[TCRED-SANTE-EQUIP-SPE] Equipment ratio by medical speciality
Updated by provider on March 14, 2025 (12:00 AM).
[FREQ] Frequency
- [A] Annual
[INDICATEUR] Indicators
- [EQUIP_SPE] Ratio of equipment
[NATURE] Nature
- [RATIO] Ratio
[SPECIALITE-SANTE] Medical speciality
- [CH] Surgery
- [GYN_OBS] Gynaecology-obstetrics
- [M] Medicine
[REF_AREA] Geographic areas
- [D01] 01 - Ain
- [D02] 02 - Aisne
- [D03] 03 - Allier
- [D04] 04 - Alpes-de-Haute-Provence
- [D05] 05 - Hautes-Alpes
- [D06] 06 - Alpes-Maritimes
- [D07] 07 - Ardèche
- [D08] 08 - Ardennes
- [D09] 09 - Ariège
- [D10] 10 - Aube
- [D11] 11 - Aude
- [D12] 12 - Aveyron
- [D13] 13 - Bouches-du-Rhône
- [D14] 14 - Calvados
- [D15] 15 - Cantal
- [D16] 16 - Charente
- [D17] 17 - Charente-Maritime
- [D18] 18 - Cher
- [D19] 19 - Corrèze
- [D21] 21 - Côte-d'Or
- [D22] 22 - Côtes-d'Armor
- [D23] 23 - Creuse
- [D24] 24 - Dordogne
- [D25] 25 - Doubs
- [D26] 26 - Drôme
- [D27] 27 - Eure
- [D28] 28 - Eure-et-Loir
- [D29] 29 - Finistère
- [D2A] 2A - Corse-du-Sud
- [D2B] 2B - Haute-Corse
- [D30] 30 - Gard
- [D31] 31 - Haute-Garonne
- [D32] 32 - Gers
- [D33] 33 - Gironde
- [D34] 34 - Hérault
- [D35] 35 - Ille-et-Vilaine
- [D36] 36 - Indre
- [D37] 37 - Indre-et-Loire
- [D38] 38 - Isère
- [D39] 39 - Jura
- [D40] 40 - Landes
- [D41] 41 - Loir-et-Cher
- [D42] 42 - Loire
- [D43] 43 - Haute-Loire
- [D44] 44 - Loire-Atlantique
- [D45] 45 - Loiret
- [D46] 46 - Lot
- [D47] 47 - Lot-et-Garonne
- [D48] 48 - Lozère
- [D49] 49 - Maine-et-Loire
- [D50] 50 - Manche
- [D51] 51 - Marne
- [D52] 52 - Haute-Marne
- [D53] 53 - Mayenne
- [D54] 54 - Meurthe-et-Moselle
- [D55] 55 - Meuse
- [D56] 56 - Morbihan
- [D57] 57 - Moselle
- [D58] 58 - Nièvre
- [D59] 59 - Nord
- [D60] 60 - Oise
- [D61] 61 - Orne
- [D62] 62 - Pas-de-Calais
- [D63] 63 - Puy-de-Dôme
- [D64] 64 - Pyrénées-Atlantiques
- [D65] 65 - Hautes-Pyrénées
- [D66] 66 - Pyrénées-Orientales
- [D67] 67 - Bas-Rhin
- [D68] 68 - Haut-Rhin
- [D69] 69 - Rhône
- [D70] 70 - Haute-Saône
- [D71] 71 - Saône-et-Loire
- [D72] 72 - Sarthe
- [D73] 73 - Savoie
- [D74] 74 - Haute-Savoie
- [D75] 75 - Paris
- [D76] 76 - Seine-Maritime
- [D77] 77 - Seine-et-Marne
- [D78] 78 - Yvelines
- [D79] 79 - Deux-Sèvres
- [D80] 80 - Somme
- [D81] 81 - Tarn
- [D82] 82 - Tarn-et-Garonne
- [D83] 83 - Var
- [D84] 84 - Vaucluse
- [D85] 85 - Vendée
- [D86] 86 - Vienne
- [D87] 87 - Haute-Vienne
- [D88] 88 - Vosges
- [D89] 89 - Yonne
- [D90] 90 - Territoire de Belfort
- [D91] 91 - Essonne
- [D92] 92 - Hauts-de-Seine
- [D93] 93 - Seine-Saint-Denis
- [D94] 94 - Val-de-Marne
- [D95] 95 - Val-d'Oise
- [D971] 971 - Guadeloupe
- [D972] 972 - Martinique
- [D973] 973 - French Guiana
- [D974] 974 - La Réunion
- [D976] 976 - Mayotte
- [FE] France
- [FM] Metropolitan France
- [F_H_IDF] Metropolitan France excluding Île-de-France
- [R11] Île-de-France
- [R24] Centre-Val de Loire
