Literature DB >> 27265947

Nursing Management Minimum Data Set: Cost-Effective Tool To Demonstrate the Value of Nurse Staffing in the Big Data Science Era.

Lisiane Pruinelli, Connie W Delaney, Amy Garciannie, Barbara Caspers, Bonnie L Westra.   

Abstract

There is a growing body of evidence of the relationship of nurse staffing to patient, nurse, and financial outcomes. With the advent of big data science and developing big data analytics in nursing, data science with the reuse of big data is emerging as a timely and cost-effective approach to demonstrate nursing value. The Nursing Management Minimum Date Set (NMMDS) provides standard administrative data elements, definitions, and codes to measure the context where care is delivered and, consequently, the value of nursing. The integration of the NMMDS elements in the current health system provides evidence for nursing leaders to measure and manage decisions, leading to better patient, staffing, and financial outcomes. It also enables the reuse of data for clinical scholarship and research.

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Year:  2016        PMID: 27265947

Source DB:  PubMed          Journal:  Nurs Econ        ISSN: 0746-1739            Impact factor:   1.085


  4 in total

1.  Secondary use of standardized nursing care data for advancing nursing science and practice: a systematic review.

Authors:  Tamara G R Macieira; Tania C M Chianca; Madison B Smith; Yingwei Yao; Jiang Bian; Diana J Wilkie; Karen Dunn Lopez; Gail M Keenan
Journal:  J Am Med Inform Assoc       Date:  2019-11-01       Impact factor: 4.497

2.  Evidence of Progress in Making Nursing Practice Visible Using Standardized Nursing Data: a Systematic Review.

Authors:  Tamara G R Macieira; Madison B Smith; Nicolle Davis; Yingwei Yao; Diana J Wilkie; Karen Dunn Lopez; Gail Keenan
Journal:  AMIA Annu Symp Proc       Date:  2018-04-16

3.  Reducing Emergency Room Visits and In-Hospitalizations by Implementing Best Practice for Transitional Care Using Innovative Technology and Big Data.

Authors:  Sharon Hewner; Suzanne S Sullivan; Guan Yu
Journal:  Worldviews Evid Based Nurs       Date:  2018-03-23       Impact factor: 2.931

4.  Artificial intelligence in nursing: Priorities and opportunities from an international invitational think-tank of the Nursing and Artificial Intelligence Leadership Collaborative.

Authors:  Charlene Esteban Ronquillo; Laura-Maria Peltonen; Lisiane Pruinelli; Charlene H Chu; Suzanne Bakken; Ana Beduschi; Kenrick Cato; Nicholas Hardiker; Alain Junger; Martin Michalowski; Rune Nyrup; Samira Rahimi; Donald Nigel Reed; Tapio Salakoski; Sanna Salanterä; Nancy Walton; Patrick Weber; Thomas Wiegand; Maxim Topaz
Journal:  J Adv Nurs       Date:  2021-05-18       Impact factor: 3.057

  4 in total

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