دورية أكاديمية
Arcus Experience: Bridging the Data Science Gap for Nurse Researchers.
العنوان: | Arcus Experience: Bridging the Data Science Gap for Nurse Researchers. |
---|---|
المؤلفون: | Flood EL; Children's Hospital of Philadelphia, Philadelphia, PA., Schweig L, Froh EB, Frankenberger WD, Lebet RM, Chen-Lim ML, Payton KJ, McCabe MA |
المصدر: | Nursing research [Nurs Res] 2024 May 10. Date of Electronic Publication: 2024 May 10. |
Publication Model: | Ahead of Print |
نوع المنشور: | Journal Article |
اللغة: | English |
بيانات الدورية: | Publisher: Lippincott-Ravn Publisher Country of Publication: United States NLM ID: 0376404 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1538-9847 (Electronic) Linking ISSN: 00296562 NLM ISO Abbreviation: Nurs Res Subsets: MEDLINE |
أسماء مطبوعة: | Publication: <1998- >: Hagerstown, MD : Lippincott-Ravn Publisher Original Publication: New York, American Journal of Nursing Co. |
مستخلص: | 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 pose a significant barrier. Objectives: We aimed to evaluate the viability of conducting nurse-led, big-data research projects within a custom-designed computational lab 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 lab 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. Four barriers and four 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. Additionally, clinical nurse researchers require protected research time and a data science infrastructure that supports novice efforts with education, mentorship, and computational lab resources. Competing Interests: The authors have no conflicts of interest to report. (Copyright © 2024 Wolters Kluwer Health, Inc. All rights reserved.) |
تواريخ الأحداث: | Date Created: 20240522 Latest Revision: 20240522 |
رمز التحديث: | 20240522 |
DOI: | 10.1097/NNR.0000000000000748 |
PMID: | 38773838 |
قاعدة البيانات: | MEDLINE |
تدمد: | 1538-9847 |
---|---|
DOI: | 10.1097/NNR.0000000000000748 |