- Email: [email protected]
Big data, data science, and big contributions
Available online at www.sciencedirect.com
Nurs Outlook 64 (2016) 113e114
www.nursingoutlook.org
From the Editor
Big data, data science, and big contributions
Marion E. Broome, PhD, RN, FAAN
“The goal is to turn data into information and information into insight.” eCarly Fiorina The changes in health care and health education over the past decade have produced many reports focusing on how we can best increase access, increase quality and decrease cost to improve the health of American citizens. Big data and data science are concepts found throughout those reports. Many universities are developing departments of ‘data analytics’ eespecially those with academics medical centers and engineering schools to figure out how to train graduates to harness the power of all the data that is now available to us-everyday-using powerful analytics. So what is big data science? It is a new interdisciplinary field in which teams of scientists use automated methods to collect, extract and analyze massive amounts of data to answer important questions heretofore not answerable. Data science is a philosophy, a collection of methods and a suite of analytics that focuses on data storage, transport, and cleaning procedures in addition to visualization tools. Biomedical big data is more that just very large data sets, or just many sources of data available at the same time. It is diverse, complex, disorganized and multimodal data generated by hospitals, researchers, and individuals who wear mobile devices and sensors that provide real time data about health status and parameters (National Institutes of Health, 2016). The data sources can include genetic, imaging, environmental exposure, and behaviors.
The use of this data holds much promise for all but for nursing, as both a profession and a discipline, this is clearly an opportunity. This past February at the Doctoral Conference sponsored by the Association of Colleges of Nursing several nationally known nurse researchers who are experts in data science and its applications presented. Bakken, Brennan and Westra (see also Brennan & Bakken, 2015; Westra, Bill, Savik & Hou, 2013) provided numerous examples of how relevant this new science is to, and for, nursing. This new field is often unwieldy and faces many challenges. And the big question is how ready are we as a discipline and profession to take advantage of and contribute to big data science? One of the biggest challenges to nursing’s contribution is how we prepare our faculty, students and current clinicians to be more aware of the precepts, methods and analytic tools in this field. How are we exposing our undergraduate students to these concepts? After all they will as nurses be involved as health coaches for patients whose precision/personalized medical treatment plans will be based on some of the big data that provides a foundation for treating individuals based on their genome, their environment, their medication profile, etc. What about our graduate students, some of whom will be the providers making decisions about ‘incoming data’ from their patients own lifestyle monitors? And our nurse scientists, when the ‘data’ they need to answer their research questions are collected for them and housed in systems too large to manage on a laptop or even on some servers. In a “Call to Action” paper published in Nursing Outlook, Clancy et al. (2013) called for the profession’s engagement in big data science and provided a clear roadmap for educating all nurses and nurse leaders about how to advocate for valuing of nursing data and use of EHR standards that ensure a nursing voice is evident. At the 2016 Doctoral Education Conference Bonnie Westra (University of Minnesota), Patricia B. Brenner (University of Wisconsin) and Suzanne Bakken (Columbia University) enurse researchers who have been doing this work for yearsegave a series of excellent presentations that as a whole provided the audience with not only an overview of that philosophy, methods and
114
Nurs Outlook 64 (2016) 113e114
analytics but how this field is so highly relevant to nursing. They were each very clear that data science will not replace entirely the traditional methods nurse researchers engage in. However, they were also clear about how critical it is that we all concentrate on preparing nurse clinicians who understand how to use electronic medical records and how the knowledge produced from them guides their care and how it can be used to evaluate new models of care. They also emphasized how PhD and DNP program faculty must integrate these concepts, methods and analytics into our doctoral programs. There is no shortage of examples of how these methods can be used to improve care delivery and quality of treatment and care for patients in our systems. As I reflected back on the last 15 years it seems we as a profession were slow and methodical in our adoption of the field of informaticsewith only a select group of scholars and expert clinicians really engaged in preparing relatively small number of graduates (compared to other specialties). And while informatics is one solid foundation from which big data science evolved it is not the same thing as informatics. It doesn’t appear we have another 15 years to change our curriculaeyet if we don’t nurses in the near future will not have a voice, much less an active role in shaping health care. Knowledge development and translation science has once again moved very quickly. Leaders in academe and practice must think about how we can provide the resources for faculty and students to prepare themselves to understand, interpret, use and the new methods and findings from these studies. In addition to resources it would seem expectations for taking advantage of those resources for gaining additional knowledge and skills to enable this integration is very important. As our colleagues we conduct research with across our campuses embrace data science we must be ready to not just be ‘at the table’, but to be active participants in new initiatives to help shape insights from the volumes of information available to health care.
