TY - JOUR
T1 - Measuring the availability of human resources for health and its relationship to universal health coverage for 204 countries and territories from 1990 to 2019
T2 - a systematic analysis for the Global Burden of Disease Study 2019
AU - GBD 2019 Human Resources for Health Collaborators
AU - Haakenstad, Annie
AU - Irvine, Caleb Mackay Salpeter
AU - Knight, Megan
AU - Bintz, Corinne
AU - Aravkin, Aleksandr Y.
AU - Zheng, Peng
AU - Gupta, Vin
AU - Abrigo, Michael R.M.
AU - Abushouk, Abdelrahman I.
AU - Adebayo, Oladimeji M.
AU - Agarwal, Gina
AU - Alahdab, Fares
AU - Al-Aly, Ziyad
AU - Alam, Khurshid
AU - Alanzi, Turki M.
AU - Alcalde-Rabanal, Jacqueline Elizabeth
AU - Alipour, Vahid
AU - Alvis-Guzman, Nelson
AU - Amit, Arianna Maever L.
AU - Andrei, Catalina Liliana
AU - Andrei, Tudorel
AU - Antonio, Carl Abelardo T.
AU - Arabloo, Jalal
AU - Aremu, Olatunde
AU - Ayanore, Martin Amogre
AU - Banach, Maciej
AU - Bärnighausen, Till Winfried
AU - Barthelemy, Celine M.
AU - Bayati, Mohsen
AU - Benzian, Habib
AU - Berman, Adam E.
AU - Bienhoff, Kelly
AU - Bijani, Ali
AU - Bikbov, Boris
AU - Biondi, Antonio
AU - Boloor, Archith
AU - Busse, Reinhard
AU - Butt, Zahid A.
AU - Cámera, Luis Alberto
AU - Campos-Nonato, Ismael R.
AU - Cárdenas, Rosario
AU - Carvalho, Felix
AU - Chansa, Collins
AU - Chattu, Soosanna Kumary
AU - Chattu, Vijay Kumar
AU - Chu, Dinh Toi
AU - Dai, Xiaochen
AU - Dandona, Lalit
AU - Dandona, Rakhi
AU - Dangel, William James
N1 - Funding Information:
T W Bärnighausen reports research grants from the European Union (Horizon 2020 and EIT Health), German Research Foundation (DFG), US National Institutes of Health, German Ministry of Education and Research, Alexander von Humboldt Foundation, Else-Kröner-Fresenius-Foundation, Wellcome Trust, Bill & Melinda Gates Foundation, KfW, The Joint United Nations Programme on HIV/AIDS (UNAIDS), and WHO; consulting fees from KfW for consultancy on the OSCAR initiative in Vietnam; participation on a data safety monitoring board or advisory board with the NIH-funded study “Healthy Options” (PIs: Smith Fawzi, Kaaya) as Chair, Data Safety and Monitoring Board (DSMB), German National Committee on the “Future of Public Health Research and Education”, Chair of the scientific advisory board to the EDCTP Evaluation, membership of the UNAIDS Evaluation Expert Advisory Committee, National Institutes of Health Study Section Member on Population and Public Health Approaches to HIV/AIDS (PPAH), US National Academies of Sciences, Engineering, and Medicine's Committee for the “Evaluation of Human Resources for Health in the Republic of Rwanda under the President's Emergency Plan for AIDS Relief (PEPFAR)”, University of Pennsylvania (UPenn) Population Aging Research Center (PARC) as an external advisory board member; and a leadership or fiduciary role in a board, society, committee, or advocacy group, paid or unpaid, with Global Health Hub Germany (which was initiated by the German Ministry of Health) as co-Chair; all outside the submitted work. B Bikbov reports grants from Lombardy Region, paid to the Istituto di Ricerche Farmacologiche Mario Negri IRCCS; support for attending meetings or travel, or both, from the European Commission; all outside the submitted work. N Fullman reports other funding support from WHO as a consultant from June to September, 2019, and Gates Ventures since 2020, all outside the submitted work. N J Henry reports grants or contracts from the Bill & Melinda Gates Foundation, outside the submitted work. S M S Islam reports grants or contracts from the National Health and Medical Research Council of Australia via the Emerging Leadership Fellowship, outside the submitted work. K Krishan reports other non-financial support from the UGC Centre of Advanced Study, CAS II, Department of Anthropology, Panjab University, Chandigarh, India, outside the submitted work. J L Leasher reports a leadership or fiduciary role in a board, society, committee, or advocacy group, paid or unpaid with Planning Group Member for the National Eye Health Education Program, outside the submitted work. V C F Pepito reports grants or contracts from Sanofi Consumer Healthcare received as payments to his institution to do research on self-care, and from the International Initiative for Impact Evaluation received as payments to his institution to conduct evaluations on PhilHealth; all outside the submitted work. D M Pigott reports grants from the Bill & Melinda Gates Foundation, outside the submitted work. All other authors declare no competing interests.
