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Regional health workforce monitoring as governance innovation: a German model to coordinate sectoral demand, skill mix and mobility

Overview of attention for article published in Human Resources for Health, November 2016
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  • Good Attention Score compared to outputs of the same age (74th percentile)
  • Average Attention Score compared to outputs of the same age and source

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1 policy source
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76 Mendeley
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Title
Regional health workforce monitoring as governance innovation: a German model to coordinate sectoral demand, skill mix and mobility
Published in
Human Resources for Health, November 2016
DOI 10.1186/s12960-016-0170-3
Pubmed ID
Authors

E. Kuhlmann, O. Lauxen, C. Larsen

Abstract

As health workforce policy is gaining momentum, data sources and monitoring systems have significantly improved in the European Union and internationally. Yet data remain poorly connected to policy-making and implementation and often do not adequately support integrated approaches. This brings the importance of governance and the need for innovation into play. The present case study introduces a regional health workforce monitor in the German Federal State of Rhineland-Palatinate and seeks to explore the capacity of monitoring to innovate health workforce governance. The monitor applies an approach from the European Network on Regional Labour Market Monitoring to the health workforce. The novel aspect of this model is an integrated, procedural approach that promotes a 'learning system' of governance based on three interconnected pillars: mixed methods and bottom-up data collection, strong stakeholder involvement with complex communication tools and shared decision- and policy-making. Selected empirical examples illustrate the approach and the tools focusing on two aspects: the connection between sectoral, occupational and mobility data to analyse skill/qualification mixes and the supply-demand matches and the connection between monitoring and stakeholder-driven policy. Regional health workforce monitoring can promote effective governance in high-income countries like Germany with overall high density of health workers but maldistribution of staff and skills. The regional stakeholder networks are cost-effective and easily accessible and might therefore be appealing also to low- and middle-income countries.

X Demographics

X Demographics

The data shown below were collected from the profiles of 5 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 76 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 76 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 12 16%
Student > Master 10 13%
Student > Ph. D. Student 10 13%
Student > Doctoral Student 9 12%
Student > Bachelor 3 4%
Other 12 16%
Unknown 20 26%
Readers by discipline Count As %
Social Sciences 11 14%
Medicine and Dentistry 9 12%
Nursing and Health Professions 9 12%
Business, Management and Accounting 7 9%
Computer Science 4 5%
Other 14 18%
Unknown 22 29%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 6. 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 29 September 2022.
All research outputs
#6,496,106
of 25,374,647 outputs
Outputs from Human Resources for Health
#686
of 1,261 outputs
Outputs of similar age
#106,936
of 417,109 outputs
Outputs of similar age from Human Resources for Health
#12
of 20 outputs
Altmetric has tracked 25,374,647 research outputs across all sources so far. This one has received more attention than most of these and is in the 74th percentile.
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 45th percentile – i.e., 45% 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 417,109 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 74% of its contemporaries.
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 35th percentile – i.e., 35% of its contemporaries scored the same or lower than it.