references
Brennan, P., & Bakken, S. (2015). Nursing needs big data and big data needs nursing. Journal of Nursing Scholarship, 47(5), 477e484. Clancy, T., Bowles, K., Gelinas, L., Androvitch, I., Delaney, C., Matney, S., ., Westra, B. (2013). A call to action: Engage in big data science. Nursing Outlook, 62(1), 62e64. National Institutes of Health. (2016). Retrived from http:// dtasciences.nih.gov/bd2k/about/what Westra, B., Bliss, D., Savik, K., Hou, Y., & Borchert, A. (2013). Effectiveness of wound, ostomy, and continence nurses on agency level wound and incontinence outcomes in home health care. Journal of Wound, Ostomy, and Continence Nursing, 40, 135e142.
Author Description Marion E. Broome is the Editor-in-Chief of Nursing Outlook. Marion E. Broome, PhD, RN, FAAN Dean and Vice Chancellor for Nursing Affairs Duke University School of Nursing Associate Vice President for Academic Affairs Duke University Health System School of Nursing Duke University Durham, NC Corresponding author: Marion E. Broome, Dean and Vice Chancellor for Nursing Affairs Duke University School of Nursing Associate Vice President for Academic Affairs Duke University Health System School of Nursing Duke University DUMC 3322, 307 Trent Dr., Durham, NC 27710. E-mail address: [email protected] 0029-6554/$ e see front matter Ó 2016 Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.outlook.2016.02.001
Nurs Outlook 64 (2016) 113e114
www.nursingoutlook.org
From the Editor
Big data, data science, and big contributions
Marion E. Broome, PhD, RN, FAAN
“The goal is to turn data into information and information into insight.” eCarly Fiorina The changes in health care and health education over the past decade have produced many reports focusing on how we can best increase access, increase quality and decrease cost to improve the health of American citizens. Big data and data science are concepts found throughout those reports. Many universities are developing departments of ‘data analytics’ eespecially those with academics medical centers and engineering schools to figure out how to train graduates to harness the power of all the data that is now available to us-everyday-using powerful analytics. So what is big data science? It is a new interdisciplinary field in which teams of scientists use automated methods to collect, extract and analyze massive amounts of data to answer important questions heretofore not answerable. Data science is a philosophy, a collection of methods and a suite of analytics that focuses on data storage, transport, and cleaning procedures in addition to visualization tools. Biomedical big data is more that just very large data sets, or just many sources of data available at the same time. It is diverse, complex, disorganized and multimodal data generated by hospitals, researchers, and individuals who wear mobile devices and sensors that provide real time data about health status and parameters (National Institutes of Health, 2016). The data sources can include genetic, imaging, environmental exposure, and behaviors.
