Integrating a Categorial Structure for Clinical Practice into EHRs.

A continuing global desire to be using clinical systems within a digital health ecosystem, able to facilitate data flows and information exchange as required to support person-centred, predictive, preventative, participatory and precision (5p) health and medical care can best be supported through the use of the standard categorial structure able to represent not only the clinical nursing practice domain but also other clinical disciplines by the generic labelling of some high-level categories. It is hypothesised that adoption of this generic clinical categorial structure within any electronic health/medical record within a well connected digital health ecosystem, supported by a cloud based openEHR platform, will enable the 5p support to be realized. This presentation provides the results of the latest update of this technical standard based on the 20+ year nursing practice categorial structure development process adopted to achieve this aim and a summary about linking this categorial structure to standard terminologies and to standard EHR/EMR system architectures.

Nursing Informatics Integration into Mainstream Health Informatics.

Nursing Informatics emerged in Australia during the early 1980s and drove the Professional development and acceptance of Health Informatics. Milestones achieved include the development of a national journal, the establishment of the Health Informatics Society of Australia and the Australasian College of Health Informatics (now collectively the Australasian Institute of Digital Health), nursing participation in Health Informatics standards development activities, adoption of the HL7 messaging standard, the delivery of numerous workshops, an annual national health informatics conference since 1993, hosting international conferences, the development and delivery of Health Informatics post graduate programs and establishing a research centre where the first prototype for an archetype repository was developed. This became the openEHR Clinical Knowledge Manager. The most recent milestone was the establishment of a private company that became a Registered Training Organisation. Continuing challenges include workforce capacity building to address the poor understanding of the need for improved data and IT governance at every level, the need to comply with proven scientific and technical principles and a need to transform national and international traditional infrastructures no longer fit for purpose to enable adequately support for global sustainable digital health ecosystems. Desired personal and aggregate data supply chains must be taken seriously and be supported by the best available technologies. Our collective biggest challenge is to improve multidisciplinary and intersectoral collaboration, semantic interoperability and optimum digital support to maintain global public health.

National healthcare systems and the need for health information governance.

This chapter gives an overview of health data, information and knowledge governance needs and associated generic principles so that information systems are able to automate such data collections from point-of-care operational systems. Also covered are health information systems' dimensions and known barriers to the delivery of quality health services, including environmental, technology and governance influences of any population's health status within the context of national health systems. This is where health information managers and health informaticians need to resolve the many challenges associated with eHealth implementations where data are assets, efficient information flow is essential, the ability to acquire new knowledge desirable, and where the use of data and information needs to be viewed from a governance perspective to ensure reliable and quality information is obtained to enhance decision making.

Impact of data governance on a nation's healthcare system building blocks.

This chapter gives an overview of a nation's healthcare system, particularly for those who are familiar with IT but not healthcare or for those working in one area of healthcare who may not be familiar with the system and data requirements across the care continuum. The structure of this chapter uses the World Health Organisation's (WHO) Health systems framework with a focus on the need for data and information governance to achieve a sustainable health system delivering improved health for all, responsively and equitably meeting genuine demands for health services, with social and financial risk protection and overall improved efficiency. It is argued that there is a need to gather the right data and to process these data in a manner that provides good information in order to more fully understand how the health system is working and where and when it isn't working well. This needs to be achieved in the most cost effective manner that doesn't detract from the allocation of resources to healthcare or the clinical workflow required to achieve quality healthcare.

Health data and data governance.

