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Description
Espirales helicoidales de liberación mecánica o hidráulica para embolización endovascular. Estéril y desechable. Longitud: 2 cm. Calibre: 0.038" Hélice: 6 mm
Classification
Material médico. Material de curacion
IMSS product code
060.365.1639.00
Presentation
Pieza
Each circle represents one of the 41 purchases of ESPIRALES made by the IMSS between 2009 and 2018.
| INSTITUTION | STATE | QUANTITY | TOTAL AMOUNT | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | LAST PURCHASE |
|---|---|---|---|---|---|---|---|
| H. de Oncología, Centro Médico Nacional Siglo XXI Umae Oncologia C.m.n. Siglo Xxi | Ciudad de México | 32 | 1.6 millones MXN | 111,338.6 MXN | 14.3 % | 31.6 | 22 de marzo de 2017 |
| H. de Especialidades, "Dr. Bernardo Sepulveda Gutiérrez" Centro Médico Nacional Siglo XXI Umae Especialidades C.m.n. Siglo Xxi | Ciudad de México | 9 | 1.8 millones MXN | 630,234.9 MXN | 88.5 % | 62.5 | 13 de marzo de 2018 |
| SUPPLIER | PURCHASES | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | TIME PERIOD |
|---|---|---|---|---|---|
| LEVBETH MEDICAL, S.A. DE C.V. | 29 | 710,485.2 MXN | 36.5 % | 85.1 | 2011 - 2018 |
| ENDOMEDICA,S. A. DE C. V. | 10 | 31,088.3 MXN | 19.5 % | 8.95 | 2009 - 2011 |
| BOSTON SCIENTIFIC DE MEXICO, S. A. DE C. V. | 2 | - MXN | - | - | 2016 - 2017 |
Entity type
Material de curacion
Date updated in QQW
3 de octubre de 2022
Source(s)
Part of the project
Organization responsible for the import
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Choose the system where you want to use the data to see the instructions. For research methodology, see the Manual for investigating open contracting.
Add this to your code:
library(rjson)
#Read JSON data into R
data <- fromJSON(file="http://localhost:10010/v3/products?limit=1&sort=&embed=true&db_prefix=&id=060.365.1639.00")
Add this to your code:
import json, urllib
#Read JSON data into python
response = urllib2.urlopen('http://localhost:10010/v3/products?limit=1&sort=&embed=true&db_prefix=&id=060.365.1639.00')
data = json.loads(response.read())
Add this to your code:
import pandas as pd
#Read JSON data into pandas
df = pd.read_json('http://localhost:10010/v3/products?limit=1&sort=&embed=true&db_prefix=&id=060.365.1639.00')