3rd International Conference on Health Informatics and Technology June 29-30, 2016 New Orleans, Louisiana, USA

Clinical Informatics is concerned with the use of information in health care by and clinicians. Clinicians collaborate with other health care and information technology professionals to develop health informatics tools which promote patient care that is safe, efficient, effective, timely, patient-centered, and equitable. Clinical informaticians transform health care by analyzing, designing, implementing, and evaluating information and communication systems that enhance individual and population health outcomes, improve patient care, and strengthen the clinician-patient relationship. Clinical informaticians use their knowledge of patient care combined with their understanding of informatics concepts, methods, and health informatics.

Nursing informatics (NI) is the specialty that integrates nursing science with multiple information management and analytical sciences to identify, define, manage, and communicate data, information, knowledge, and wisdom in nursing practice. NI supports nurses, consumers, patients, the interprofessional healthcare team, and other stakeholders in their decision-making in all roles and settings to achieve desired outcomes. This support is accomplished through the use of information structures, information processes, and information technology. 

It deals with the resources, devices and methods required to optimize the acquisition, storage, retrieval and use of information in health and biomedicine. Health informatics tools include not only computers but also clinical guidelines, formal medical terminologies, and information and communication systems. It is applied to the areas of nursing, clinical care, dentistry, pharmacy, public health and (bio)medical research. Public health informatics has been defined as the systematic application of information and computer science and technology to public health practice, research and learning. Public health organizations are faced with the challenge of collecting and analyzing data related to the health of a population, and managing this data to maximize efficiency and efficacy. The Certificate in Public Health Informatics is designed to develop experts in the systematic application of information technology to public health practice, research and learning.

Translational Bioinformatics (TBI) is an emerging field in the study of health informatics, focused on the convergence of molecular bioinformatics, biostatistics, statistical genetics, and clinical informatics. Its focus is on applying informatics methodology to the increasing amount of biomedical and genomic data to formulate knowledge and medical tools, which can be utilized by scientists, clinicians, and patients. Furthermore, it involves applying biomedical research to improve human health through the use of computer-based information system. TBI employs data mining and analyzing biomedical informatics in order to generate clinical knowledge for application. Clinical knowledge includes finding similarities in patient populations, interpreting biological information to suggest therapy treatments and predict health outcomes.

Big data offers enormous potential for improving healthcare delivery, many of the existing claims concerning big data in healthcare are based on anecdotal reports and theoretical vision papers, rather than scientific evidence based on empirical research. Big data have learned through the various paradigms of health information technology (HIT) implementations. Though the role of HIT in reengineering the healthcare system has been well discussed and the benefits to improved processes and patient safety have been demonstrated, there is still much room for HIT outcomes-based research to demonstrate its value. HIT has also brought with it issues such as human computer interaction, technology-induced errors (e-iatrogenesis) and workaround issues, which have the potential to grow as innovations continue to be introduced into healthcare at rapid rates.

The Health informatics management (HIM) is the practice of obtaining, examining and preserving digital and traditional medical information vital to providing standard patient care. With the general computerization of health and medical records, paper-based records are being substituted with Electronic Health Records i.e. EHRs. The devices of health informatics and information technology are being increasingly utilized to initiate efficiency in information management practices in the health care sectors. Both hospital information systems i.e. "HIM" and health human resources information systems i.e. "HRHIS" are common applications of Health information management.

Health Informatics Engineering (HSE) targets the delivery of healthcare over the entire patient care cycle, which includes screening, vaccination, preventive medicine, diagnosis, treatment, medications, monitoring and checkups. Model-based decision tools create engineered innovations in clinical operations, individual treatment choice and supporting supply chains to advance safe, high-quality, consistent and accessible healthcare while avoiding unnecessary costs. HSE focuses on the design of engineered processes to combine resources and support clinical decision making to assure its effective implementation over the entire course of a patient’s care.
 

Patient engagement has always been a good thing to strive for in health care practices. Today, however, patient engagement is an essential strategy for achieving what the Institute for Healthcare Improvement calls the “triple aim” of health care: improving the experience of care, improving the health of populations, and reducing per capita costs of health care. Specifically, patient engagement can help health care practices.

Health informatics ethics will combine information from medical ethics and from informatics ethics.  This is related to recent history of these two fields so that the reader can understand the context within which modern health informatics ethics is to be discussed.  Because  of  the  unique  nature  of  medicine,  this  chapter  will  spend  considerable  space  examining  recent medical ethics first.

A clinical decision support system (CDSS) is a health information technology system that is designed to assist physicians and other health professionals with clinical decision-making tasks. A working definition has been proposed by Robert Hayward of the Centre for Health Evidence: "Clinical Decision Support systems link health observations with health knowledge to influence health choices by clinicians for improved health care". CDSSs constitute a major topic in artificial intelligence in medicine.

Health care modeling and mircosimualtion models are fast becoming an important analytical tool that policymakers and practitioners are using in a Post-ACA implementation world. Collecting terabytes of data and using it effectively are two very different tasks. The latest trends in efficient and effective ways to use data to analyze a wide array of health data is important today and this can be achieved through proper health care knowledge management and decision support systems.

Healthcare technology application is organized knowledge and skills in the form of devices, medicines, vaccines, procedures and systems developed to solve a health problem and improve quality of lives. This includes the pharmaceuticals, devices, procedures and organizational systems used in health care. Medical technology, which is a proper subset of health technology, encompasses a wide range of healthcare products and is used to diagnose, monitor or treat diseases or medical conditions affecting humans. Such technologies (applications of medical science) are intended to improve the quality of healthcare delivered through earlier diagnosis, less invasive treatment options and reductions in hospital stays and rehabilitation times. Recent advances in medical technology have also focused on cost reduction. Medical technology may broadly include medical devices, information technology, biotech, and healthcare services. The impacts of medical technology may involve social and ethical issues. For example, physicians may seek objective information from technology rather than listening to subjective patient reports.

Health Informatics Research or Clinical Research Informatics (CRI) takes the core foundations, principles, and technologies related to Health Informatics and apply these to clinical research contexts. As such, CRI is a sub-discipline of Health Informatics, and interest and activities in CRI have increased greatly in recent years given the overwhelming problems associated with the explosive growth of clinical research data and information.

Neuroinformatics is a research field concerned with the organization of neuroscience data by the application of computational models and analytical tools. These areas of research are important for the integration and analysis of increasingly large-volume, high-dimensional, and fine-grain experimental data. Neuroinformaticians provide computational tools, mathematical models, and create interoperable databases for clinicians and research scientists. Neuroscience is a heterogeneous field, consisting of many and various sub-disciplines (e.g., Cognitive Psychology, Behavioral Neuroscience, and Behavioral Genetics). In order for our understanding of the brain to continue to deepen, it is necessary that these sub-disciplines are able to share data and findings in a meaningful way; Neuroinformaticians facilitate this.

Healthcare Informatics 2016 provides great avenues for Investors seeking for investment opportunities and expanding their business horizons. Our conference is attended by participants from more than 40 countries and attracts an interesting combination of academic researchers, practitioners and individuals who are engaged in various aspects of innovations in Healthcare Informatics research and  Healthcare Policy thereby providing plenty of networking opportunities and newfound knowledge.

To explore more about business and investment opportunities write us at healthinformatics@conferenceseries.net