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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 Publisher Pubmed



Haakenstad A1, 6 ; Irvine CMS1 ; Knight M1 ; Bintz C1 ; Aravkin AY1, 2, 3 ; Zheng P1, 3 ; Gupta V1, 3 ; Abrigo MRM7 ; Abushouk AI8, 11 ; Adebayo OM13 ; Agarwal G16 ; Alahdab F17 ; Alaly Z18, 19 ; Alam K20 Show All Authors
Authors
  1. Haakenstad A1, 6
  2. Irvine CMS1
  3. Knight M1
  4. Bintz C1
  5. Aravkin AY1, 2, 3
  6. Zheng P1, 3
  7. Gupta V1, 3
  8. Abrigo MRM7
  9. Abushouk AI8, 11
  10. Adebayo OM13
  11. Agarwal G16
  12. Alahdab F17
  13. Alaly Z18, 19
  14. Alam K20
  15. Alanzi TM21
  16. Alcalderabanal JE22
  17. Alipour V26, 27
  18. Alvisguzman N28, 29
  19. Amit AML30
  20. Andrei CL32
  21. Andrei T35
  22. Antonio CAT36, 37
  23. Arabloo J26
  24. Aremu O38
  25. Ayanore MA39, 40
  26. Banach M41, 42
  27. Barnighausen TW9, 43
  28. Barthelemy CM1
  29. Bayati M44
  30. Benzian H45
  31. Berman AE46
  32. Bienhoff K1
  33. Bijani A47
  34. Bikbov B48
  35. Biondi A49
  36. Boloor A50
  37. Busse R52
  38. Butt ZA53, 54
  39. Camera LA55
  40. Camposnonato IR23
  41. Cardenas R57
  42. Carvalho F58
  43. Chansa C43, 60
  44. Chattu SK61
  45. Chattu VK62, 63
  46. Chu DT64
  47. Dai X1, 3
  48. Dandona L1, 66, 67
  49. Dandona R1, 3, 66
  50. Dangel WJ1
  51. Daryani A68
  52. De Neve JW43
  53. Dhimal M69
  54. Dipeolu IO70
  55. Djalalinia S73
  56. Do HT74
  57. Doshi CP75
  58. Doshmangir L76
  59. Ehsanichimeh E78
  60. El Tantawi M82
  61. Fernandes E59
  62. Fischer F83
  63. Foigt NA84
  64. Fomenkov AA85
  65. Foroutan M86, 87
  66. Fukumoto T88
  67. Fullman N1
  68. Gad MM89, 90
  69. Ghadiri K91, 92
  70. Ghafourifard M77
  71. Ghashghaee A94
  72. Glucksman T1
  73. Goudarzi H97, 98
  74. Gupta RD99, 100
  75. Hamadeh RR101
  76. Hamidi S102
  77. Haro JM103, 104
  78. Hasanpoor E105
  79. Hay SI1, 3
  80. Hegazy MI106
  81. Heibati B107
  82. Henry NJ108
  83. Hole MK109
  84. Hossain N110
  85. Househ M111
  86. Ilesanmi OS14, 71
  87. Imaninasab MH112
  88. Irvani SSN113
  89. Islam SMS114, 115
  90. Jahani MA47
  91. Joshi A116
  92. Kalhor R95, 96
  93. Kayode GA117, 118
  94. Khalid N119
  95. Khatab K120, 121
  96. Kisa A122, 123
  97. Kochhar S4, 124
  98. Krishan K125
  99. Kuate Defo B126, 127
  100. Lal DK66
  101. Lami FH128
  102. Larsson AO129, 130
  103. Leasher JL131
  104. Legrand KE1
  105. Lim LL132, 133
  106. Mahotra NB134
  107. Majeed A135
  108. Maleki A79, 137
  109. Manjunatha N138
  110. Massenburg BB5
  111. Mestrovic T1, 139
  112. Mini GK140, 141
  113. Mirica A35
  114. Mirrakhimov EM142, 143
  115. Mohammad Y144
  116. Mohammed S52, 145
  117. Mokdad AH1, 3
  118. Morrison SD5
  119. Naghavi M1, 3
  120. Ndwandwe DE146
  121. Negoi I33, 148
  122. Negoi RI34, 149
  123. Ngunjiri JW150
  124. Nguyen CT151
  125. Nigatu YT152
  126. Onwujekwe OE153
  127. Ortegaaltamirano DV24
  128. Otstavnov N154
  129. Otstavnov SS154, 155
  130. Owolabi MO15, 72
  131. Pakhare AP116
  132. Pepito VCF31
  133. Perico N157
  134. Pham HQ158
  135. Pigott DM1, 3
  136. Pokhrel KN159
  137. Rabiee M160
  138. Rabiee N161, 162
  139. Rahimimovaghar V80
  140. Rawaf DL136, 163
  141. Rawaf S135, 164
  142. Rawal L165
  143. Remuzzi G157
  144. Renzaho AMN166, 167
  145. Resnikoff S168, 169
  146. Rezaei N81, 170
  147. Rezapour A26
  148. Rickard J171, 172
  149. Roever L173
  150. Sahu M1
  151. Samy AM12
  152. Sanabria J174, 175
  153. Santricmilicevic MM176, 177
  154. Saraswathy SYI178
  155. Seedat S179
  156. Senthilkumaran S180
  157. Servanmori E25
  158. Shaikh MA181
  159. Sheikh A10, 182
  160. Silva DAS184
  161. Stein C1, 3
  162. Stein DJ147
  163. Titova MV185, 186
  164. Topp SM187, 188
  165. Tovanipalone MR189, 190
  166. Ullah S191
  167. Unnikrishnan B51
  168. Vacante M49
  169. Valdez PR56, 192
  170. Vasankari TJ193, 194
  171. Venketasubramanian N195, 196
  172. Vlassov V156
  173. Vos T1, 3
  174. Yearwood JA197
  175. Yonemoto N198, 199
  176. Younis MZ200, 201
  177. Yu C202
  178. Zadey S204
  179. Zaman SB205, 206
  180. Zerfu TA183, 207
  181. Zhang ZJ203
  182. Ziapour A93
  183. Zodpey S65
  184. Lim SS1, 3
  185. Murray CJL1, 3
  186. Lozano R1, 3

Source: The Lancet Published:2022


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. Funding: Bill & Melinda Gates Foundation. © 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license
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