems. This is intended as an initial step towards an attempt to structure research on this field, clearly lacking sound principles to evaluate and compare results, and ultimately focusing its efforts and being able to objectively evaluate scientific progress. CONCLUSIONS Evaluation and comparison of results in medical informatics, and specifically EHR systems, must address technical and non-technical aspects. It is challenging to condensate in a single framework all potential views of such a field, and any chosen approach is bound to have its limitations. That being said, any well structured comparison approach, such as the framework presented here, is better than no comparison framework at all, as has been the current situation to date. This paper has presented the first attempt known to the authors to define such a framework.

An overview of legacy information system migration

Legacy information systems typically form the backbone of the information flow within an organisation and are the main vehicle for consolidating information about the business. These systems also pose considerable problems: brittleness, inflexibility, isolation, nonextensibility, lack of openness etc., the so called legacy system problem which opens up a new research topic, legacy system migration. This paper provides a brief review of the main issues involved in legacy information systems migration.

Resource-based approach to feature interaction in adaptive software

This paper proposes the RAFTING approach (Resource-based Approach to FeaTure InteractioN) to address the feature interaction problem in the context of dynamically adapted software. RAFTING focuses on the resources used by features, rather than the features themselves. Therefore, for this papers purposes, resource contention will be considered the main cause for feature interaction. We illustrate how a resource-based approach simplifies the detection of feature interactions, particularly when a limited amount of information is known about the individual components being dynamically added to the system.

Prediction of cerebral aneurysm rupture using hemodynamic, morphologic and clinical features: a data mining approach

Cerebral aneurysms pose a major clinical threat and the current practice upon diagnosis is a complex, lengthy, and costly, multicriteria analysis, which to date is not fully understood. This paper reports the development of several classifiers predicting whether a given clinical case is likely to rupture taking into account available information of the patient and characteristics of the aneurysm. The dataset used included 157 cases, with 294 features each. The broad range of features include basic demographics and clinical information, morphological characteristics computed from the patients medical images, as well as results gained from personalised blood flow simulations. In this premiere attempt the wealth of aneurysm-related information gained from multiple heterogeneous sources and complex simulation processes is used to systematically apply different data-mining algorithms and assess their predictive accuracy in this domain. The promising results show up to 95% classification accuracy. Moreover, the analysis also enables to confirm or reject risk factors commonly accepted or suspected in the domain.

Clinical coverage of an archetype repository over SNOMED-CT

Clinical archetypes provide a means for health professionals to design what should be communicated as part of an Electronic Health Record (EHR). An ever-growing number of archetype definitions follow this health information modelling approach, and this international archetype resource will eventually cover a large number of clinical concepts. On the other hand, clinical terminology systems that can be referenced by archetypes also have a wide coverage over many types of health-care information. No existing work measures the clinical content coverage of archetypes using terminology systems as a metric. Archetype authors require guidance to identify under-covered clinical areas that may need to be the focus of further modelling effort according to this paradigm. This paper develops a first map of SNOMED-CT concepts covered by archetypes in a repository by creating a so-called terminological Shadow. This is achieved by mapping appropriate SNOMED-CT concepts from all nodes that contain archetype terms, finding the top two category levels of the mapped concepts in the SNOMED-CT hierarchy, and calculating the coverage of each category. A quantitative study of the results compares the coverage of different categories to identify relatively under-covered as well as well-covered areas. The results show that the coverage of the well-known National Health Service (NHS) Connecting for Health (CfH) archetype repository on all categories of SNOMED-CT is not equally balanced. Categories worth investigating emerged at different points on the coverage spectrum, including well-covered categories such as Attributes, Qualifier value, under-covered categories such as Microorganism, Kingdom animalia, and categories that are not covered at all such as Cardiovascular drug (product).

Database sampling with functional dependencies

Abstract During the development of information systems, there is a need to prototype the database that the applications will use when in operation. A prototype database can be built by sampling data from an existing database. Including relevant semantic information when extracting a sample from a database is considered invaluable to support the development of data-intensive applications. Functional dependencies are an example of semantic information that could be considered when sampling a database. This paper investigates how a database relation can be sampled so that the resulting sample satisfies precisely a given set of functional dependencies (and its logical consequences), i.e. is an Armstrong relation.

Towards collaborative data management in the VPH-Share project

The goal of the Virtual Physiological Human Initiative is to provide a systematic framework for understanding physiological processes in the human body in terms of anatomical structure and biophysical mechanisms across multiple length and time scales. In the long term it will transform the delivery of European healthcare into a more personalised, predictive, and integrative process, with significant impact on healthcare and on disease prevention. This paper outlines how the recently funded project VPH-Share contributes to this vision. The project is motivated by the needs of the whole VPH community to harness ICT technology to improve health services for the individual. VPH-Share will provide the organisational fabric (the infostructure), realised as a series of services, offered in an integrated framework, to expose and to manage data, information and tools, to enable the composition and operation of new VPH workflows and to facilitate collaborations between the members of the VPH community.

Building Consistent Sample Databases to Support Information System Evolution and Migration

Prototype databases are needed in any information system development process to support data-intensive applications development. It is common practice to populate these databases using synthetic data. This data usually bears little relation to the applications domain and considers only a very reduced subset of the integrity constraints the database will hold during operation.