The use of this data holds much promise for all but for nursing, as both a profession and a discipline, this is clearly an opportunity. This past February at the Doctoral Conference sponsored by the Association of Colleges of Nursing several nationally known nurse researchers who are experts in data science and its applications presented. Bakken, Brennan and Westra (see also Brennan & Bakken, 2015; Westra, Bill, Savik & Hou, 2013) provided numerous examples of how relevant this new science is to, and for, nursing. This new field is often unwieldy and faces many challenges. And the big question is how ready are we as a discipline and profession to take advantage of and contribute to big data science? One of the biggest challenges to nursing’s contribution is how we prepare our faculty, students and current clinicians to be more aware of the precepts, methods and analytic tools in this field. How are we exposing our undergraduate students to these concepts? After all they will as nurses be involved as health coaches for patients whose precision/personalized medical treatment plans will be based on some of the big data that provides a foundation for treating individuals based on their genome, their environment, their medication profile, etc. What about our graduate students, some of whom will be the providers making decisions about ‘incoming data’ from their patients own lifestyle monitors? And our nurse scientists, when the ‘data’ they need to answer their research questions are collected for them and housed in systems too large to manage on a laptop or even on some servers. In a “Call to Action” paper published in Nursing Outlook, Clancy et al. (2013) called for the profession’s engagement in big data science and provided a clear roadmap for educating all nurses and nurse leaders about how to advocate for valuing of nursing data and use of EHR standards that ensure a nursing voice is evident. At the 2016 Doctoral Education Conference Bonnie Westra (University of Minnesota), Patricia B. Brenner (University of Wisconsin) and Suzanne Bakken (Columbia University) enurse researchers who have been doing this work for yearsegave a series of excellent presentations that as a whole provided the audience with not only an overview of that philosophy, methods and
114
Nurs Outlook 64 (2016) 113e114
analytics but how this field is so highly relevant to nursing. They were each very clear that data science will not replace entirely the traditional methods nurse researchers engage in. However, they were also clear about how critical it is that we all concentrate on preparing nurse clinicians who understand how to use electronic medical records and how the knowledge produced from them guides their care and how it can be used to evaluate new models of care. They also emphasized how PhD and DNP program faculty must integrate these concepts, methods and analytics into our doctoral programs. There is no shortage of examples of how these methods can be used to improve care delivery and quality of treatment and care for patients in our systems. As I reflected back on the last 15 years it seems we as a profession were slow and methodical in our adoption of the field of informaticsewith only a select group of scholars and expert clinicians really engaged in preparing relatively small number of graduates (compared to other specialties). And while informatics is one solid foundation from which big data science evolved it is not the same thing as informatics. It doesn’t appear we have another 15 years to change our curriculaeyet if we don’t nurses in the near future will not have a voice, much less an active role in shaping health care. Knowledge development and translation science has once again moved very quickly. Leaders in academe and practice must think about how we can provide the resources for faculty and students to prepare themselves to understand, interpret, use and the new methods and findings from these studies. In addition to resources it would seem expectations for taking advantage of those resources for gaining additional knowledge and skills to enable this integration is very important. As our colleagues we conduct research with across our campuses embrace data science we must be ready to not just be ‘at the table’, but to be active participants in new initiatives to help shape insights from the volumes of information available to health care.
references
Brennan, P., & Bakken, S. (2015). Nursing needs big data and big data needs nursing. Journal of Nursing Scholarship, 47(5), 477e484. Clancy, T., Bowles, K., Gelinas, L., Androvitch, I., Delaney, C., Matney, S., ., Westra, B. (2013). A call to action: Engage in big data science. Nursing Outlook, 62(1), 62e64. National Institutes of Health. (2016). Retrived from http:// dtasciences.nih.gov/bd2k/about/what Westra, B., Bliss, D., Savik, K., Hou, Y., & Borchert, A. (2013). Effectiveness of wound, ostomy, and continence nurses on agency level wound and incontinence outcomes in home health care. Journal of Wound, Ostomy, and Continence Nursing, 40, 135e142.
Author Description Marion E. Broome is the Editor-in-Chief of Nursing Outlook. Marion E. Broome, PhD, RN, FAAN Dean and Vice Chancellor for Nursing Affairs Duke University School of Nursing Associate Vice President for Academic Affairs Duke University Health System School of Nursing Duke University Durham, NC Corresponding author: Marion E. Broome, Dean and Vice Chancellor for Nursing Affairs Duke University School of Nursing Associate Vice President for Academic Affairs Duke University Health System School of Nursing Duke University DUMC 3322, 307 Trent Dr., Durham, NC 27710. E-mail address: [email protected] 0029-6554/$ e see front matter Ó 2016 Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.outlook.2016.02.001