Interplay between Clinical Guidelines and Organizational Workflow Systems. Experience from the MobiGuide Project.

BACKGROUND: Implementing a decision-support system within a healthcare organization requires integration of clinical domain knowledge with resource constraints. Computer-interpretable guidelines (CIG) are excellent instruments for addressing clinical aspects while business process management (BPM) languages and Workflow (Wf) engines manage the logistic organizational constraints. OBJECTIVES: Our objective is the orchestration of all the relevant factors needed for a successful execution of patient's care pathways, especially when spanning the continuum of care, from acute to community or home care. METHODS: We considered three strategies for integrating CIGs with organizational workflows: extending the CIG or BPM languages and their engines, or creating an interplay between them. We used the interplay approach to implement a set of use cases arising from a CIG implementation in the domain of Atrial Fibrillation. To provide a more scalable and standards-based solution, we explored the use of Cross-Enterprise Document Workflow Integration Profile. RESULTS: We describe our proof-of-concept implementation of five use cases. We utilized the Personal Health Record of the MobiGuide project to implement a loosely-coupled approach between the Activiti BPM engine and the Picard CIG engine. Changes in the PHR were detected by polling. IHE profiles were used to develop workflow documents that orchestrate cross-enterprise execution of cardioversion. CONCLUSIONS: Interplay between CIG and BPM engines can support orchestration of care flows within organizational settings.

Clinical Bioinformatics: challenges and opportunities.

BACKGROUND: Network Tools and Applications in Biology (NETTAB) Workshops are a series of meetings focused on the most promising and innovative ICT tools and to their usefulness in Bioinformatics. The NETTAB 2011 workshop, held in Pavia, Italy, in October 2011 was aimed at presenting some of the most relevant methods, tools and infrastructures that are nowadays available for Clinical Bioinformatics (CBI), the research field that deals with clinical applications of bioinformatics. METHODS: In this editorial, the viewpoints and opinions of three world CBI leaders, who have been invited to participate in a panel discussion of the NETTAB workshop on the next challenges and future opportunities of this field, are reported. These include the development of data warehouses and ICT infrastructures for data sharing, the definition of standards for sharing phenotypic data and the implementation of novel tools to implement efficient search computing solutions. RESULTS: Some of the most important design features of a CBI-ICT infrastructure are presented, including data warehousing, modularity and flexibility, open-source development, semantic interoperability, integrated search and retrieval of -omics information. CONCLUSIONS: Clinical Bioinformatics goals are ambitious. Many factors, including the availability of high-throughput "-omics" technologies and equipment, the widespread availability of clinical data warehouses and the noteworthy increase in data storage and computational power of the most recent ICT systems, justify research and efforts in this domain, which promises to be a crucial leveraging factor for biomedical research.

Bringing research to the point of care: Hypergenes project study.

With advance of health information IT systems and increasing volumes of disparate biomedical information repositories, harvesting them for research purposes is becoming more difficult. This is partly due to the proprietary nature of the current systems, but also due to diverse requirements of different research paradigms. On the flip side, ever larger amounts of clinical and genomic data are currently accumulated in research projects. Tapping into these research silos would not only contribute to further research, but could help convey timely information to clinicians at the point of care. This paper presents RIMon - a portal-based infrastructure for information-intensive research cycle as used in the Hypergenes project, which aims at building a method to dissect complex genetic traits using essential hypertension as a disease model. RIMon allows users to: (a) collect data from points of care, (b) query and retrieve collected data for analysis, (c) query accumulated information and knowledge to construct disease models based on analysis results, and (d) to eventually make the research results readily available to the clinicians at the point of care. This translational cycle is demonstrated in the Hypergenes project along with a potential usage scenario.

Genomewide association study using a high-density single nucleotide polymorphism array and case-control design identifies a novel essential hypertension susceptibility locus in the promoter region of endothelial NO synthase.