- [R27] Bourgogne-Franche-Comté
- [R28] Normandie
- [R32] Hauts-de-France
- [R44] Grand Est
- [R52] Pays de la Loire
- [R53] Bretagne
- [R75] Nouvelle-Aquitaine
- [R76] Occitanie
- [R84] Auvergne-Rhône-Alpes
- [R93] Provence-Alpes-Côte d'Azur
- [R94] Corse
[UNIT_MEASURE] Unit
- [P100000] per 100,000 inhabitants
[CORRECTION] Seasonal adjustment
- [BRUT] Uncorrected
[SERIE_ARRETEE] Stopped_series
- [FALSE] nO
Search filters
Frequency [FREQ] (1)
Indicators [INDICATEUR] (1)
Nature [NATURE] (1)
Medical speciality [SPECIALITE-SANTE] (3)
Geographic areas [REF_AREA] (117)
Unit [UNIT_MEASURE] (1)
Seasonal adjustment [CORRECTION] (1)
Stopped_series [SERIE_ARRETEE] (1)
This dataset has 351 series:
- from
- 2013=62
- to
- 2023=46
- min:
- 45
- max:
- 62
- avg:
- 50.727
- σ:
- 4.974
- from
- 2013=110
- to
- 2023=79
- min:
- 79
- max:
- 110
- avg:
- 88.909
- σ:
- 10.326
- from
- 2013=181
- to
- 2023=126
- min:
- 126
- max:
- 181
- avg:
- 148.182
- σ:
- 16.786
- from
- 2013=102
- to
- 2023=73
- min:
- 73
- max:
- 102
- avg:
- 96.364
- σ:
- 7.935
- from
- 2013=124
- to
- 2023=116
- min:
- 110
- max:
- 127
- avg:
- 117.818
- σ:
- 6.176
- from
- 2013=168
- to
- 2023=157
- min:
- 150
- max:
- 174
- avg:
- 163.636
- σ:
- 6.513
- from
- 2013=137
- to
- 2023=96
- min:
- 96
- max:
- 143
- avg:
- 116.727
- σ:
- 17.509
- from
- 2013=170
- to
- 2023=77
- min:
- 77
- max:
- 170
- avg:
- 95.636
- σ:
- 24.28
- from
- 2013=72
- to
- 2023=49
- min:
- 49
- max:
- 73
- avg:
- 64.727
- σ:
- 8.368
- from
- 2013=159
- to
- 2023=111
- min:
- 109
- max:
- 178
- avg:
- 144.455
- σ:
- 21.723
Series code | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 | 2019 | 2020 | 2021 | 2022 | 2023 |
---|---|---|---|---|---|---|---|---|---|---|---|
[A.EQUIP_SPE.RATIO.CH.D01.P100000.BRUT.FALSE] | 62 | 59 | 51 | 51 | 50 | 49 | 49 | 45 | 48 | 48 | 46 |
[A.EQUIP_SPE.RATIO.CH.D02.P100000.BRUT.FALSE] | 110 | 103 | 100 | 91 | 89 | 82 | 83 | 80 | 80 | 81 | 79 |
[A.EQUIP_SPE.RATIO.CH.D03.P100000.BRUT.FALSE] | 181 | 170 | 162 | 148 | 148 | 146 | 147 | 147 | 128 | 127 | 126 |
[A.EQUIP_SPE.RATIO.CH.D04.P100000.BRUT.FALSE] | 102 | 93 | 93 | 101 | 101 | 101 | 99 | 99 | 99 | 99 | 73 |
[A.EQUIP_SPE.RATIO.CH.D05.P100000.BRUT.FALSE] | 124 | 127 | 125 | 123 | 122 | 112 | 112 | 110 | 110 | 115 | 116 |
[A.EQUIP_SPE.RATIO.CH.D06.P100000.BRUT.FALSE] | 168 | 166 | 167 | 166 | 174 | 170 | 163 | 150 | 162 | 157 | 157 |
[A.EQUIP_SPE.RATIO.CH.D07.P100000.BRUT.FALSE] | 137 | 143 | 141 | 133 | 115 | 114 | 101 | 104 | 102 | 98 | 96 |
[A.EQUIP_SPE.RATIO.CH.D08.P100000.BRUT.FALSE] | 170 | 97 | 94 | 94 | 95 | 84 | 86 | 81 | 85 | 89 | 77 |
[A.EQUIP_SPE.RATIO.CH.D09.P100000.BRUT.FALSE] | 72 | 72 | 73 | 70 | 70 | 70 | 69 | 56 | 55 | 56 | 49 |
[A.EQUIP_SPE.RATIO.CH.D10.P100000.BRUT.FALSE] | 159 | 157 | 153 | 155 | 153 | 151 | 178 | 150 | 109 | 113 | 111 |
Showing results 1 - 10 / 351