Funding Information:
This study was funded by the Bill & Melinda Gates Foundation. T W Bärnighausen was supported by the Alexander von Humboldt Foundation through the Alexander von Humboldt Professor award, funded by the German Federal Ministry of Education and Research. F Carvalho acknowledges support from FCT - Fundação para a Ciência e a Tecnologia, I.P., in the scope of the project UIDP/04378/2020 and UIDB/04378/2020 of the Research Unit on Applied Molecular Biosciences - UCIBIO and the project LA/P/0140/2020 of the Associate Laboratory Institute for Health and Bioeconomy - i4HB; FCT/MCTES (Ministério da Ciência, Tecnologia e Ensino Superior) through the project UIDB/50006/2020. A A Fomenkov acknowledges the research carried out within the state assignment of Ministry of Science and Higher Education of the Russian Federation (theme No. 121050500047-5). S M S Islam is funded by a NHMRC Emerging Leadership Fellowship. K Krishan acknowledges non-financial support from the UGC Centre of Advanced Study, CAS-II, Department of Anthropology, Panjab University, Chandigarh, India, outside the submitted work. D E Ndwandwe acknowledges support from Cochrane South Africa, South African Medical Research Council. A M Samy acknowledges support from Ain Shams University and the Egyptian Fulbright Mission Program. A Sheikh acknowledges support from Health Data Research UK. D A S Silva thanks CAPES, Brazil for supporting the Graduate Program of Physical Education at Federal University of Santa Catarina and CNPq, Brazil, for research support. S Ullah acknowledges support from the University of Agriculture, Faisalabad, Pakistan. B Unnikrishnan acknowledges support from Kasturba Medical College, Mangalore, Manipal Academy of Higher Education, Manipal. S B Zaman acknowledges receiving a scholarship from the Australian Government Research Training Program (RTP) in support of his academic career.
Publisher Copyright:
© 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license
PY - 2022/6/4
Y1 - 2022/6/4
N2 - Background: Human resources for health (HRH) include a range of occupations that aim to promote or improve human health. The UN Sustainable Development Goals (SDGs) and the WHO Health Workforce 2030 strategy have drawn attention to the importance of HRH for achieving policy priorities such as universal health coverage (UHC). Although previous research has found substantial global disparities in HRH, the absence of comparable cross-national estimates of existing workforces has hindered efforts to quantify workforce requirements to meet health system goals. We aimed to use comparable and standardised data sources to estimate HRH densities globally, and to examine the relationship between a subset of HRH cadres and UHC effective coverage performance. Methods: Through the International Labour Organization and Global Health Data Exchange databases, we identified 1404 country-years of data from labour force surveys and 69 country-years of census data, with detailed microdata on health-related employment. From the WHO National Health Workforce Accounts, we identified 2950 country-years of data. We mapped data from all occupational coding systems to the International Standard Classification of Occupations 1988 (ISCO-88), allowing for standardised estimation of densities for 16 categories of health workers across the full time series. Using data from 1990 to 2019 for 196 of 204 countries and territories, covering seven Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) super-regions and 21 regions, we applied spatiotemporal Gaussian process regression (ST-GPR) to model HRH densities from 1990 to 2019 for all countries and territories. We used stochastic frontier meta-regression to model the relationship between the UHC effective coverage index and densities for the four categories of health workers enumerated in SDG indicator 3.c.1 pertaining to HRH: physicians, nurses and midwives, dentistry personnel, and pharmaceutical personnel. We identified minimum workforce density thresholds required to meet a specified target of 80 out of 100 on the UHC effective coverage index, and quantified national shortages with respect to those minimum thresholds. Findings: We estimated that, in 2019, the world had 104·0 million (95% uncertainty interval 83·5–128·0) health workers, including 12·8 million (9·7–16·6) physicians, 29·8 million (23·3–37·7) nurses and midwives, 4·6 million (3·6–6·0) dentistry personnel, and 5·2 million (4·0–6·7) pharmaceutical personnel. We calculated a global physician density of 16·7 (12·6–21·6) per 10 000 population, and a nurse and midwife density of 38·6 (30·1–48·8) per 10 000 population. We found the GBD super-regions of sub-Saharan Africa, south Asia, and north Africa and the Middle East had the lowest HRH densities. To reach 80 out of 100 on the UHC effective coverage index, we estimated that, per 10 000 population, at least 20·7 physicians, 70·6 nurses and midwives, 8·2 dentistry personnel, and 9·4 pharmaceutical personnel would be needed. In total, the 2019 national health workforces fell short of these minimum thresholds by 6·4 million physicians, 30·6 million nurses and midwives, 3·3 million dentistry personnel, and 2·9 million pharmaceutical personnel. Interpretation: Considerable expansion of the world's health workforce is needed to achieve high levels of UHC effective coverage. The largest shortages are in low-income settings, highlighting the need for increased financing and coordination to train, employ, and retain human resources in the health sector. Actual HRH shortages might be larger than estimated because minimum thresholds for each cadre of health workers are benchmarked on health systems that most efficiently translate human resources into UHC attainment. Funding: Bill & Melinda Gates Foundation.
