Health workforce metrics pre- and post-2015: a stimulus to public policy and planning
Identifieur interne : 000198 ( Pmc/Checkpoint ); précédent : 000197; suivant : 000199Health workforce metrics pre- and post-2015: a stimulus to public policy and planning
Auteurs : Francisco Pozo-Martin [Espagne] ; Andrea Nove [Espagne] ; Sofia Castro Lopes [Espagne] ; James Campbell [Suisse] ; James Buchan [Australie] ; Gilles Dussault [Portugal] ; Teena Kunjumen [Suisse] ; Giorgio Cometto [Suisse] ; Amani Siyam [Suisse]Source :
- Human Resources for Health [ 1478-4491 ] ; 2017.
Abstract
Evidence-based health workforce policies are essential to ensure the provision of high-quality health services and to support the attainment of universal health coverage (UHC). This paper describes the main characteristics of available health workforce data for 74 of the 75 countries identified under the ‘Countdown to 2015’ initiative as accounting for more than 95% of the world’s maternal, newborn and child deaths. It also discusses best practices in the development of health workforce metrics post-2015.
Using available health workforce data from the Global Health Workforce Statistics database from the Global Health Observatory, we generated descriptive statistics to explore the current status, recent trends in the number of skilled health professionals (SHPs: physicians, nurses, midwives) per 10 000 population, and future requirements to achieve adequate levels of health care in the 74 countries. A rapid literature review was conducted to obtain an overview of the types of methods and the types of data sources used in human resources for health (HRH) studies.
There are large intercountry and interregional differences in the density of SHPs to progress towards UHC in Countdown countries: a median of 10.2 per 10 000 population with range 1.6 to 142 per 10 000. Substantial efforts have been made in some countries to increase the availability of SHPs as shown by a positive average exponential growth rate (AEGR) in SHPs in 51% of Countdown countries for which there are data. Many of these countries will require large investments to achieve levels of workforce availability commensurate with UHC and the health-related sustainable development goals (SDGs). The availability, quality and comparability of global health workforce metrics remain limited. Most published workforce studies are descriptive, but more sophisticated needs-based workforce planning methods are being developed.
There is a need for high-quality, comprehensive, interoperable sources of HRH data to support all policies towards UHC and the health-related SDGs. The recent WHO-led initiative of supporting countries in the development of National Health Workforce Accounts is a very promising move towards purposive health workforce metrics post-2015. Such data will allow more countries to apply the latest methods for health workforce planning.
The online version of this article (doi:10.1186/s12960-017-0190-7) contains supplementary material, which is available to authorized users.
Url:
DOI: 10.1186/s12960-017-0190-7
PubMed: 28202047
PubMed Central: 5312527
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institution-id-type="GRID">grid.3575.4</institution-id><institution></institution><institution>Global Health Workforce Network, WHO Headquarters,</institution></institution-wrap>Geneva, Switzerland</nlm:aff><country xml:lang="fr">Suisse</country><wicri:regionArea>Geneva</wicri:regionArea></affiliation></author><author><name sortKey="Siyam, Amani" sort="Siyam, Amani" uniqKey="Siyam A" first="Amani" last="Siyam">Amani Siyam</name><affiliation wicri:level="1"><nlm:aff id="Aff2"><institution-wrap><institution-id institution-id-type="ISNI">0000000121633745</institution-id><institution-id institution-id-type="GRID">grid.3575.4</institution-id><institution></institution><institution>Health Systems and Innovations, WHO Headquarters,</institution></institution-wrap>Geneva, Switzerland</nlm:aff><country xml:lang="fr">Suisse</country><wicri:regionArea>Geneva</wicri:regionArea></affiliation></author></analytic><series><title level="j">Human Resources for Health</title><idno type="eISSN">1478-4491</idno><imprint><date when="2017">2017</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><sec><title>Background</title><p>Evidence-based health workforce policies are essential to ensure the provision of high-quality health services and to support the attainment of universal health coverage (UHC). This paper describes the main characteristics of available health workforce data for 74 of the 75 countries identified under the ‘Countdown to 2015’ initiative as accounting for more than 95% of the world’s maternal, newborn and child deaths. It also discusses best practices in the development of health workforce metrics post-2015.