Hereditary leiomyomatosis and renal cell cancer presenting as metastatic kidney cancer at 18 years of age: implications for surveillance

Hereditary leiomyomatosis and renal cell cancer (HLRCC) is an autosomal dominant syndrome characterized by skin piloleiomyomas, uterine leiomyomas and papillary type 2 renal cancer caused by germline mutations in the fumarate hydratase (FH) gene. Previously, we proposed renal imaging for FH mutation carriers starting at the age of 20 years. However, recently an 18-year-old woman from a Dutch family with HLRCC presented with metastatic renal cancer. We describe the patient and family data, evaluate current evidence on renal cancer risk and surveillance in HLRCC and consider the advantages and disadvantages of starting surveillance for renal cancer in childhood. We also discuss the targeted therapies administered to our patient

Biomedical informatics and translational medicine

Biomedical informatics involves a core set of methodologies that can provide a foundation for crossing the "translational barriers" associated with translational medicine. To this end, the fundamental aspects of biomedical informatics (e.g., bioinformatics, imaging informatics, clinical informatics, and public health informatics) may be essential in helping improve the ability to bring basic research findings to the bedside, evaluate the efficacy of interventions across communities, and enable the assessment of the eventual impact of translational medicine innovations on health policies. Here, a brief description is provided for a selection of key biomedical informatics topics (Decision Support, Natural Language Processing, Standards, Information Retrieval, and Electronic Health Records) and their relevance to translational medicine. Based on contributions and advancements in each of these topic areas, the article proposes that biomedical informatics practitioners ("biomedical informaticians") can be essential members of translational medicine teams

The Management of openEHR Archetypes for Semantically Interoperable Electronic Health Records

Walker et al. recently assessed the value of electronic health care information exchange and interoperability in the US and concluded that a compelling business case exists for its national implementation [1]. These findings are to be interpreted cautiously, and comparable studies are currently underway in other countries. In this context, the openEHR foundation (http://www.openEHR.org) has now published Release 1.0 of the openEHR specification as a common architecture specification for semantically interoperable Electronic Health Records (EHR). These specifications provide a sophisticated, uniform way to model clinical knowledge using archetypes. Archetypes are expressed using the Archetype Definition Language and are based on the openEHR reference model. For semantic interoperability between various Health Information Systems such as EHRs, systematic management of clinical knowledge is essential [2], [3]– no matter what the actual approach and methodology chosen to establish interoperable systems. Archetypes allow clinicians to efficiently agree on the content needed - and increasingly stakeholders in Australia and internationally choose archetypes as the means to define and standardize clinical knowledge. In this context, the aim of this paper is to analyse functional requirements for a web-based system that supports internationally collaborative creation and maintenance of archetypes as well as their systematic management (Domain Knowledge Governance, [4])

E-health records and future healthcare

This chapter gives an educational overview of: • Data collected, stored in health records and used for multiple purposes • Electronic health records and how these are likely to influence our future • Personal health records• Clinical systems and their relationship to national data collections • Potential future use of new technologie

openEHR Archetypes in Electronic Health Records: the Path to Semantic Interoperability?

A myriad of reasons ranging from physician concerns about workflow to broad environmental issues are still inhibiting the adoption of Electronic Health Record (EHR) systems [Ref. 1]. Some argue the most important reason why clinicians are reluctant to adopt clinical IT systems is a perceived lack of added value [Ref. 2] The UK Royal College of Nursing finds in a recent study that 93% of nurses believe that training for EHRs is very important, but over 50% received no training [Ref. 3]. Clinicians commonly feel that it is others who benefit from their keyboard labours – health system administrators, payors, and – hopefully – the patient [Ref. 2]. To really add value for the clinician it is still a necessity to develop best-of-breed systems (e.g. [Ref. 4]) commonly by circumventing existing systems with a strong administrative focus. Best-of-breed systems are at best awkwardly integrated, often maintained with minimum resources, and not interoperable with other systems. Further complicating this matter, health care is constantly changing in three ways (breadth, depth, complexity): new information, information in finer-grained detail, and new relationships are always being discovered or becoming relevant. Therefore, knowledge inherent in EHR systems will eventually become irrelevant or wrong. The openEHR archetype methodology (http://www.openEHR.org) is a possible solution to this dilemma as it claims to empower the clinician and ensure seamless integration and semantic interoperability. The aim of this paper is to shortly present the openEHR approach, analyse to what extend it empowers the clinician and what impact openEHR archetypes have on semantic interoperability