Essential hypertension is a multifactorial disorder and is the main risk factor for renal and cardiovascular complications. The research on the genetics of hypertension has been frustrated by the small predictive value of the discovered genetic variants. The HYPERGENES Project investigated associations between genetic variants and essential hypertension pursuing a 2-stage study by recruiting cases and controls from extensively characterized cohorts recruited over many years in different European regions. The discovery phase consisted of 1865 cases and 1750 controls genotyped with 1M Illumina array. Best hits were followed up in a validation panel of 1385 cases and 1246 controls that were genotyped with a custom array of 14 055 markers. We identified a new hypertension susceptibility locus (rs3918226) in the promoter region of the endothelial NO synthase gene (odds ratio: 1.54 [95% CI: 1.37-1.73]; combined P=2.58 · 10(-13)). A meta-analysis, using other in silico/de novo genotyping data for a total of 21 714 subjects, resulted in an overall odds ratio of 1.34 (95% CI: 1.25-1.44; P=1.032 · 10(-14)). The quantitative analysis on a population-based sample revealed an effect size of 1.91 (95% CI: 0.16-3.66) for systolic and 1.40 (95% CI: 0.25-2.55) for diastolic blood pressure. We identified in silico a potential binding site for ETS transcription factors directly next to rs3918226, suggesting a potential modulation of endothelial NO synthase expression. Biological evidence links endothelial NO synthase with hypertension, because it is a critical mediator of cardiovascular homeostasis and blood pressure control via vascular tone regulation. This finding supports the hypothesis that there may be a causal genetic variation at this locus.

A standard based approach for biomedical knowledge representation.

The new generation of health information standards, where the syntax and semantics of the content is explicitly formalized, allows for interoperability in healthcare scenarios and analysis in clinical research settings. Studies involving clinical and genomic data include accumulating knowledge as relationships between genotypic and phenotypic information as well as associations within the genomic and clinical worlds. Some involve analysis results targeted at a specific disease; others are of a predictive nature specific to a patient and may be used by decision support applications. Representing knowledge is as important as representing data since data is more useful when coupled with relevant knowledge. Any further analysis and cross-research collaboration would benefit from persisting knowledge and data in a unified way. This paper describes a methodology used in Hypergenes, an EC FP7 project targeting Essential Hypertension, which captures data and knowledge using standards such as HL7 CDA and Clinical Genomics, aligned with the CEN EHR 13606 specification. We demonstrate the benefits of such an approach for clinical research as well as in healthcare oriented scenarios.

Independent health record banks for older people--the ultimate integration of dispersed and disparate medical records.

Older people have more health issues and use more healthcare services than young people. Consequently, many more records are created by various healthcare providers when they document the care they provided to the older person. The law in most countries requires the healthcare provider to persist the records for a certain amount of time. Thus, as time progresses, it becomes more challenging to integrate at the point of care the dispersed and disparate data sets created by the various providers and relate to the same older person. In addition to the data representation disparities, most often those data sets overlap and contradict and cannot be easily used by the clinician during the relatively short time dedicated to the care encounter/service. A possible solution to this challenge is to have lifelong electronic health records sustained by new players in the healthcare arena--Independent Health record Banks (IHRBs), which function as the sole record keepers of individual's health records. This article explores implications of the IHRB vision to the older people and argues that IHRBs offer the ultimate integration of health data for the older people to whom availability of complete medical history is crucial to getting better care.

Biomedical data integration - capturing similarities while preserving disparities.

One of the challenges of healthcare data processing, analysis and warehousing is the integration of data gathered from disparate and diverse data sources. Promoting the adoption of worldwide accepted information standards along with common terminologies and the use of technologies derived from semantic web representation, is a suitable path to achieve that. To that end, the HL7 V3 Reference Information Model (RIM) [1] has been used as the underlying information model coupled with the Web Ontology Language (OWL) [2] as the semantic data integration technology. In this paper we depict a biomedical data integration process and demonstrate how it was used for integrating various data sources, containing clinical, environmental and genomic data, within Hypergenes, a European Commission funded project exploring the Essential Hypertension [3] disease model.