</p></sec><sec><title>Methods</title><p>Using available health workforce data from the Global Health Workforce Statistics database from the Global Health Observatory, we generated descriptive statistics to explore the current status, recent trends in the number of skilled health professionals (SHPs: physicians, nurses, midwives) per 10 000 population, and future requirements to achieve adequate levels of health care in the 74 countries. A rapid literature review was conducted to obtain an overview of the types of methods and the types of data sources used in human resources for health (HRH) studies.</p></sec><sec><title>Results</title><p>There are large intercountry and interregional differences in the density of SHPs to progress towards UHC in Countdown countries: a median of 10.2 per 10 000 population with range 1.6 to 142 per 10 000. Substantial efforts have been made in some countries to increase the availability of SHPs as shown by a positive average exponential growth rate (AEGR) in SHPs in 51% of Countdown countries for which there are data. Many of these countries will require large investments to achieve levels of workforce availability commensurate with UHC and the health-related sustainable development goals (SDGs). The availability, quality and comparability of global health workforce metrics remain limited. Most published workforce studies are descriptive, but more sophisticated needs-based workforce planning methods are being developed.</p></sec><sec><title>Conclusions</title><p>There is a need for high-quality, comprehensive, interoperable sources of HRH data to support all policies towards UHC and the health-related SDGs. The recent WHO-led initiative of supporting countries in the development of National Health Workforce Accounts is a very promising move towards purposive health workforce metrics post-2015. Such data will allow more countries to apply the latest methods for health workforce planning.</p></sec><sec><title>Electronic supplementary material</title><p>The online version of this article (doi:10.1186/s12960-017-0190-7) contains supplementary material, which is available to authorized users.</p></sec></div></front><back><div1 type="bibliography"><listBibl><biblStruct><analytic><author><name sortKey="Campbell, J" uniqKey="Campbell J">J Campbell</name></author><author><name sortKey="Dussault, G" uniqKey="Dussault G">G Dussault</name></author><author><name sortKey="Buchan, J" uniqKey="Buchan J">J Buchan</name></author><author><name sortKey="Pozo Martin, F" uniqKey="Pozo Martin F">F Pozo-Martin</name></author><author><name sortKey="Guerra Arias, M" uniqKey="Guerra Arias M">M Guerra Arias</name></author><author><name sortKey="Leone, C" uniqKey="Leone C">C 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<front><journal-meta><journal-id journal-id-type="nlm-ta">Hum Resour Health</journal-id><journal-id journal-id-type="iso-abbrev">Hum Resour Health</journal-id><journal-title-group><journal-title>Human Resources for Health</journal-title></journal-title-group><issn pub-type="epub">1478-4491</issn><publisher><publisher-name>BioMed Central</publisher-name><publisher-loc>London</publisher-loc></publisher></journal-meta><article-meta><article-id pub-id-type="pmid">28202047</article-id><article-id pub-id-type="pmc">5312527</article-id><article-id pub-id-type="publisher-id">190</article-id><article-id pub-id-type="doi">10.1186/s12960-017-0190-7</article-id><article-categories><subj-group subj-group-type="heading"><subject>Research</subject></subj-group></article-categories><title-group><article-title>Health workforce metrics pre- and post-2015: a stimulus to public policy and planning</article-title></title-group><contrib-group><contrib contrib-type="author"><name><surname>Pozo-Martin</surname><given-names>Francisco</given-names></name><xref ref-type="aff" rid="Aff1">1</xref></contrib><contrib contrib-type="author" corresp="yes"><name><surname>Nove</surname><given-names>Andrea</given-names></name><address><phone>+44 7894 261229</phone><email>andrea.nove@icsintegrare.org</email></address><xref ref-type="aff" rid="Aff1">1</xref></contrib><contrib contrib-type="author"><name><surname>Lopes</surname><given-names>Sofia