Integrating genetic information resources with an EHR

posterThe integration between the electronic health record (HER) and on0line information resources, using tools such as "infobuttons", is considered a promising solution to fulfill clinicians' information needs at the point-of-care. This article describes the implementation of "infobutton" links from a problem list of a web-based HER to two on-line genetic information resources: Genetics Home Reference (GHR) and GeneTests

Big Data Transforms Discovery-Utilization Therapeutics Continuum.

Enabling omic technologies adopt a holistic view to produce unprecedented insights into the molecular underpinnings of health and disease, in part, by generating massive high-dimensional biological data. Leveraging these systems-level insights as an engine driving the healthcare evolution is maximized through integration with medical, demographic, and environmental datasets from individuals to populations. Big data analytics has accordingly emerged to add value to the technical aspects of storage, transfer, and analysis required for merging vast arrays of omic-, clinical-, and eco-datasets. In turn, this new field at the interface of biology, medicine, and information science is systematically transforming modern therapeutics across discovery, development, regulation, and utilization

Semantic Integration of Cervical Cancer Data Repositories to Facilitate Multicenter Association Studies: The ASSIST Approach

The current work addresses the unifi cation of Electronic Health Records related to cervical cancer into a single medical knowledge source, in the context of the EU-funded ASSIST research project. The project aims to facilitate the research for cervical precancer and cancer through a system that virtually unifi es multiple patient record repositories, physically located in different medical centers/hospitals, thus, increasing fl exibility by allowing the formation of study groups “on demand” and by recycling patient records in new studies. To this end, ASSIST uses semantic technologies to translate all medical entities (such as patient examination results, history, habits, genetic profi le) and represent them in a common form, encoded in the ASSIST Cervical Cancer Ontology. The current paper presents the knowledge elicitation approach followed, towards the defi nition and representation of the disease’s medical concepts and rules that constitute the basis for the ASSIST Cervical Cancer Ontology. The proposed approach constitutes a paradigm for semantic integration of heterogeneous clinical data that may be applicable to other biomedical application domains

A bi-objective genetic algorithm approach to risk mitigation in project scheduling

A problem of risk mitigation in project scheduling is formulated as a bi-objective optimization problem, where the expected makespan and the expected total cost are both to be minimized. The expected total cost is the sum of four cost components: overhead cost, activity execution cost, cost of reducing risks and penalty cost for tardiness. Risks for activities are predefined. For each risk at an activity, various levels are defined, which correspond to the results of different preventive measures. Only those risks with a probable impact on the duration of the related activity are considered here. Impacts of risks are not only accounted for through the expected makespan but are also translated into cost and thus have an impact on the expected total cost. An MIP model and a heuristic solution approach based on genetic algorithms (GAs) is proposed. The experiments conducted indicate that GAs provide a fast and effective solution approach to the problem. For smaller problems, the results obtained by the GA are very good. For larger problems, there is room for improvement

Marshfield Clinic: Health Information Technology Paves the Way for Population Health Management

Highlights Fund-defined attributes of an ideal care delivery system and best practices, including an internal electronic health record, primary care teams, physician quality metrics and mentors, and standardized care processes for chronic care management

Organizing for Higher Performance: Case Studies of Organized Delivery Systems

Offers lessons learned from healthcare delivery systems promoting the attributes of an ideal model as defined by the Fund: information continuity, care coordination and transitions, system accountability, teamwork, continuous innovation, and easy access

Are providers prepared for genomic medicine: interpretation of Direct-to-Consumer genetic testing (DTC-GT) results and genetic self-efficacy by medical professionals.

BACKGROUND:Precision medicine is set to deliver a rich new data set of genomic information. However, the number of certified specialists in the United States is small, with only 4244 genetic counselors and 1302 clinical geneticists. We conducted a national survey of 264 medical professionals to evaluate how they interpret genetic test results, determine their confidence and self-efficacy of interpreting genetic test results with patients, and capture their opinions and experiences with direct-to-consumer genetic tests (DTC-GT). METHODS:Participants were grouped into two categories, genetic specialists (genetic counselors and clinical geneticists) and medical providers (primary care, internists, physicians assistants, advanced nurse practitioners, etc.). The survey (full instrument can be found in the Additional file 1) presented three genetic test report scenarios for interpretation: a genetic risk for diabetes, genomic sequencing for symptoms report implicating a potential HMN7B: distal hereditary motor neuropathy VIIB diagnosis, and a statin-induced myopathy risk. Participants were also asked about their opinions on DTC-GT results and rank their own perceived level of preparedness to review genetic test results with patients. RESULTS:The rates of correctly interpreting results were relatively high (74.4% for the providers compared to the specialist's 83.4%) and age, prior genetic test consultation experience, and level of trust assigned to the reports were associated with higher correct interpretation rates. The self-selected efficacy and the level of preparedness to consult on a patient's genetic results were higher for the specialists than the provider group. CONCLUSION:Specialists remain the best group to assist patients with DTC-GT, however, primary care providers may still provide accurate interpretation of test results when specialists are unavailable

Implementation of Pharmacogenomics into Electronic Health Record and Clinical Decision Support

The advent of electronic health records (EHR) and clinical decision support (CDS) has brought numerous changes in the healthcare field and has improved how patients receive care. The field of pharmacogenomics has made many breakthrough discoveries in the last few decades and these new advances have immensely reduced the cost of genetic testing. As advances have been made, researchers have discovered that individuals may respond to a medication differently due to genetic variants. There is a shift in the medical field from a one size fits all model to a personalized medicine model based on genetic information. Institutions have started to incorporate genetic information in their EHR and CDS systems to aid clinicians in the prescribing process. The rate of implementation is uneven among the institutions across the United States. Healthcare institutions have encountered some challenges associated with implementing pharmacogenomic data into CDS and EHR system. These challenges include lack of clinician education about pharmacogenomic data, poor user interface, and lack of resources for additional information for these alerts. If these challenges are overcome, there is great potential for pharmacogenomic CDS systems to help improve patient care and reduce adverse drug events