Integrating genomics into clinical practice: standards and regulatory challenges.

Bridging between the worlds of healthcare and life sciences is crucial to realizing the personalized healthcare vision. Initiatives regarding legislation and regulation in this interdisciplinary field, along with significant advancement in the development of data standards for genotype-phenotype associations, give rise to a banking paradigm in the form of both biobanks and independent health record banks (IHRBs). These data banks are the information technology infrastructures that are expected to enable the implementation of personalized healthcare. As opposed to the regional strategy currently piloted in the US, IHRBs offer an alternative constellation to achieving a nationwide health information network and the bills introduced in the US Congress relating to these data banks have stimulated public discussion on how best to personalize the care process.

Standardization of microarray and pharmacogenomics data.

This chapter provides a bottom-up perspective on bioinformatics data standards, beginning with a historical perspective on biochemical nomenclature standards. Various file format standards were soon developed to convey increasingly complex and voluminous data that nomenclature alone could not effectively organize without additional structure and annotation. As areas of biochemistry and molecular biology have become more integral to the practice of modern medicine, broader data representation models have been created, from corepresentation of genomic and clinical data as a framework for drug research and discovery to the modeling of genotyping and pharmacogenomic therapy within the broader process of the delivery of health care.

Clinical genomics data standards for pharmacogenetics and pharmacogenomics.

This special report concerns a talk on data standards given at a workshop entitled 'An International Perspective on Pharmacogenetics: The Intersections between Innovation, Regulation and Health Delivery', which was held by the Organization for Economic Co-operation and Development (OECD) on October 17-19, 2005, in Rome, Italy. The worlds of healthcare and life sciences (HCLS) are extremely fragmented in terms of their underlying information technology, making it difficult to semantically exchange information between disparate entities. While we have reached the point where functional interoperability is ubiquitous, we are still far from achieving true semantic interoperability where a receiving system can use incoming data as though it was created internally. The critical enablers of semantic interoperability are information standards dedicated to HCLS data, spanning all the way from biological research data to clinical research and clinical trials, and finally to healthcare clinical data. The challenge lies in integrating various data standards based on predetermined goals, thereby improving the quality of care provided to patients.

The implications of electronic health record for personalized medicine.

The emerging concept of an electronic health record (EHR) targeted at a patient centric, cross-institutional and longitudinal information entity (possibly spanning the individuals lifetime) has great promise for personalized medicine. In fact, it is probably the only vehicle through which we may truly realize the personalization of medicine beyond population-based genetic profiles that are expected to become part of medication and treatment indications in the near future. The new EHR standards include mechanisms that integrate clinical data with genomic testing results obtained through applying research-type procedures, such as full DNA sequencing, to an individual patient. Although the most optimal process for the utilization of integrated clinical-genomic data in the EHR framework is still unclear, the new Health Level Seven (HL7) Clinical Genomics Draft Standard for Trial Use suggests using the 'encapsulate & bubble-up' approach, which includes two main phases: the encapsulation of raw genomic data and bubbling-up the most clinically significant portions of that data, while associating it with clinical phenotypes residing in the individual's EHR.

The implications of electronic health records for personalized medicine.

The emerging concept of an electronic health record (EHR) targeted at a patient centric, cross-institutional and longitudinal information entity (possibly spanning the individuals lifetime) has great promise for personalized medicine. In fact, it is probably the only vehicle through which we may truly realize the personalization of medicine beyond population-based genetic profiles that are expected to become part of medication and treatment indications in the near future. The new EHR standards include mechanisms that integrate clinical data with genomic testing results obtained through applying research-type procedures, such as full DNA sequencing, to an individual patient. Although the most optimal process for the utilization of integrated clinical-genomic data in the EHR framework is still unclear, the new Health Level Seven (HL7) Clinical Genomics Draft Standard for Trial Use suggests using the 'encapsulate & bubble-up' approach, which includes two main phases: the encapsulation of raw genomic data and bubbling-up the most clinically significant portions of that data, while associating it with clinical phenotypes residing in the individual's EHR.