Castro</given-names></name><xref ref-type="aff" rid="Aff1">1</xref></contrib><contrib contrib-type="author"><name><surname>Campbell</surname><given-names>James</given-names></name><xref ref-type="aff" rid="Aff2">2</xref><xref ref-type="aff" rid="Aff3">3</xref></contrib><contrib contrib-type="author"><name><surname>Buchan</surname><given-names>James</given-names></name><xref ref-type="aff" rid="Aff4">4</xref></contrib><contrib contrib-type="author"><name><surname>Dussault</surname><given-names>Gilles</given-names></name><xref ref-type="aff" rid="Aff5">5</xref></contrib><contrib contrib-type="author"><name><surname>Kunjumen</surname><given-names>Teena</given-names></name><xref ref-type="aff" rid="Aff2">2</xref></contrib><contrib contrib-type="author"><name><surname>Cometto</surname><given-names>Giorgio</given-names></name><xref ref-type="aff" rid="Aff3">3</xref></contrib><contrib contrib-type="author"><name><surname>Siyam</surname><given-names>Amani</given-names></name><xref ref-type="aff" rid="Aff2">2</xref></contrib><aff id="Aff1"><label>1</label>Instituto de Cooperación Social Integrare, calle Balmes 30, 3-1, 08007 Barcelona, Spain</aff><aff id="Aff2"><label>2</label><institution-wrap><institution-id institution-id-type="ISNI">0000000121633745</institution-id><institution-id institution-id-type="GRID">grid.3575.4</institution-id><institution></institution><institution>Health Systems and Innovations, WHO Headquarters,</institution></institution-wrap>Geneva, Switzerland</aff><aff id="Aff3"><label>3</label><institution-wrap><institution-id institution-id-type="ISNI">0000000121633745</institution-id><institution-id institution-id-type="GRID">grid.3575.4</institution-id><institution></institution><institution>Global Health Workforce Network, WHO Headquarters,</institution></institution-wrap>Geneva, Switzerland</aff><aff id="Aff4"><label>4</label><institution-wrap><institution-id institution-id-type="ISNI">0000 0004 1936 7611</institution-id><institution-id institution-id-type="GRID">grid.117476.2</institution-id><institution>School of Nursing Midwifery and Health,</institution><institution>University of Technology Sydney,</institution></institution-wrap>Sydney, Australia</aff><aff id="Aff5"><label>5</label><institution-wrap><institution-id institution-id-type="ISNI">0000000121511713</institution-id><institution-id institution-id-type="GRID">grid.10772.33</institution-id><institution>Global Health and Tropical Medicine, Instituto de Higiene e Medicina Tropical,</institution><institution>Universidade Nova de Lisboa,</institution></institution-wrap>Lisbon, Portugal</aff></contrib-group><pub-date pub-type="epub"><day>15</day><month>2</month><year>2017</year></pub-date><pub-date pub-type="pmc-release"><day>15</day><month>2</month><year>2017</year></pub-date><pub-date pub-type="collection"><year>2017</year></pub-date><volume>15</volume><elocation-id>14</elocation-id><history><date date-type="received"><day>12</day><month>2</month><year>2016</year></date><date date-type="accepted"><day>9</day><month>2</month><year>2017</year></date></history><permissions><copyright-statement>© The Author(s). 2017</copyright-statement><license license-type="OpenAccess"><license-p><bold>Open Access</bold>This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (<ext-link ext-link-type="uri" xlink:href="http://creativecommons.org/licenses/by/4.0/">http://creativecommons.org/licenses/by/4.0/</ext-link>), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (<ext-link ext-link-type="uri" xlink:href="http://creativecommons.org/publicdomain/zero/1.0/">http://creativecommons.org/publicdomain/zero/1.0/</ext-link>) applies to the data made available in this article, unless otherwise stated.</license-p></license></permissions><abstract id="Abs1"><sec><title>Background</title><p>Evidence-based health workforce policies are essential to ensure the provision of high-quality health services and to support the attainment of universal health coverage (UHC). This paper describes the main characteristics of available health workforce data for 74 of the 75 countries identified under the ‘Countdown to 2015’ initiative as accounting for more than 95% of the world’s maternal, newborn and child deaths. It also discusses best practices in the development of health workforce metrics post-2015.