Health is a knowledge industry, based on data collected to support care, service planning, financing and knowledge advancement. Increasingly there is a need to collect, retrieve and use health record information in an electronic format to provide greater flexibility, as this enables retrieval and display of data in multiple locations and formats irrespective of where the data were collected. Electronically maintained records require greater structure and consistency to achieve this. The use of data held in records generated in real time in clinical systems also has the potential to reduce the time it takes to gain knowledge, as there is less need to collect research specific information, this is only possible if data governance principles are applied. Connected devices and information systems are now generating huge amounts of data, as never before seen. An ability to analyse and mine very large amounts of data, "Big Data", provides policy and decision makers with new insights into varied aspects of work and information flow and operational business patterns and trends, and drives greater efficiencies, and safer and more effective health care. This enables decision makers to apply rules and guidance that have been developed based upon knowledge from many individual patient records through recognition of triggers based upon that knowledge. In clinical decision support systems information about the individual is compared to rules based upon knowledge gained from accumulated information of many to provide guidance at appropriate times in the clinical process. To achieve this the data in the individual system, and the knowledge rules must be represented in a compatible and consistent manner. This chapter describes data attributes; explains the difference between data and information; outlines the requirements for quality data; shows the relevance of health data standards; and describes how data governance impacts representation of content in systems and the use of that information.

Our health language and data collections.

All communication within the health industry is dependent upon the use of our health language consisting of a very extensive and complex vocabulary. Converting this language into computable formats is necessary in a digital environment with a strong reliance on data, information and knowledge sharing. This chapter describes our health language, what terminologies and ontologies are, their use and relationships with natural language, indexing, data standards, data collections and the need for data governance.

Health information systems.

Health information provides the foundation for all decision making in healthcare whether clinical at the bed side, or at a national government level. This information is generally collected as part of systems which support administrative or clinical workflow and practice. This chapter describes the many and varied features of systems such as electronic health records (EHRs), how they fit with health information systems and how they collectively manage information flow. Systems engineering methods and tools are described together with their use to suit the health industry. This focuses on the need for suitable system architectures and semantic interoperability. These concepts and their relevance to the health industry are explained. The relationship and requirements for appropriate data governance in these systems is also considered.

Health workforce competencies needed for a digital world.

The health workforce constitutes a very significant health system building block. As such it needs to have the capacity to influence how health data are captured, processed and used at all levels of decision making. This requires a national strategy that ensures all new health professional graduates are adequately prepared and that the existing workforce is developed to make the best possible use of all available digital technologies. This chapter provides an argument for why and how the health workforce should be contributing to health information governance, followed by an historical overview of various initiatives undertaken, the results achieved and issues identified during these processes. It concludes with an exploration of strategies that may be adopted to bring about change and achieve improvements.

Health informatics - an introduction.

This chapter gives an educational overview of: * the scope of the health informatics discipline * health informatics and e-health definitions * health informatics professional networks * potential benefits of applying health informatics technologies.

Health care services, information systems & sustainability.

This chapter gives an educational overview of: * many competing characteristics within national health systems * national primary information and knowledge flows between health care entities * the role of information technologies in assisting health organizations become sustainable enterprises * the business of maintaining healthy populations for any nation * desirable e-health strategy objectives.

E-health records and future healthcare.

This chapter gives an educational overview of: * Data collected, stored in health records and used for multiple purposes * Electronic health records and how these are likely to influence our future * Personal health records * Clinical systems and their relationship to national data collections * Potential future use of new technologies.

Sustainable clinical knowledge management: an archetype development life cycle.

This chapter gives an educational overview of: 1. The significance of having a formal ontology of health care data 2. How openEHR has used an ontological approach to designing an electronic health record 3. The phases of archetype development and key steps in the process 4. The openEHR architecture and integrated development environment.

National standards in health informatics.

This chapter gives an educational overview of: * The relationship between standards and a national e-health strategy * National and international standards development processes * The Development of a national HI standards roadmap * The benefits of standards adoption.

Resource, quality and safety management.

This chapter gives an educational overview of: * Resource management relative to sustainability and the use casemix systems * Types of resources and their information system needs to support their optimal management * Quality, performance measurement options and associated information needs * Casemix systems' characteristics, usage and need for enterprise systems.

Milestones of the IMIA-NI history and future directions.

IMIA-NI's past achievements are reflected upon in the context of its current strategic directions. Two key historical milestones are described in some detail, the ISO Reference terminology model for nursing and the International Nursing Minimum Data Set development project, as this work is continuing to influence future directions in health and nursing informatics. Current features of our health care environment are explored noting the current desire of most nations to implement electronic health records (EHRs) and its relationship with IMIA-NI's strategic directions. Nurses can play their part by working collaboratively, converting their knowledge into computer processable formats, establishing the necessary professional knowledge governance infrastructure and lobbying key decision makers to establish national infrastructures that will enable the adoption and optimum use of EHRs.

