Nursing Knowledge: Big Data Science-Implications for Nurse Leaders.

The integration of Big Data from electronic health records and other information systems within and across health care enterprises provides an opportunity to develop actionable predictive models that can increase the confidence of nursing leaders' decisions to improve patient outcomes and safety and control costs. As health care shifts to the community, mobile health applications add to the Big Data available. There is an evolving national action plan that includes nursing data in Big Data science, spearheaded by the University of Minnesota School of Nursing. For the past 3 years, diverse stakeholders from practice, industry, education, research, and professional organizations have collaborated through the "Nursing Knowledge: Big Data Science" conferences to create and act on recommendations for inclusion of nursing data, integrated with patient-generated, interprofessional, and contextual data. It is critical for nursing leaders to understand the value of Big Data science and the ways to standardize data and workflow processes to take advantage of newer cutting edge analytics to support analytic methods to control costs and improve patient quality and safety.

A national action plan for sharable and comparable nursing data to support practice and translational research for transforming health care.

BACKGROUND: There is wide recognition that, with the rapid implementation of electronic health records (EHRs), large data sets are available for research. However, essential standardized nursing data are seldom integrated into EHRs and clinical data repositories. There are many diverse activities that exist to implement standardized nursing languages in EHRs; however, these activities are not coordinated, resulting in duplicate efforts rather than building a shared learning environment and resources. OBJECTIVE: The purpose of this paper is to describe the historical context of nursing terminologies, challenges to the use of nursing data for purposes other than documentation of care, and a national action plan for implementing and using sharable and comparable nursing data for quality reporting and translational research. METHODS: In 2013 and 2014, the University of Minnesota School of Nursing hosted a diverse group of nurses to participate in the Nursing Knowledge: Big Data and Science to Transform Health Care consensus conferences. This consensus conference was held to develop a national action plan and harmonize existing and new efforts of multiple individuals and organizations to expedite integration of standardized nursing data within EHRs and ensure their availability in clinical data repositories for secondary use. This harmonization will address the implementation of standardized nursing terminologies and subsequent access to and use of clinical nursing data. CONCLUSION: Foundational to integrating nursing data into clinical data repositories for big data and science, is the implementation of standardized nursing terminologies, common data models, and information structures within EHRs. The 2014 National Action Plan for Sharable and Comparable Nursing Data for Transforming Health and Healthcare builds on and leverages existing, but separate long standing efforts of many individuals and organizations. The plan is action focused, with accountability for coordinating and tracking progress designated.

Ambient Findability: Developing a Flowsheet Ontology for i2B2.

The process of moving from the locally defined flowsheet ontology containing redundancy and jargon to one understandable by researchers is described. Over 250 million nursing flowsheet observations were imported into a data repository that uses the i2b2 framework. Focus groups were used to derive a new ontology model--18 templates were identified. One hundred measures, 50% of all patient observations over 36 months, were encoded in SNOMED CT(©). 78% of the concepts were mapped.

Development of the nursing problem list subset of SNOMED CT®.

OBJECTIVE: To create an interoperable set of nursing diagnoses for use in the patient problem list in the EHR to support interoperability. DESIGN: Queries for nursing diagnostic concepts were executed against the UMLS Metathesaurus to retrieve all nursing diagnoses across four nursing terminologies where the concept was also represented in SNOMED CT. A candidate data set was retrieved and included the nursing diagnoses and corresponding SNOMED CT concepts from the UMLS Metathesaurus. The team members identified the concepts that met the semantic selection criteria for inclusion in the nursing problem list. RESULTS: 1320 concepts were returned in the initial UMLS Metathesaurus query of nursing diagnostic concepts. Further analysis was conducted to identify those nursing diagnostic concepts mapped to SNOMED CT and duplicate concepts were removed resulting in 591 unique UMLS Metathesaurus concepts. The query extracted all concepts from two of the nursing terminologies that contained interventions and outcomes. After cleaning the dataset, the final count of SNOMED CT concepts in the nursing problem list subset is 369. CONCLUSIONS: The problem list is a key component of the patient care and has been acknowledged as critical by the EHR Meaningful Use criteria. Nursing diagnoses on the problem list are foundational for constructing a nursing care plan. A multidisciplinary patient problem list will facilitate communication and evaluation of the contribution of nursing care to the patient's clinical care experiences and outcomes.