</p></sec><sec><title>Methods</title><p>Using available health workforce data from the Global Health Workforce Statistics database from the Global Health Observatory, we generated descriptive statistics to explore the current status, recent trends in the number of skilled health professionals (SHPs: physicians, nurses, midwives) per 10 000 population, and future requirements to achieve adequate levels of health care in the 74 countries. A rapid literature review was conducted to obtain an overview of the types of methods and the types of data sources used in human resources for health (HRH) studies.</p></sec><sec><title>Results</title><p>There are large intercountry and interregional differences in the density of SHPs to progress towards UHC in Countdown countries: a median of 10.2 per 10 000 population with range 1.6 to 142 per 10 000. Substantial efforts have been made in some countries to increase the availability of SHPs as shown by a positive average exponential growth rate (AEGR) in SHPs in 51% of Countdown countries for which there are data. Many of these countries will require large investments to achieve levels of workforce availability commensurate with UHC and the health-related sustainable development goals (SDGs). The availability, quality and comparability of global health workforce metrics remain limited. Most published workforce studies are descriptive, but more sophisticated needs-based workforce planning methods are being developed.</p></sec><sec><title>Conclusions</title><p>There is a need for high-quality, comprehensive, interoperable sources of HRH data to support all policies towards UHC and the health-related SDGs. The recent WHO-led initiative of supporting countries in the development of National Health Workforce Accounts is a very promising move towards purposive health workforce metrics post-2015. Such data will allow more countries to apply the latest methods for health workforce planning.</p></sec><sec><title>Electronic supplementary material</title><p>The online version of this article (doi:10.1186/s12960-017-0190-7) contains supplementary material, which is available to authorized users.</p></sec></abstract><kwd-group xml:lang="en"><title>Keywords</title><kwd>Health workforce</kwd><kwd>Health systems</kwd><kwd>Metrics</kwd><kwd>Countdown</kwd><kwd>Data</kwd><kwd>Densities</kwd><kwd>Low- and middle-income countries</kwd><kwd>Universal health coverage</kwd><kwd>Sustainable development goals</kwd></kwd-group><funding-group><award-group><funding-source><institution>U.S. Fund for UNICEF</institution></funding-source><award-id>Countdown to 2015 for Maternal, Newborn and Child Survival Grant from the Bill and Melinda Gates Foundation</award-id></award-group></funding-group><custom-meta-group><custom-meta><meta-name>issue-copyright-statement</meta-name><meta-value>© The Author(s) 2017</meta-value></custom-meta></custom-meta-group></article-meta></front></pmc><affiliations><list><country><li>Australie</li><li>Espagne</li><li>Portugal</li><li>Suisse</li></country><region><li>Catalogne</li></region></list><tree><country name="Espagne"><region name="Catalogne"><name sortKey="Pozo Martin, Francisco" sort="Pozo Martin, Francisco" uniqKey="Pozo Martin F" first="Francisco" last="Pozo-Martin">Francisco Pozo-Martin</name></region><name sortKey="Lopes, Sofia Castro" sort="Lopes, Sofia Castro" uniqKey="Lopes S" first="Sofia Castro" last="Lopes">Sofia Castro Lopes</name><name sortKey="Nove, Andrea" sort="Nove, Andrea" uniqKey="Nove A" first="Andrea" last="Nove">Andrea Nove</name></country><country name="Suisse"><noRegion><name sortKey="Campbell, James" sort="Campbell, James" uniqKey="Campbell J" first="James" last="Campbell">James Campbell</name></noRegion><name sortKey="Campbell, James" sort="Campbell, James" uniqKey="Campbell J" first="James" last="Campbell">James Campbell</name><name sortKey="Cometto, Giorgio" sort="Cometto, Giorgio" uniqKey="Cometto G" first="Giorgio" last="Cometto">Giorgio Cometto</name><name sortKey="Kunjumen, Teena" sort="Kunjumen, Teena" uniqKey="Kunjumen T" first="Teena" last="Kunjumen">Teena Kunjumen</name><name sortKey="Siyam, Amani" sort="Siyam, Amani" uniqKey="Siyam A" first="Amani" last="Siyam">Amani Siyam</name></country><country name="Australie"><noRegion><name sortKey="Buchan, James" sort="Buchan, James" uniqKey="Buchan J" first="James" last="Buchan">James Buchan</name></noRegion></country><country name="Portugal"><noRegion><name sortKey="Dussault, Gilles" sort="Dussault, Gilles" uniqKey="Dussault G" first="Gilles" last="Dussault">Gilles Dussault</name></noRegion></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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