Towards sustainability of health information systems: how can we define, measure and achieve it?

Health information systems (HIS) in their current form are rarely sustainable. In order to sustain our health information systems and with it our health systems, we need to focus on defining and maintaining sustainable Health Information System building blocks or components. These components need to be easily updatable when clinical knowledge (or anything else) changes, easily adaptable when business requirements or processes change, and easily exchangeable when technology advances. One major prerequisite for this is that we need to be able to define and measure sustainability, so that it can become one of the major business drivers in HIS development. Therefore, this paper analyses general definitions and indicators for sustainability, and analyses their applicability to HIS. We find that general 'Emergy analysis' is one possibility to measure sustainability for HIS. Based on this, we investigate major enablers and inhibitors to sustainability in a highlevel framework consisting of four pillars: clinical, technical, socio-technical, and political/business.

Building health informatics skills for health professionals: results from the Australian Health Informatics Skill Needs Survey.

OBJECTIVE: To ascertain health professionals' perceptions of health informatics skills required in their roles. DESIGN: A paper-based survey with a stratified random sample of Australian health professionals and a web-based survey open to all Australian health professionals were conducted. MEASUREMENT: A questionnaire on the health professionals' perceived degree of competency required for a total of 69 specific skills in five skill categories based on the International Medical Informatics Association's (IMIA) set of recommendations on education and IMIA's scientific map. RESULTS: 462 health professionals responded to the paper-based questionnaire, and 167 respondents to the Internet questionnaire. Internet respondents reported higher required degrees of competency for specific health informatics and information technology skills than paper respondents, while paper respondents valued clinical skills higher than the Internet respondents. CONCLUSION: Health professionals increasingly use information technology (IT), and some also deploy, research or develop health care IT. Consequently, they need to be adequately educated for their specific roles in health informatics. Our results inform developers of educational programs while acknowledging the diversity of roles in health informatics and the diversity of pathways towards a professional health informatics qualification.

Information literacy-what it is about? Literature review of the concept and the context.

OBJECTIVES: The use of IT in health care has merged advanced knowledge and skills for health care professionals. Former studies indicate that basic skills in computer use are no more than comprehensive competencies to manage electronically stored information in health care. The purpose of this paper is to review the literature focusing on the concept information literacy in the field of health, nursing and medical informatics. The target is to find out how information literacy is defined, in what kind of context it is presented and who are the focus of interest. METHODS: An automated literature search was performed on-line to Medline and by using the EndNote Bibliographic Software. All together the number of papers analyzed was 97 or 78% of the total literature search result. RESULTS: The survey indicates that the concept information literacy does not exist as such in the literature, but it can be found as a synonym to 'computer literacy' or even more obscure concepts such as 'informatics awareness' or 'computer experience'. The definitions of these concepts varied considerably. A variety of descriptions of educational programs were also found, none were based on the IMIA recommendations. CONCLUSIONS: In international cooperation such as that of IMIA WG1, a wide range of efforts still needs to be carried out to compile educational programmes in health informatics to enhance knowledge and skills in computer use among health care professionals.

Globalisation of health and medical informatics education--what are the issues?

PURPOSE: We are witnessing a paradigm shift in higher education as a result of technological advances, adoption of on-line learning and a greater participation in e-commerce by higher education providers. Given the dearth of academics with high-level expertise in health informatics in many countries, we need to explore how best to use our scarce resources to have the greatest possible impact regarding the preparation of health professionals such that they can make the best possible use of available informatics technologies to support health service delivery. METHODS: The International Medical Informatics Association's (IMIA) education working group together with its institutional (academic members) is exploring how best to provide global and collaborative health informatics education and research. Central Queensland University (CQU), one of these members, is also working with the Health Level Seven (HL7) organisation to provide specific standards education internationally using flexible delivery methods. RESULTS: A number of issues requiring further exploration and resolutions have been identified. An overview of these is provided.