Personalized Medicine: the Future of Health Care

BACKGROUND: Most medical treatments have been designed for the “average patients”. As a result of this “one-size-fits-all-approach”, treatments can be very successful for some patients but not for others. The issue is shifting by the new innovation approach in diseases treatment and prevention, precision medicine, which takes into account individual differences in people\u27s genes, environments, and lifestyles. This review was aimed to describe a new approach of healthcare performance strategy based on individual genetic variants.CONTENT: Researchers have discovered hundreds of genes that harbor variations contributing to human illness, identified genetic variability in patients\u27 responses to different of treatments, and from there begun to target the genes as molecular causes of diseases. In addition, scientists are developing and using diagnostic tests based on genetics or other molecular mechanisms to better predict patients\u27 responses to targeted therapy.SUMMARY: Personalized medicine seeks to use advances in knowledge about genetic factors and biological mechanisms of disease coupled with unique considerations of an individual\u27s patient care needs to make health care more safe and effective. As a result of these contributions to improvement in the quality of care, personalized medicine represents a key strategy of healthcare reform

Incorporation of Personal Single Nucleotide Polymorphism (SNP) Data into a National Level Electronic Health Record for Disease Risk Assessment, Part 1: An Overview of Requirements

Background: Personalized medicine approaches provide opportunities for predictive and preventive medicine. Using genomic, clinical, environmental, and behavioral data, tracking and management of individual wellness is possible. A prolific way to carry this personalized approach into routine practices can be accomplished by integrating clinical interpretations of genomic variations into electronic medical records (EMRs)/electronic health records (EHRs). Today, various central EHR infrastructures have been constituted in many countries of the world including Turkey. Objective: The objective of this study was to concentrate on incorporating the personal single nucleotide polymorphism (SNP) data into the National Health Information System of Turkey (NHIS-T) for disease risk assessment, and evaluate the performance of various predictive models for prostate cancer cases. We present our work as a miniseries containing three parts: (1) an overview of requirements, (2) the incorporation of SNP into the NHIS-T, and (3) an evaluation of SNP incorporated NHIS-T for prostate cancer. Methods: For the first article of this miniseries, the scientific literature is reviewed and the requirements of SNP data integration into EMRs/EHRs are extracted and presented. Results: In the literature, basic requirements of genomic-enabled EMRs/EHRs are listed as incorporating genotype data and its clinical interpretation into EMRs/EHRs, developing accurate and accessible clinicogenomic interpretation resources (knowledge bases), interpreting and reinterpreting of variant data, and immersing of clinicogenomic information into the medical decision processes. In this section, we have analyzed these requirements under the subtitles of terminology standards, interoperability standards, clinicogenomic knowledge bases, defining clinical significance, and clinicogenomic decision support. Conclusions: In order to integrate structured genotype and phenotype data into any system, there is a need to determine data components, terminology standards, and identifiers of clinicogenomic information. Also, we need to determine interoperability standards to share information between different information systems of stakeholders, and develop decision support capability to interpret genomic variations based on the knowledge bases via different assessment approaches.Publisher's Versio

A standards-based ICT framework to enable a service-oriented approach to clinical decision support

This research provides evidence that standards based Clinical Decision Support (CDS) at the point of care is an essential ingredient of electronic healthcare service delivery. A Service Oriented Architecture (SOA) based solution is explored, that serves as a task management system to coordinate complex distributed and disparate IT systems, processes and resources (human and computer) to provide standards based CDS. This research offers a solution to the challenges in implementing computerised CDS such as integration with heterogeneous legacy systems. Reuse of components and services to reduce costs and save time. The benefits of a sharable CDS service that can be reused by different healthcare practitioners to provide collaborative patient care is demonstrated. This solution provides orchestration among different services by extracting data from sources like patient databases, clinical knowledge bases and evidence-based clinical guidelines (CGs) in order to facilitate multiple CDS requests coming from different healthcare settings. This architecture aims to aid users at different levels of Healthcare Delivery Organizations (HCOs) to maintain a CDS repository, along with monitoring and managing services, thus enabling transparency. The research employs the Design Science research methodology (DSRM) combined with The Open Group Architecture Framework (TOGAF), an open source group initiative for Enterprise Architecture Framework (EAF). DSRM’s iterative capability addresses the rapidly evolving nature of workflows in healthcare. This SOA based solution uses standards-based open source technologies and platforms, the latest healthcare standards by HL7 and OMG, Decision Support Service (DSS) and Retrieve, Update Locate Service (RLUS) standard. Combining business process management (BPM) technologies, business rules with SOA ensures the HCO’s capability to manage its processes. This architectural solution is evaluated by successfully implementing evidence based CGs at the point of care in areas such as; a) Diagnostics (Chronic Obstructive Disease), b) Urgent Referral (Lung Cancer), c) Genome testing and integration with CDS in screening (Lynch’s syndrome). In addition to medical care, the CDS solution can benefit organizational processes for collaborative care delivery by connecting patients, physicians and other associated members. This framework facilitates integration of different types of CDS ideal for the different healthcare processes, enabling sharable CDS capabilities within and across organizations

