Haakenstad, Annie, Irvine, Caleb Mackay Salpeter, Knight, Megan, Bintz, Corinne, Aravkin, Aleksandr Y., Zheng, Peng, Gupta, Vin, Abrigo, Michael R.M., Abushouk, Abdelrahman I., Adebayo, Oladimeji M., Agarwal, Gina, Alahdab, Fares, Al-Aly, Ziyad, Alam, Khurshid, Alanzi, Turki M., Alcalde-Rabanal, Jacqueline Elizabeth, Alipour, Vahid, Alvis-Guzman, Nelson, Amit, Arianna Maever L., Andrei, Catalina Liliana, Andrei, Tudorel, Antonio, Carl Abelardo T., Arabloo, Jalal, Aremu, Olatunde, Ayanore, Martin Amogre, Banach, Maciej, Barnighausen, Till Winfried, Barthelemy, Celine M., Bayati, Mohsen, Benzian, Habib, Berman, Adam E., Bienhoff, Kelly, Bijani, Ali, Bikbov, Boris, Biondi, Antonio, Boloor, Archith, Busse, Reinhard, Butt, Zahid A., Camera, Luis Alberto, Campos-Nonato, Ismael R., Cardenas, Rosario, Carvalho, Felix, Chansa, Collins, Chattu, Soosanna Kumary, Chattu, Vijay Kumar, Chu, Dinh-Toi, Dai, Xiaochen, Dandona, Lalit, Dandona, Rakhi, Dangel, William James, Daryani, Ahmad, De Neve, Jan-Walter, Dhimal, Meghnath, Dipeolu, Isaac Oluwafemi, Djalalinia, Shirin, Do, Hoa Thi, Doshi, Chirag P., Doshmangir, Leila, Ehsani-Chimeh, Elham, El Tantawi, Maha, Fernandes, Eduarda, Fischer, Florian, Foigt, Nataliya A., Fomenkov, Artem Alekseevich, Foroutan, Masoud, Fukumoto, Takeshi, Fullman, Nancy, Gad, Mohamed M., Ghadiri, Keyghobad, Ghafourifard, Mansour, Ghashghaee, Ahmad, Glucksman, Thomas, Goudarzi, Houman, Das Gupta, Rajat, Hamadeh, Randah R., Hamidi, Samer, Haro, Josep Maria, Hasanpoor, Edris, Hay, Simon I., Hegazy, Mohamed I., Heibati, Behzad, Henry, Nathaniel J., Hole, Michael K., Hossain, Naznin, Househ, Mowafa, Ilesanmi, Olayinka Stephen, Imani-Nasab, Mohammad-Hasan, Irvani, Seyed Sina Naghibi, Islam, Sheikh Mohammed Shariful, Jahani, Mohammad Ali, Joshi, Ankur, Kalhor, Rohollah, Kayode, Gbenga A., Khalid, Nauman, Khatab, Khaled, Kisa, Adnan, Kochhar, Sonali, Krishan, Kewal, Defo, Barthelemy Kuate, Lal, Dharmesh Kumar, Lami, Faris Hasan, Larsson, Anders O., Leasher, Janet L., LeGrand, Kate E., Lim, Lee-Ling, Mahotra, Narayan B., Majeed, Azeem, Maleki, Afshin, Manjunatha, Narayana, Massenburg, Benjamin Ballard, Mestrovic, Tomislav, Mini, G.K., Mirica, Andreea, Mirrakhimov, Erkin M., Mohammad, Yousef, Mohammed, Shafiu, Mokdad, Ali H., Morrison, Shane Douglas, Naghavi, Mohsen, Ndwandwe, Duduzile Edith, Negoi, Ionut, Negoi, Ruxandra Irina, Ngunjiri, Josephine W., Nguyen, Cuong Tat, Nigatu, Yeshambel T., Onwujekwe, Obinna E., Ortega-Altamirano, Doris V., Otstavnov, Nikita, Otstavnov, Stanislav S., Owolabi, Mayowa O., Pakhare, Abhijit P., Pepito, Veincent Christian Filipino, Perico, Norberto, Pham, Hai Quang, Pigott, David M., Pokhrel, Khem Narayan, Rabiee, Mohammad, Rabiee, Navid, Rahimi-Movaghar, Vafa, Rawaf, David Laith, Rawaf, Salman, Rawal, Lal, Remuzzi, Giuseppe, Renzaho, Andre M. N., Resnikoff, Serge, Rezaei, Nima, Rezapour, Aziz, Rickard, Jennifer, Roever, Leonardo, Sahu, Maitreyi, Samy, Abdallah M., Sanabria, Juan, Santric-Milicevic, Milena M., Saraswathy, Sivan Yegnanarayana Iyer, Seedat, Soraya, Senthilkumaran, Subramanian, Servan-Mori, Edson, Shaikh, Masood Ali, Sheikh, Aziz, Silva, Diego Augusto Santos, Stein, Caroline, Stein, Dan J., Titova, Mariya Vladimirovna, Topp, Stephanie M., Tovani-Palone, Marcos Roberto, Ullah, Saif, Unnikrishnan, Bhaskaran, Vacante, Marco, Valdez, Pascual R., Vasankari, Tommi Juhani, Venketasubramanian, Narayanaswamy, Vlassov, Vasily, Vos, Theo, Yearwood, Jamal Akeem, Yonemoto, Naohiro, Younis, Mustafa Z., Yu, Chuanhua, Zadey, Siddhesh, Bin Zaman, Sojib, Zerfu, Taddese Alemu, Zhang, Zhi-Jiang, Ziapour, Arash, Zodpey, Sanjay, Lim, Stephen S., Murray, Christopher J. L., and Lozano, Rafael (2022) Measuring the availability of human resources for health and its relationship to universal health coverage for 204 countries and territories from 1990 to 2019: a systematic analysis for the Global Burden of Disease Study 2019. Lancet, 399 (10341). pp. 2129-2154.

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Abstract

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.

Item ID:	75760
Item Type:	Article (Research - C1)
ISSN:	1474-547X
Copyright Information:	© 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license.
Date Deposited:	17 Aug 2022 08:40
FoR Codes:	42 HEALTH SCIENCES > 4203 Health services and systems > 420311 Health systems @ 50% 42 HEALTH SCIENCES > 4206 Public health > 420602 Health equity @ 25% 44 HUMAN SOCIETY > 4407 Policy and administration > 440706 Health policy @ 25%
SEO Codes:	20 HEALTH > 2002 Evaluation of health and support services > 200205 Health policy evaluation @ 30% 20 HEALTH > 2002 Evaluation of health and support services > 200206 Health system performance (incl. effectiveness of programs) @ 50% 20 HEALTH > 2002 Evaluation of health and support services > 200204 Health inequalities @ 20%
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