International Conference on Nursing Informatics


"ICT to Improve Quality and Safety at the Point Of Care"

6-8 JUNE 2018, GUADALAJARA, MEXICO


International Conference on Nursing Informatics 2018


1.- Point of care solutions, models and devices


Clinical point of care is the point in time when clinicians deliver healthcare products and services to patients at the time of care. The increased adoption of electronic health records (EHR) in healthcare institutions and practices creates the need for electronic POC documentation through the use of various medical devices. POC documentation is meant to assist clinicians by minimizing time spent on documentation and maximizing time for patient care. Examples of the successful application of this technology are the Electronic Nursing Record, data derived from a variety of medical devices and patient monitors, clinical surveillance systems that involve advanced algorithms and data management systems that can be used to prevent serious conditions from occurring, and apps for specific follow up of clinical parameters and treatment adherence.


2.- Big Data Analytics and Decision support

Intelligent decision support systems (IDSS), through the interpretive analysis of large-scale patient data with intelligent and knowledge-based methods, “allow doctors and nurses to quickly gather information and process it in various ways in order to assist with making diagnosis and treatment decision”. IDSS can be applied in healthcare in diverse areas such as the examination of real-time data from diverse monitoring devices, analyses of patient and family history for the purpose of diagnosis, reviews of common characteristics and trends in medical record databases and many more areas. Diagnose by regularly interpreting and monitoring patient data. An IDSS can implement rules and patterns for individual patients, based on clinical parameters, and raise warning flags when such rules are violated. These flags can lead to clinical interventions that save lives. Help chronic disease management through establishing benchmarks and alerts. For chronically ill patients, a deviation noticed by an IDSS in, say, a blood test reading from a diabetic patient could result in an intervention before the patient gets into difficulty. Help public health surveillance by detecting pandemic diseases or in surveillance of chronic diseases. In case of a pandemic, an IDSS can interpret data and predict possible future spread of the disease. Perform regular clinical decision support functions like preventing drug-drug interactions.


3.- Meaningful use of electronic information systems

Intelligent decision support systems (IDSS), through the interpretive analysis of large-scale patient data with intelligent and knowledge-based methods, “allow doctors and nurses to quickly gather information and process it in various ways in order to assist with making diagnosis and treatment decision”. IDSS can be applied in healthcare in diverse areas such as the examination of real-time data from diverse monitoring devices, analyses of patient and family history for the purpose of diagnosis, reviews of common characteristics and trends in medical record databases and many more areas. Diagnose by regularly interpreting and monitoring patient data. An IDSS can implement rules and patterns for individual patients, based on clinical parameters, and raise warning flags when such rules are violated. These flags can lead to clinical interventions that save lives. Help chronic disease management through establishing benchmarks and alerts. For chronically ill patients, a deviation noticed by an IDSS in, say, a blood test reading from a diabetic patient could result in an intervention before the patient gets into difficulty. Help public health surveillance by detecting pandemic diseases or in surveillance of chronic diseases. In case of a pandemic, an IDSS can interpret data and predict possible future spread of the disease. Perform regular clinical decision support functions like preventing drug-drug interactions.


4.- Quality, safety and ethics

Ethical issues in both nursing practice (e.g. ethical and value conflict, human rights issues, and moral distress among nurses) and quality improvement (e.g. confidentiality issues, patient involvement, ethical approval dilemmas) coupled with shortages of healthcare and human resources, increased patient transfers in the care environment, and their consequences for patient safety and quality outcomes continue to plague the workplaces of nurses. In fact, the frequency of moral distress among nurses, arising from unresolved ethical issues, negatively correlates with the quality of nursing care. Hence, these conditions culminated in a growing support for the role, management, and integration of ethics quality in healthcare. The relevance of ethics quality to nursing is evident also from the need among frontline nurses and managers for more practical and systematic ways to address everyday, overlapping clinical and organizational ethical issues. Therefore, ethics quality remains a key performance area (KPA) and key performance indicator (KPI) of a continuous quality improvement (CQI) strategy in nursing. Thus, ethics quality in nursing is seen as a pragmatic response to balance a complex and convoluted problem of quality and patient safety. As an integrated perspective, ethics quality merges the normative and empirical aspects of ethics and quality, clinical ethics and organizational ethics, and can serve as a way to provide nurses and patients, with a net- work of accessible ethical tools and educational resources (via the use of technology) and facilitate ethical competencies (e.g. patient-centered care and decision making, interprofessional collaboration) to improve ethically safe nursing care and research for patients, communities, and populations.


5.- Patient participation and citizen involvement

Patient and citizen participation is now regarded as central to the promotion of sustainable health and health care. Involvement efforts create and encounter many diverse ethical challenges that have the potential to enhance or undermine their success. This includes different expressions of patient and citizen participation and the support health ethics offers. It is contended that despite its prominence and the link between patient empowerment and autonomy, traditional bioethics is insufficient to guide participation efforts. In addition, the turn to a “social paradigm” of ethics in examinations of biotechnologies and public health does not provide an account of values that is commensurable with the pervasive autonomy paradigm. This exacerbates rather than eases tensions for patients and citizens endeavoring to engage with health. Citizen and patient participation must have a significant influence on the way we do health ethics if its potential is to be fulfilled.


6.- Education, competences and capacity building5.- Patient participation and citizen involvement

Major changes in the health care system and practice environments will require equally profound changes in the education of nurses both before and after they receive their licenses. Nursing education at all levels needs to provide a better understanding of and experience in care management, quality improvement methods, systems-level change management, and the reconceptualized roles of nurses in a reformed health care system. Nursing education should serve as a platform for continued lifelong learning and include opportunities for seamless transition to higher degree programs. Accrediting, licensing, and certifying organizations need to mandate demonstrated mastery of core skills and competencies to complement the completion of degree programs and written board examinations. To respond to the underrepresentation of racial and ethnic minority groups and men in the nursing workforce, the nursing student body must become more diverse. Finally, nurses should be educated with physicians and other health professionals as students and throughout their careers. Papers describing successful Nursing Informatics programs in industrialized countries and emerging economies are welcome to be presented.




 Important dates


Opening of NI2018 Registrations:
September 1, 2017
Deadline for Full Paper, Student Paper, and Poster submissions:
November 15, 2017
Notification of Acceptance:
January 15, 2018
Deadline for final version of submissions:
February 28, 2018
NI2018:
June 6 - 8, 2018