Expressing observations from electronic medical record flowsheets in an i2b2 based clinical data repository to support research and quality improvement.

While nursing documentation in electronic medical record (EMR) flowsheets may represent the largest investment of clinician time with information systems, organizations lack tools to visualize and repurpose this data for research and quality improvement. Incorporating flowsheet documentation into a clinical data repository and methods to reduce the flowsheet ontology's redundancy are described. 411 million flowsheet observations, derived from an EMR predominantly used in inpatient, outpatient oncology, and emergency room settings, were incorporated into a repository using the i2b2 framework. The local flowsheet ontology contained 720 "templates" employing 5,379 groups (2,678 distinct), 37,836 measures (13,659 distinct) containing 226,666 choices for a total size of 270,641. Aggressive pruning and clustering resulted in 150 templates, 743 groups (615 distinct), 6,950 measures (4,066 distinct) with 22,497 choices, and size of 30,371. Making nursing data accessible within i2b2 provides a new perspective for contributing clinical organizations and heightens collaboration between the academic and clinical activities.

Educating a health terminologist.

An overview of competencies and suggestions for educating healthcare terminologists is presented. This new role in healthcare informatics requires formal and informal education that pays particular attention to the adult learner. Knowledge of terminology and informatics standards development is critical, as well as knowledge about the use of terminology management servers.

Creating experiential learning activities using Web 2.0 tools and technologies: a case study.

Learning is no longer an internal individual activity but occurs through networks and connections. The aim of this project was to teach online health informatics students to use Web 2.0 tools and technologies to form networks and connections through experiential learning assignments. Web 2.0 tools and technologies were evaluated using a criteria checklist prior to implementation for students enrolled in health informatics classes at the University of Kansas School of Nursing. Health informatics students have developed competencies using an instant message service, blogging, concept mapping, social bookmarking, and interacting a virtual environment. In the future, health care professionals will have to work in rapidly changing environments and keep abreast of new innovations and tools, learn to use those tools, and to teach others about the tools.

Second life: not your conventional simulation.

Second Life is a massive, multiuser, virtual environment. The University of Kansas School of Nursing has introduced SL into the health informatics curriculum as a virtual environment for students and faculty to interact and communicate. Students have successfully completed course activities in SL. Informatics faculty continue to develop simulations in SL.

Visualizing simulated learning experiences through the use of informatics tools.

High-fidelity simulation technology is a growing educational technology. Designing effective simulations requires the use of informatics tools such as UML modeling. This poster demonstrates the steps in modeling a simulation exercise.

Using a modified electronic health record to develop nursing process skills.

In our study, we described the experiences and behaviors of beginning nursing students learning the nursing process using a modified electronic health record. Eight students led by an experienced nursing instructor from a midwestern university comprised the criterion purposive sample. Data were obtained from observations of the group, interviews with students and the teacher, and evaluation of care plans that were generated using the technology. Two foundational themes were identified through qualitative content analysis: Techno-Savvy Students and Teacher, Simulated Technology, and Data-Rich Case Studies--a valuable hybrid "SEED" for learning. Seeing, Hearing, and Doing--a catalyst for application and spontaneous interaction. The concluding theme emerged: Honing the Data Gatherer and Data User Roles with a Modified Electronic Health Record--an authentic, learner-centered experience. Further study is needed to measure learning outcomes with similar technology-based, learner-centered activities.

Guideposts to the future--an agenda for nursing informatics.

