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Variability of staffing and staff mix across acute care units in Alberta, Canada

Overview of attention for article published in Human Resources for Health, December 2016
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Title
Variability of staffing and staff mix across acute care units in Alberta, Canada
Published in
Human Resources for Health, December 2016
DOI 10.1186/s12960-016-0172-1
Pubmed ID
Authors

Krishna Sharma, Stephanie E. Hastings, Esther Suter, Judy Bloom

Abstract

The health workforce has a crucial position in healthcare, and effective distribution of the workforce is one of the critical areas for healthcare improvement. This requires a proper understanding of the allocation of healthcare providers including staffing levels and staffing variability within a healthcare system. High variability may imply significant differences in outcomes and greater opportunity to better distribute staffing and improve patient outcomes. The objective of this study was to examine staffing variation across acute care units in a large and integrated healthcare system. We used survey and administrative data on full time equivalencies of Registered Nurses, Licensed Practical Nurses, Health Care Aides, and allied health staff for 287 acute care units to examine staffing levels across multiple unit types. We used a subsample of 157 units in a more detailed analysis of staffing levels and staff distribution. Results from the full sample indicate that staffing levels, particularly for Registered Nurses, vary substantially across unit types. Subsample analyses showed that the highest variation in staffing levels occurred in rural units, which also had higher average staffing for licensed practical nurses and allied health staff. Rural units had fewer Health Care Aides than did other units. The majority of units were staffed with a combination of all three nursing providers, but the most common arrangement in rural units was staffing of Registered Nurses and Licensed Practical Nurses only. We also found that units with the highest number Registered Nurses also tended to have higher numbers of other staff, particularly allied health providers. We observed significant variation in staffing levels and mix in acute care units. Some of the differences might be attributable to differences in patient needs and unit types. However, we also observed high variability in units with similar services and patient populations. As other research has shown that staffing is linked to differences in patient outcomes, there is an important opportunity to improve staffing for greater efficiency and higher quality care.

X Demographics

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The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 51 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 51 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 13 25%
Student > Ph. D. Student 6 12%
Researcher 5 10%
Student > Bachelor 5 10%
Student > Doctoral Student 3 6%
Other 10 20%
Unknown 9 18%
Readers by discipline Count As %
Nursing and Health Professions 18 35%
Medicine and Dentistry 6 12%
Agricultural and Biological Sciences 3 6%
Arts and Humanities 2 4%
Business, Management and Accounting 2 4%
Other 8 16%
Unknown 12 24%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 06 December 2016.
All research outputs
#15,740,505
of 25,374,917 outputs
Outputs from Human Resources for Health
#1,040
of 1,261 outputs
Outputs of similar age
#231,320
of 416,453 outputs
Outputs of similar age from Human Resources for Health
#17
of 20 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. This one is in the 37th percentile – i.e., 37% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,261 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 13.3. This one is in the 15th percentile – i.e., 15% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 416,453 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 43rd percentile – i.e., 43% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 20 others from the same source and published within six weeks on either side of this one. This one is in the 5th percentile – i.e., 5% of its contemporaries scored the same or lower than it.