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Simulating future supply of and requirements for human resources for health in high-income OECD countries

Overview of attention for article published in Human Resources for Health, December 2016
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (83rd percentile)
  • Good Attention Score compared to outputs of the same age and source (79th percentile)

Mentioned by

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15 tweeters

Citations

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9 Dimensions

Readers on

mendeley
47 Mendeley
Title
Simulating future supply of and requirements for human resources for health in high-income OECD countries
Published in
Human Resources for Health, December 2016
DOI 10.1186/s12960-016-0168-x
Pubmed ID
Authors

Gail Tomblin Murphy, Stephen Birch, Adrian MacKenzie, Janet Rigby

Abstract

As part of efforts to inform the development of a global human resources for health (HRH) strategy, a comprehensive methodology for estimating HRH supply and requirements was described in a companion paper. The purpose of this paper is to demonstrate the application of that methodology, using data publicly available online, to simulate the supply of and requirements for midwives, nurses, and physicians in the 32 high-income member countries of the Organisation for Economic Co-operation and Development (OECD) up to 2030. A model combining a stock-and-flow approach to simulate the future supply of each profession in each country-adjusted according to levels of HRH participation and activity-and a needs-based approach to simulate future HRH requirements was used. Most of the data to populate the model were obtained from the OECD's online indicator database. Other data were obtained from targeted internet searches and documents gathered as part of the companion paper. Relevant recent measures for each model parameter were found for at least one of the included countries. In total, 35% of the desired current data elements were found; assumed values were used for the other current data elements. Multiple scenarios were used to demonstrate the sensitivity of the simulations to different assumed future values of model parameters. Depending on the assumed future values of each model parameter, the simulated HRH gaps across the included countries could range from shortfalls of 74 000 midwives, 3.2 million nurses, and 1.2 million physicians to surpluses of 67 000 midwives, 2.9 million nurses, and 1.0 million physicians by 2030. Despite important gaps in the data publicly available online and the short time available to implement it, this paper demonstrates the basic feasibility of a more comprehensive, population needs-based approach to estimating HRH supply and requirements than most of those currently being used. HRH planners in individual countries, working with their respective stakeholder groups, would have more direct access to data on the relevant planning parameters and would thus be in an even better position to implement such an approach.

Twitter Demographics

The data shown below were collected from the profiles of 15 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 47 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Indonesia 1 2%
Unknown 46 98%

Demographic breakdown

Readers by professional status Count As %
Researcher 9 19%
Student > Ph. D. Student 8 17%
Student > Master 6 13%
Other 5 11%
Lecturer 4 9%
Other 15 32%
Readers by discipline Count As %
Medicine and Dentistry 13 28%
Unspecified 10 21%
Nursing and Health Professions 10 21%
Engineering 4 9%
Social Sciences 3 6%
Other 7 15%

Attention Score in Context

This research output has an Altmetric Attention Score of 10. 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 07 March 2017.
All research outputs
#1,360,994
of 12,225,951 outputs
Outputs from Human Resources for Health
#186
of 652 outputs
Outputs of similar age
#55,654
of 334,969 outputs
Outputs of similar age from Human Resources for Health
#5
of 24 outputs
Altmetric has tracked 12,225,951 research outputs across all sources so far. Compared to these this one has done well and is in the 88th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 652 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.6. This one has gotten more attention than average, scoring higher than 71% of its peers.
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 334,969 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 83% of its contemporaries.
We're also able to compare this research output to 24 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 79% of its contemporaries.