A plea to nurse educators: Incorporate big data use as a foundational skill for undergraduate and graduate nurses

The Arcus Experience: Bridging the Data Science Gap for Nurse Researchers

BACKGROUND

For years, nurse researchers have been called upon to engage with "big data" in the electronic health record (EHR) by leading studies focusing on nurse-centric patient outcomes and providing clinical analysis of potential outcome indicators. However, the current gap in nurses' data science education and training poses a significant barrier.

OBJECTIVES

We aimed to evaluate the viability of conducting nurse-led, big-data research projects within a custom-designed computational laboratory and examine the support required by a team of researchers with little to no big-data experience.

METHODS

Four nurse-led research teams developed a research question reliant on existing EHR data. Each team was given its own virtual computational laboratory populated with raw data. A data science education team provided instruction in coding languages-primarily structured query language and R-and data science techniques to organize and analyze the data.

RESULTS

Three research teams have completed studies, resulting in one manuscript currently undergoing peer review and two manuscripts in progress. The final team is performing data analysis. Five barriers and five facilitators to big-data projects were identified.

DISCUSSION

As the data science learning curve is steep, organizations need to help bridge the gap between what is currently taught in doctoral nursing programs and what is required of clinical nurse researchers to successfully engage in big-data methods. In addition, clinical nurse researchers require protected research time and a data science infrastructure that supports novice efforts with education, mentorship, and computational laboratory resources.

Prevalence of Telehealth in Nursing: Implications for Regulation and Education in the Era of Value-Based Care

Value-based care theoretically catalyzes the business case for telehealth. Hence, the purpose of this study was to define the proportion of a statewide nursing workforce who self-reported telehealth or telephonic nursing as their primary work setting in a U.S. state undergoing rapid transitions to value-based care. We conducted a secondary analysis of a 2017 statewide nurse relicensure survey (n = 10,851), overall response rate 99%. The focus of the analysis was registered nurses who reported that they were currently working in Vermont or serving residents of the state (n = 8,457). Analysis was limited to descriptive statistics. We found that 18.4% of respondents (n = 1,556) reported their employment status as "telehealth/ working as a telephonic nurse." Responding to a different question, 17.2% (n = 1,458) defined "telehealth/telephonic" as their primary work setting. Thus, nearly one fifth of nurses practicing in the state were employed in telehealth, a role for which there is scant preparation in nursing education. The multistate practice of roughly one third of these nurses highlights the importance of the Enhanced Nurse Licensure Compact and raises questions about global telenurse practice. Taken as a whole, these findings have profound implications for health care policy development and implementation, ongoing workforce development and analyses, nursing regulation, education, and continuing education. New and renewed skills are needed to provide safe, effective, culturally relevant telehealth, and virtual care.