Hello, I'm Karen Munsen, professor at the University of Minnesota School of Nursing. In this module, we will focus on knowledge management and informatics opportunities that may be useful for our data to action initiatives. Our learning objectives for this module are to examine informatics as a possible methodology and resource to inform data to action initiatives. To appreciate principles and practices of knowledge management that underlie informatics tools and techniques. To analyze use of publicly available population health records as contextual information to manage knowledge and data for action to reduce health disparities. These learning activities are designed to pique your interest in health informatics and how that may relate to the social determinants of health and data to action initiatives. In today's data-rich world, the notion that data leads to information, information leads to knowledge and knowledge evolves into wisdom, has been put forth by numerous authors. Allee suggests there is more to the process and has proposed an archetype that makes explicit the complexity of knowledge. This notion is at the very heart of our understanding, and it shows up as the curved line that magically turns data into action through knowledge management to make a difference in the world. What is Informatics? Healthcare informatics is a discipline at the intersection of many sciences. Information science, computer science, social science, behavioral science, and health care. The interdisciplinary study of the design development, adoption, and application of information technology-based innovations in healthcare services delivery, management, and planning. It goes by many aliases. It is also called health information systems, health care informatics, medical informatics, nursing informatics, clinical informatics, consumer informatics, population health informatics, and biomedical informatics. That's a lot of words. In the fewest words possible, I would say that informatics standardizes knowledge as data for shared use by people and machines. Knowledge management is at the heart of information science. In this presentation, we'll go into detail about levels of knowledge management and their applications to the social determinants of health, based on Allee's work and building on our hourglass model publication. Which is one of your assigned readings. The levels are data, information, knowledge, meaning, philosophy, wisdom, and union, depicted here in a wheel that shows the circular nature of the knowledge management process. Data, information, knowledge. The first three levels are basic to the notion that we can expect to be able to gather discrete bits are encoded as ones and zeros and examine them in such a way that these bits fit together into a mental model. To achieve this, we need sensors or machine enabled human input. An informatics expert moral imperative is to make sure that the input is good and that the analysis is appropriate, and the knowledge that is displayed is done so in an unbiased, easy to interpret way. Everything we've discussed about data and analysis in this course applies here. The state of the science for these levels is coming along. More and more data are available. As we have seen, more and more data scientists are being trained to work with the data so that information can become knowledge. How can we make the data information and knowledge that communities need available and easily accessible? In Allee's model data, information and knowledge provide the foundation for managing meaning defined as the thing that is conveyed, especially by language. Allee suggests this thing that is conveyed, maybe ideas capturing a synthesis of relationships between and among data components. Enabling understanding of context relationships and trends. We need meaning to learn from data and to generate alternative ideas. We can see that human intelligence works to generate meaning from data. Machine learning can only suggest possibilities at this level. This is where community intelligence is especially needed as meaning needs contextual feedback for it's very validity. Philosophy, wisdom and union. The subsequent levels build on meaning. Philosophy, wisdom and union learning seeks to understand dynamic relationships and non-linear processes discerning the patterns that connect, including archetypes and metaphors, enabling explorations within self-questioning and discovery of purpose and intentions and interconnectedness. We can glean learning across these levels about the social determinants of health to inform a sense of unity, partnership, and commitment to a greater good that includes environmental and planetary health. Our work in community can create narratives based on these learnings that can transform who we are, what we know about ourselves, and what that means for us. This is why informatics matters for data to action work. Because powerful computers can be either our allies are not, and both have major implications for our health and future. This is why we need ethical guidance for social determinants of health data. This is why we need team science to bring people together who have the skills to create, use, and meaningfully interpret data and turn it into something that create positive change by informing policy. This is why we need more informatics experts and data scientists who represent diverse populations. This is why we created our specialization to give voice and shape reality in this era, in which reality is constructed by data. If you'd like to get a glimpse of this extraordinary thought leader, I've included a video in which Verna Allee shares data ideas about knowledge management for business. We began this presentation by defining informatics, and we noted that there are many health-related informatics specialties. In 2020, Pentel and colleagues challenged the informatics discipline to create a new specialty, social informatics. They asserted that this new specialty is necessary to drive research that informs how to approach the unique interoperability, execution and ethical challenges involved in incorporating social information into health care. Social informatics could be a new tool in the toolbox for better integrating social and medical care in ways that can improve individual and population health and health equity. As you read, consider their perspectives as authors. Shachak, responded positively to this notion, but emphasize that social determinants, informatics maybe a better name than Social Informatics. Whose voices should be at the table as this new specialty is developing, and what perspectives must be reflected for true success in knowledge representation and management. That's all for Part 1. Now onto Part 2, Informatics Opportunities in which we seek answers to the question, how can informatics help with my knowledge, management needs?