Call for Abstract
3rd International Conference on Health Informatics and Technology, will be organized around the theme “Transforming future health care through application of knowledge in Information technology”
Healthcare Informatics 2016 is comprised of 16 tracks and 101 sessions designed to offer comprehensive sessions that address current issues in Healthcare Informatics 2016.
Submit your abstract to any of the mentioned tracks. All related abstracts are accepted.
Register now for the conference by choosing an appropriate package suitable to you.
Health communication strategies and healthcare informatics used to improve population health outcomes and health care quality, and to achieve health equity. Ideas about health and behaviors are shaped by the communication, information, and technology that people interact with every day. Health communication and health information technology (IT) are central to health care, public health, and the way our society views health. These processes make up the context and the ways professionals and the public search for, understand, and use health information, significantly impacting their health decisions and actions.
- Track 1-1Healthcare Informatics Future
- Track 1-2Healthcare Informatics Development
- Track 1-3Healthcare Informatics Functions
- Track 1-4Healthcare Informatics Financial applications
- Track 1-5Healthcare Informatics Alternative medicine
- Track 1-6Healthcare Informatics Flu
- Track 1-7Healthcare Informatics and Medical Technology
- Track 1-8Healthcare Informatics USA
- Track 1-9Healthcare Informatics New Orleans
- Track 1-10Healthcare Informatics Epidemiology
- Track 1-11Healthcare Informatics Tools
- Track 1-12Healthcare Informatics Quality
- Track 1-13Healthcare Informatics Advance Practices
- Track 1-14Healthcare Informatics Trends
- Track 1-15Healthcare Informatics Emerging Techology
- Track 1-16Healthcare Informatics Issues
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.
- Track 2-1Nutrition Informatics
- Track 2-2Clinical Data Warehouses
- Track 2-3Clinical Research Informatics
- Track 2-4Clinical Data Warehouses
- Track 2-5Clinical Informatics Factors
- Track 2-6Clinical Informatics Applications
- Track 2-7Medical 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.
- Track 3-1Nursing Informatics Research
- Track 3-2Nursing Informatics Practice
- Track 3-3Nursing Informatics Methodology
- Track 3-4Nursing Informatics Management
- Track 3-5Nursing Informatics Implementation
- Track 3-6E-Health and Nursing Informatics
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.
- Track 4-1Geographical Health Informatics
- Track 4-2Public Health Informatics Types
- Track 4-3Consumer Health Informatics
- Track 4-4Wearable Health Informatics
- Track 4-5Consumer Health Informatics
- Track 4-6Population Health Informatics
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.
- Track 5-1Translational Bioinformatics Metagenomics
- Track 5-2Translational Bioinformatics Biological networks
- Track 5-3Translational Bioinformatics Analysis
- Track 5-4Translational Bioinformatics Medicine
- Track 5-5Translational bioinformatics Applications
- Track 5-6Translational and Integrative bioinformatics
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.
- Track 6-1Big data Analytics
- Track 6-2Big Data Experiences
- Track 6-3Big data Medical Devices
- Track 6-4Big Data Medical Records
- Track 6-5Big data Processing
- Track 6-6Big Data Systems
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.
- Track 7-1Health Information management in Telemedicine
- Track 7-2Healthcare Mobile APPS
- Track 7-3Health Information Management Coding
- Track 7-4Health Information Management data
- Track 7-5Health Information management in mHealth
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.
- Track 8-1Health Systems Engineering Implementation
- Track 8-2Healthcare Systems Technology and Techniques
- Track 8-3Health Information systems
- Track 8-4Health information systems for chronic disease
- Track 8-5Health Systems Engineering Interference
- Track 8-6Healthcare Applications
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.
- Track 9-1Healthcare Informatics and Patient Safety
- Track 9-2 Patient data Integration
- Track 9-3Patient Safety Management
- Track 9-4Patient Care Communication
- Track 9-5Patient Medication Adherence
- Track 9-6e-patients
- Track 9-7 Patient fitness App Integration
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.
- Track 10-1Healthcare Ethical Issues
- Track 10-2Healthcare workforce of the future
- Track 10-3Health Informatics Clinical practice
- Track 10-4Health Care quality and efficiency
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.
- Track 11-1Computer support for surgical intervention
- Track 11-2Epidemiological modeling
- Track 11-3Health Informatic Methodologies
- Track 11-4Health Informatic Warehousing
- Track 11-5Health Informatic and Surgery
- Track 11-6Health Informatics Data
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.
- Track 12-1Healthcare Predictive Modeling
- Track 12-2Healthcare Modeling in System Biology
- Track 12-3Healthcare Modeling for e-Health
- Track 12-4Healthcare Modelling in Biological Systems
- Track 12-5Healthcare Biomedical modeling
- Track 12-6Healthcare Modeling Evaluation
- Track 12-7Health Systems Simulation
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.
- Track 13-1Mobile Health care
- Track 13-2Healthcare Telemetry
- Track 13-3Healthcare Wireless Systems
- Track 13-4Healthcare Software Systems
- Track 13-5e-Health Informatics
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.
- Track 14-1Electronic Health Records
- Track 14-2Electronic Medical Records
- Track 14-3EHR Reports
- Track 14-4EHR Implementation
- Track 14-5EHR Systems
- Track 14-6EHR software
- Track 14-7Data Mining
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.
- Track 15-1Computational Neuroscience
- Track 15-2Neurotechnology
- Track 15-3Brain Computer Interfaces
- Track 15-4Electrophysiology
- Track 15-5Neuroscience Imaging
- Track 15-6Neurological Diseases
- Track 15-7Molecular Biology
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 [email protected]