What is the point of this work? Our vision is one of standardizing and sharing the information nurses gather in EHRs to advance insights and evidence used to prevent, diagnose, treat, and evaluate health conditions.  Additionally, the data that describes the context of the workplace has been standardized and is now moving toward implementation to explain care delivery factors that influence patient outcomes, such as staffing, turnover, or nurse satisfaction.

At the fourth annual Nursing Knowledge: Big Data Science Conference held earlier this summer in Minneapolis, MN, 170 participants heard advice from Pamela Cipriano, President of the American Nurses Association (ANA); Deborah Trautman, CEO of the American Association of Colleges of Nursing; Norma Lang, a long-time nurse leader in quality and outcomes; and representatives from the Patient-Centered Outcome Research Institute (PCORI) and legislature  on how to advance the policy agenda to integrate these essential data.

The Big Data summit, with year-round working groups, is clear evidence that a compelling shared vision, collaboration, and partnership within and interdisciplinary teams can find solutions for the common good.    Here are a few examples of what we have achieved over four years:

1. Standardized vocabulary for documentation. Earlier this year the Office of the National Coordinator (ONC) for Health Information Technology announced its recommendation for use of Logical Observation Identifiers Names and Codes (LOINC®) and Systematized Nomenclature of Medicine — Clinical Terms (SNOMED CT) as the standard terminologies for coding and electronic exchange of clinical health information. The ONC is the principal federal entity charged with coordinating efforts to implement the most advanced health information technology and the electronic exchange of health information. Big Data summit participants had launched an aggressive advocacy effort to bring about this outcome, in collaboration with the ANA.

Collecting contextual data enables health care systems to objectively evaluate and compare the effectiveness of their nursing care, staffing, and facilities – unit-by-unit and shift-by-shift. The Nursing Management Minimum Data Set (initiated by Diane (Gardner) Huber and Connie Delaney in 1997) supports administrative and management decision making that aligns the needs of the patient with the skills and knowledge of nursing providers, and has recently been added to an internationally adopted standard.

2. Streamlining documentation and creating useful data to support research. Information systems contain redundant data even within the same EHR, resulting in duplicate documentation and inconsistent data across settings such as emergency departments, intensive care units, medical-surgical units, rehabilitation, or home care. Recommendations for streamlining documentation and creating information models that integrate redundant data are emerging from the Nursing Big Data Initiative. Additionally the products of these efforts will be placed in an open-source repository for anyone to access once the work is ready for use by others.
3. Nurses’ competency in technology and documentation has been extended through nursing education standards. Completion of the American Association of Colleges of Nursing and the Gordon and Betty Moore Foundation initiative has advanced informatics competencies of nursing faculty.
4. Big data research is empowered. EHR data is necessary for ground-breaking research using nursing big data.  Moving from disparate data and documentation within organizations to data sharing across systems and organizations allows for new big data science.  Using  social and behavioral factors that influence individual health expand research personalizing research for  better health. Using  information about the  context of health care, for example who is providing care and what their expertise and  experience are, a swell as where the care is occurring help  nurses individualize high quality, safe, and low cost care.

Fueled by a shared vision of a more efficient health system, leaders from major vendors, government, and academia are collaborating more than ever.  The volunteers who have advanced this work recognize that each accomplishment is dependent upon progress across disciplines.  After 35 years of discussion, leaders,  care providers  and payers  are integrating their systems and expertise to support  nurses in delivering the most  effective health care.

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At the third annual Nursing Knowledge: Big Data Science conference, held June 3–5, 2015, presenters reported the results of 10 projects influencing the creation and use of sharable and comparable nursing data. The projects involved nurses from practice, academia, research, industry, and professional organizations. The conference proceedings, soon to be published, will include all conference activities as well as recommendations for 2015-2016 projects that will evolve through collaborative work over this next year. For further information, all presentations from the 2013, 2014, and 2015 conferences can be found on the UMN’s School of Nursing website.

Key messages from this conference include:

• “If you want to go fast, go alone. If you want to go far, go together.” As this African proverb suggests, this conference is about going together.
• In 1992, Norma Lang wrote about nursing, “If we cannot name it, we cannot control it, teach it, finance it, research it, or put it into public policy.” We now need to move beyond naming nursing and implement one or more of the nursing terminologies recognized by the American Nurses Association and do so in consistent, efficient ways to streamline documentation and create reusable data for quality improvement and research.
• According to an ANA Position Statement (March 19, 2015): “When creating clinical data warehouses for comparative effectiveness research or exchanging a Consolidated Continuity of Care Document (C-CDA), including problems and interventions, with another setting, Systematized Nomenclature of Medicine–Clinical Terms (SNOMED CT®) and Logical Observation Identifiers Names and Codes (LOINC®) should be used. LOINC should be used for coding nursing assessments and outcomes, and SNOMED CT for problems, interventions, and observation findings.”
• To ensure quality, safety, and value in healthcare, clinical decisions need to be supported by accurate, timely, and up-to-date clinical information.
• The documentation burden must be reduced by providing information in the EHR at the right time in the workflow to support evidence-based and personalized care.
• Healthcare organizations should employ nurse informaticists, who can provide valuable insight into concept representation, design, implementation, and optimization of health IT to support evidence-based practice, research, and education.
• To achieve the desired outcomes, nurse informaticists should have formal informatics education and certification.
• Engage nursing leaders to understand and advance the importance of data science to evidence-informed nursing practice to achieve the triple aim of better health, better experience, and better efficiency of healthcare.
• Develop new nursing business intelligence and analytic tools that will take advantage of the rich clinical, operational, financial, and quality/safety outcome data currently available to measure and compare nursing value.
• Engage nurses in health IT policy.

In summary, the national action plan with associated projects is moving nursing forward to have sharable and comparable data to demonstrate the value of nursing in collaboration with interprofessional colleagues. You are encouraged to support this effort. Plan to attend the next conference Jun 1-3, 2016 and join the conversation using #NursingandBigData or https://twitter.com/UMNNursing. Also, feel free to reach out or share via email, Facebook, or Twitter.

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