Next-generation sequencing-based genome diagnostics across clinical genetics centers: Implementation choices and their effects

Implementation of next-generation DNA sequencing (NGS) technology into routine diagnostic genome care requires strategic choices. Instead of theoretical discussions on the consequences of such choices, we compared NGS-based diagnostic practices in eight clinical genetic centers in the Netherlands, based on genetic testing of nine pre-selected patients with cardiomyopathy. We highlight critical implementation choices, including the specific contributions of laboratory and medical specialists, bioinformaticians and researchers to diagnostic genome care, and how these affect interpretation and reporting of variants. Reported pathogenic mutations were consistent for all but one patient. Of the two centers that were inconsistent in their diagnosis, one reported to have found 'no causal variant', thereby underdiagnosing this patient. The other provided an alternative diagnosis, identifying another variant as causal than the other centers. Ethical and legal analysis showed that informed consent procedures in all centers were generally adequate for diagnostic NGS applications that target a limited set of genes, but not for exome- and genome-based diagnosis. We propose changes to further improve and align these procedures, taking into account the blurring boundary between diagnostics and research, and specific counseling options for exome- and genome-based diagnostics. We conclude that alternative diagnoses may infer a certain level of 'greediness' to come to a positive diagnosis in interpreting sequencing results. Moreover, there is an increasing interdependence of clinic, diagnostics and research departments for comprehensive diagnostic genome care. Therefore, we invite clinical geneticists, physicians, researchers, bioinformatics experts and patients to reconsider their role and position in future diagnostic genome care

Electronic Health Record Architecture: A Systematic Review

Numerous advantages are derived from the electronic health record (EHR).Though achieving such advantages depends on its architecture, at present no unique understanding of the architecture dimensions and specifications is available. Therefore, the aim of the present study is a systematic review of architecture perception of the electronic health record. The authors searched the literature in Science Direct, Scopus, PubMed and Proudest Databases (2000 to Jun 2015).  Data extraction was done by 2 reviewers on content, structure, content/structure relationship, confidentiality and security of the EHR. Subsequent to refining the 87 retrieved studies, 25 studies were finally included in the study. In the studies and paradigms so far proposed for the EHR, a unique comprehensive architecture model from the viewpoint of research criteria has not been investigated and it has been considered only from some dimensions. Hence, we provide a new definition of the EHR architecture

Clinical information modeling processes for semantic interoperability of electronic health records: systematic review and inductive analysis

This is a pre-copyedited, author-produced PDF of an article accepted for publication in Journal of the American Medical Informatics Association following peer review. The version of record is available online at: http://dx.doi.org/10.1093/jamia/ocv008[EN] [Objective] This systematic review aims to identify and compare the existing processes and methodologies that have been published in the literature for defining clinical information models (CIMs) that support the semantic interoperability of electronic health record (EHR) systems. [Material and Methods] Following the preferred reporting items for systematic reviews and meta-analyses systematic review methodology, the authors reviewed published papers between 2000 and 2013 that covered that semantic interoperability of EHRs, found by searching the PubMed, IEEE Xplore, and ScienceDirect databases. Additionally, after selection of a final group of articles, an inductive content analysis was done to summarize the steps and methodologies followed in order to build CIMs described in those articles. [Results] Three hundred and seventy-eight articles were screened and thirty six were selected for full review. The articles selected for full review were analyzed to extract relevant information for the analysis and characterized according to the steps the authors had followed for clinical information modeling. [Discussion] Most of the reviewed papers lack a detailed description of the modeling methodologies used to create CIMs. A representative example is the lack of description related to the definition of terminology bindings and the publication of the generated models. However, this systematic review confirms that most clinical information modeling activities follow very similar steps for the definition of CIMs. Having a robust and shared methodology could improve their correctness, reliability, and quality. [Conclusion] Independently of implementation technologies and standards, it is possible to find common patterns in methods for developing CIMs, suggesting the viability of defining a unified good practice methodology to be used by any clinical information modeler.This research has been partially funded by the Instituto de Salud Carlos III (Platform for Innovation in Medical Technologies and Health), grant PT13/0006/0036 and the Spanish Ministry of Economy and Competitiveness, grants TIN2010-21388-C02-01 and PTQ-12-05620.Moreno-Conde, A.; Moner Cano, D.; Da Cruz, WD.; Santos, MR.; Maldonado Segura, JA.; Robles Viejo, M.; Kalra, D. (2015). 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Constructing a bio-health knowledge base for access via a standardised electronic health record prototype

