Document Detail


Staffing matters-every shift: data from the Military Nursing Outcomes Database can be used to demonstrate that the right number and mix of nurses prevent errors.
MedLine Citation:
PMID:  23154676     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
Data from the Military Nursing Outcomes Database (MilNOD) project demonstrate that inadequately staffed shifts can increase the likelihood of adverse events, such as falls with injury, medication errors, and needlestick injuries to nurses. Such evidence can be used to show that it takes not only the right number of nursing staff on every shift to ensure safe patient care, but also the right mix of expertise and experience. Based on findings from the MilNOD project, the authors present realistic scenarios of common dilemmas hospitals face in nurse staffing, illustrating the potential hazards for patients and nurses alike.
Authors:
Gordon West; Patricia A Patrician; Lori Loan
Related Documents :
17102276 - Perceptions of impact of electronic health records on nurses' work.
20485206 - Is it time to pull the plug on 12-hour shifts?: part 1. the evidence.
15228866 - Career satisfaction among female nurses.
10197006 - Factors in job satisfaction of the psychiatric clinical nurse specialist.
11183976 - A ceo roundtable on making mergers succeed.
8509976 - Negotiating nurse-patient authority in pediatric home health care.
Publication Detail:
Type:  Journal Article    
Journal Detail:
Title:  The American journal of nursing     Volume:  112     ISSN:  1538-7488     ISO Abbreviation:  Am J Nurs     Publication Date:  2012 Dec 
Date Detail:
Created Date:  2012-11-29     Completed Date:  2013-02-04     Revised Date:  2013-05-20    
Medline Journal Info:
Nlm Unique ID:  0372646     Medline TA:  Am J Nurs     Country:  United States    
Other Details:
Languages:  eng     Pagination:  22-7; discussion 28     Citation Subset:  AIM; IM; N    
Affiliation:
Uniformed Services University of the Health Sciences USUHS, Graduate School of Nursing, Bethesda, MD, USA. gordon.west@us.army.mil
Export Citation:
APA/MLA Format     Download EndNote     Download BibTex
MeSH Terms
Descriptor/Qualifier:
Accidental Falls / prevention & control*
Hospitals, Military / manpower
Humans
Medication Errors / prevention & control*
Military Nursing / statistics & numerical data
Models, Statistical
Needlestick Injuries / prevention & control*
Nursing Staff, Hospital / supply & distribution*
Personnel Staffing and Scheduling*
Quality of Health Care*
United States
Workload

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


Previous Document:  Creating a bio-hybrid signal transduction pathway: opening a new channel of communication between ce...
Next Document:  Missing incidents in community-dwelling people with dementia: understanding how these dangerous even...