As new directions and priorities emerge in health care, nursing informatics leaders must prepare to guide the profession appropriately. To use an analogy, where a road bends or changes directions, guideposts indicate how drivers can stay on course. The AMIA Nursing Informatics Working Group (NIWG) produced this white paper as the product of a meeting convened: 1) to describe anticipated nationwide changes in demographics, health care quality, and health care informatics; 2) to assess the potential impact of genomic medicine and of new threats to society; 3) to align AMIA NIWG resources with emerging priorities; and 4) to identify guideposts in the form of an agenda to keep the NIWG on course in light of new opportunities. The anticipated societal changes provide opportunities for nursing informatics. Resources described below within the Department of Health and Human Services (HHS) and the National Committee for Health and Vital Statistics (NCVHS) can help to align AMIA NIWG with emerging priorities. The guideposts consist of priority areas for action in informatics, nursing education, and research. Nursing informatics professionals will collaborate as full participants in local, national, and international efforts related to the guideposts in order to make significant contributions that empower patients and providers for safer health care.

Teaching undergraduate nursing students critical thinking: An innovative informatics strategy.

Simulated e-Health Delivery System (SEEDS) uses a clinical information system (CIS) to teach students how to process data from virtual patient case studies and work with information technology. SEEDS was developed in response to the Institute of Medicine recommendation that students be taught about information systems in order to improve quality patient care and reduce errors. Curriculum implications, implementation of the system, and technology challenges are discussed.

Practical definition of SNOMED CT concepts: The case of education, advice and counselling.

Rigour is needed in the construction of health terminologies to avoid introducing ambiguity and error into clinical records. When two large scale terminologies (SNOMED RT and Clinical terms Version 3) were merged to form SNOMED CT) a number duplicate and ambiguous concepts were introduced. The SNOMED nursing working group was tasked with producing a draft editorial policy to resolve duplications and ambiguities in terms related to education, advice and counselling. Consultation and input from two opportunistic workshops resulted in a draft policy that was tested before being approved for use. Education and counselling were identified as different concepts but the consensus view was it was not possible to differentiate between related concepts such as advice about, teaching and training in a way that will allow unambiguous use in practice. Expansion of existing working groups and improved communications infrastructure will support more widespread clinical input to SNOMED CT maintenance and updating.

Bedside, classroom and bench: collaborative strategies to generate evidence-based knowledge for nursing practice.

The rise of evidence-base practice (EBP) as a standard for care delivery is rapidly emerging as a global phenomenon that is transcending political, economic and geographic boundaries. Evidence-based nursing (EBN) addresses the growing body of nursing knowledge supported by different levels of evidence for best practices in nursing care. Across all health care, including nursing, we face the challenge of how to most effectively close the gap between what is known and what is practiced. There is extensive literature on the barriers and difficulties of translating research findings into practical application. While the literature refers to this challenge as the "Bench to Bedside" lag, this paper presents three collaborative strategies that aim to minimize this gap. The Bedside strategy proposes to use the data generated from care delivery and captured in the massive data repositories of electronic health record (EHR) systems as empirical evidence that can be analysed to discover and then inform best practice. In the Classroom strategy, we present a description for how evidence-based nursing knowledge is taught in a baccalaureate nursing program. And finally, the Bench strategy describes applied informatics in converting paper-based EBN protocols into the workflow of clinical information systems. Protocols are translated into reference and executable knowledge with the goal of placing the latest scientific knowledge at the fingertips of front line clinicians. In all three strategies, information technology (IT) is presented as the underlying tool that makes this rapid translation of nursing knowledge into practice and education feasible.

Where is the nursing in SNOMED CT? CTGFN has the answer!

The SNOMED" micro CTGFN (Convergent Terminology Group for Nursing) is a working group reporting to the SNOMED International Editorial Board. They are charged with ensuring a terminology supportive of nursing's requirement for describing patient care. The strategies utilized for nursing content follow.

Information model and terminology model issues related to goals.

Goal statements are a significant component of structures that support the process of health care delivery such as practice guidelines, standards of care, critical pathways, disease management plans, patient education plans, and nursing care plans. Although these structures are increasingly computer-based, there has been little attention to the formal representation of goal statements. This is a necessary prerequisite for enabling semantic interoperability. Existing and evolving information model and terminology model standards offer some approaches that may be applicable to goal statements, however, a number of issues require resolution