AB - Background: Human resources for health (HRH) include a range of occupations that aim to promote or improve human health. The UN Sustainable Development Goals (SDGs) and the WHO Health Workforce 2030 strategy have drawn attention to the importance of HRH for achieving policy priorities such as universal health coverage (UHC). Although previous research has found substantial global disparities in HRH, the absence of comparable cross-national estimates of existing workforces has hindered efforts to quantify workforce requirements to meet health system goals. We aimed to use comparable and standardised data sources to estimate HRH densities globally, and to examine the relationship between a subset of HRH cadres and UHC effective coverage performance. Methods: Through the International Labour Organization and Global Health Data Exchange databases, we identified 1404 country-years of data from labour force surveys and 69 country-years of census data, with detailed microdata on health-related employment. From the WHO National Health Workforce Accounts, we identified 2950 country-years of data. We mapped data from all occupational coding systems to the International Standard Classification of Occupations 1988 (ISCO-88), allowing for standardised estimation of densities for 16 categories of health workers across the full time series. Using data from 1990 to 2019 for 196 of 204 countries and territories, covering seven Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) super-regions and 21 regions, we applied spatiotemporal Gaussian process regression (ST-GPR) to model HRH densities from 1990 to 2019 for all countries and territories. We used stochastic frontier meta-regression to model the relationship between the UHC effective coverage index and densities for the four categories of health workers enumerated in SDG indicator 3.c.1 pertaining to HRH: physicians, nurses and midwives, dentistry personnel, and pharmaceutical personnel. We identified minimum workforce density thresholds required to meet a specified target of 80 out of 100 on the UHC effective coverage index, and quantified national shortages with respect to those minimum thresholds. Findings: We estimated that, in 2019, the world had 104·0 million (95% uncertainty interval 83·5–128·0) health workers, including 12·8 million (9·7–16·6) physicians, 29·8 million (23·3–37·7) nurses and midwives, 4·6 million (3·6–6·0) dentistry personnel, and 5·2 million (4·0–6·7) pharmaceutical personnel. We calculated a global physician density of 16·7 (12·6–21·6) per 10 000 population, and a nurse and midwife density of 38·6 (30·1–48·8) per 10 000 population. We found the GBD super-regions of sub-Saharan Africa, south Asia, and north Africa and the Middle East had the lowest HRH densities. To reach 80 out of 100 on the UHC effective coverage index, we estimated that, per 10 000 population, at least 20·7 physicians, 70·6 nurses and midwives, 8·2 dentistry personnel, and 9·4 pharmaceutical personnel would be needed. In total, the 2019 national health workforces fell short of these minimum thresholds by 6·4 million physicians, 30·6 million nurses and midwives, 3·3 million dentistry personnel, and 2·9 million pharmaceutical personnel. Interpretation: Considerable expansion of the world's health workforce is needed to achieve high levels of UHC effective coverage. The largest shortages are in low-income settings, highlighting the need for increased financing and coordination to train, employ, and retain human resources in the health sector. Actual HRH shortages might be larger than estimated because minimum thresholds for each cadre of health workers are benchmarked on health systems that most efficiently translate human resources into UHC attainment. Funding: Bill & Melinda Gates Foundation.
KW - Global Burden of Disease
KW - Global Health
KW - Humans
KW - Occupations
KW - Pharmaceutical Preparations
KW - Universal Health Insurance
KW - Workforce
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U2 - 10.1016/S0140-6736(22)00532-3
DO - 10.1016/S0140-6736(22)00532-3
M3 - Article
C2 - 35617980
AN - SCOPUS:85131397944
SN - 0140-6736
VL - 399
SP - 2129
EP - 2154
JO - The Lancet
JF - The Lancet
IS - 10341
ER -