Aim and Objectives: To explore the feasibility of accessing biological information and associated health information through a standards-based electronic health record. The objectives include constructing: a condition specific knowledge base prototype; an EHR system prototype based on a standard record architecture; and an interface that connects the two. Method: An ontology was constructed to organise biological and health information in a formal and structured way. Cystic fibrosis was selected as an exemplar condition and the Continuity of Care Record was selected for an EHR prototype application. The sequence variations information and health information in the knowledge base are presented through the EHR prototype's interface and the results are evaluated. Results: A substantive knowledge base prototype of cystic fibrosis was constructed. The content includes: the most common genetic mutations related to cystic fibrosis; time-oriented descriptions of cystic fibrosis; Cochrane conclusions; and gene therapy for cystic fibrosis. The content is organised on both time and problem oriented axes. It was found to be possible to present bio-health information that was case-specific through the EHR prototype interface. Conclusion: Sequence variations information and associated health information can be made accessible through a standards-based electronic health record prototype. Complex knowledge can be accessed, to some extent automatically, thereby providing a starting point for integrating formal and structured biological information within health record systems which can be deployed in clinical settings.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Constructing a bio-health knowledge base for access via a standardised electronic health record prototype

Aim and Objectives: To explore the feasibility of accessing biological information and associated health information through a standards-based electronic health record. Theobjectives include constructing: a condition specific knowledge base prototype; an EHR system prototype based on a standard record architecture; and an interface that connects the two.Method: An ontology was constructed to organise biological and health information in a formal and structured way. Cystic fibrosis was selected as an exemplar condition andthe Continuity of Care Record was selected for an EHR prototype application. The sequence variations information and health information in the knowledge base are presented through the EHR prototype's interface and the results are evaluated.Results: A substantive knowledge base prototype of cystic fibrosis was constructed. The content includes: the most common genetic mutations related to cystic fibrosis;time-oriented descriptions of cystic fibrosis; Cochrane conclusions; and gene therapy for cystic fibrosis. The content is organised on both time and problem oriented axes. It was found to be possible to present bio-health information that was case-specific through the EHR prototype interface.Conclusion: Sequence variations information and associated health information can be made accessible through a standards-based electronic health record prototype. Complexknowledge can be accessed, to some extent automatically, thereby providing a starting point for integrating formal and structured biological information within health recordsystems which can be deployed in clinical settings

CLINICAL GENOMIC RESEARCH MANAGEMENT

Technological advancement in Genomics has propelled research in a new era, where methods of conducting experiments have completely been renovated. Riding the wave of Information Technology, equipped with statistical tools, Genomics provide a revolutionized perspective unthought-of in the past. With the completion of the Human Genome project, we have a common reference for analysis at the level of the complete genome. High throughput technologies for gene expression, genotyping and sequencing are propelling present research. Attempts are now being made for the incorporation of these methods in the health care in a structured format. Clinicians cherish the use of genomics for the assessment disease predisposition and realizing personalized medical care for a better health care. As genome sequencing is becoming swifter and its cost reducing, the public genomic data has increased many folds. Data from other high throughput technologies and annotations further increase the storage requirements. Laboratory management software, LIMS, is now becoming the limiting factor as automation and integration increases. Thus genomics now faces the challenge of management of this enormous data catering to varied needs, not limited only for the research laboratories, but extends also to health care institutions and individual clinicians. Further, there is a growing need for the analysis and visualization of the generated data to be integrated into the same platform for a continuous research experience and systematic supervision. Data security is of prime concern, especially in health care concerning human subjects. The interest of the clinicians adds another management requirement, a delivery system for the concerned subject. Hypertension is a complex disorder with world-wide prevalence. HYPERGENES project was centered on the objective of integrating biological data and processes with Hypertension as the disease model. The HYPERGENES project focuses on the definition of a comprehensive genetic epidemiological model of complex traits like Essential Hypertension (EH) and intermediate phenotypes of hypertension such as Target Organ Damage (TOD). During the HYPERGENES project, the above mentioned challenges were comprehended and evaluated, leading to the present work as an endeavor to provide a generalized integrated solution towards the management of genomic and clinical data for clinical genomic research. This PhD thesis represents the description of AD2BioDB, biological data management platform and SeqPipe, dynamic pipeline management software, in the path of meeting the challenges posed in the area of clinical genomics. AD2BioDB provides the platform where data generated using different technologies can be managed and analyzed with reporting and visualization modules for improved understanding of the results among all research collaborators. AD2BioDB is the management software environment in which the in-silico data can be shared and analyzed. The analysis software is connected within AD2BioDB through the plug-in system. SeqPipe software provides opportunity to dynamically create pipeline workflows for the multi-step analysis of data. The interactive graphical user interface provides the opportunity for coding free pipeline creation and analysis. This tool is especially useful in the dynamic NGS analysis, where multiple tools i with different versions are in use. SeqPipe can be used as independent software or as a plug-in analysis tool within an application like AD2BioDB. The key features of AD2BioDB can be summarized as: \uf0b7 Clinical genomics data management \uf0b7 Project management \uf0b7 Data security \uf0b7 Dynamic creation of graphical representation. \uf0b7 Distributed workflow analysis \uf0b7 Reporting and alert features. \uf0b7 Dynamic integration of high throughput technologies We developed AD2BioDB as a prototype in our laboratory for providing support to the increasing genomic data and complexity of analysis. The software aims at providing a continuous research experience with a versatile platform that supports data management, analysis and public knowledge integration. Through the integration of SeqPipe into AD2BioDB, the management system becomes robust in providing a distributed analysis environment