印度私立门诊抗生素处方率与模式：来自医疗审计数据的证据

数据集获取（Figshare）

• 源站标题：Outpatient antibiotic prescription rate and pattern in the private sector in India: Evidence from medical audit data
• DOI：10.1371/journal.pone.0224848
• 发布日期：2019-11-13
• 文件数：3 个
• 文件总体积：49.50 KB
• 源站页面：https://plos.figshare.com/articles/dataset/Outpatient_antibiotic_prescription_rate_and_pattern_in_the_private_sector_in_India_Evidence_from_medical_audit_data/10300358

命令行下载

curl -L -o "pone.0224848.s001.docx" "https://ndownloader.figshare.com/files/18718784"
curl -L -o "pone.0224848.s002.docx" "https://ndownloader.figshare.com/files/18718787"
curl -L -o "pone.0224848.s003.docx" "https://ndownloader.figshare.com/files/18718790"

文件清单

• pone.0224848.s001.docx（13.13 KB）
• pone.0224848.s002.docx（13.55 KB）
• pone.0224848.s003.docx（22.82 KB）

文件总体积 49.50 KB（源站 API 实测）。

数据加载示例（图像类）

from PIL import Image
import glob, os

files = (glob.glob(os.path.join(path, "**", "*.png"), recursive=True)
       + glob.glob(os.path.join(path, "**", "*.jpg"), recursive=True)
       + glob.glob(os.path.join(path, "**", "*.tif"), recursive=True))
print("图像文件数:", len(files))
img = Image.open(files[0]); print("尺寸/模式:", img.size, img.mode)

# torchvision Dataset 方式:
# from torchvision import datasets
# ds = datasets.ImageFolder(path)  # 要求 子目录=类别

目录组织与标注格式以源站说明和下载后实际文件为准。

数据说明

The key objective of this research was to generate new evidence on outpatient antibiotic prescription rate and patterns in the private sector in India. We used 12-month period (May 2013 to April 2014) medical audit dataset from IQVIA (formerly IMS Health). We coded the diagnosis provided in the medical audit data to International Statistical Classification of Diseases and Related Health Problems (ICD-10) and the prescribed antibiotics for the diagnosis to Anatomic Therapeutic Chemical (ATC) classification of World Health Organization (ATC index-2016). We calculated and reported antibiotic prescription rate per 1,000 persons per year, by age groups, antibiotic class and disease conditions. Our main findings are—approximately 519 million antibiotic prescriptions were dispensed in the private sector, which translates into 412 prescriptions per 1,000 persons per year. Majority of the antibiotic prescriptions were dispensed for acute upper respiratory infections (J06) (20.4%); unspecified acute lower respiratory infection (J22) (12.8%); disorders of urinary system (N39) (6.0%); cough (R05) (4.7%); and acute nasopharyngitis (J00) (4.6%) and highest antibiotic prescription rates were observed in the age group 0–4 years. To conclude our study reports first ever country level estimates of antibiotic prescription by antibiotic classes, age groups, and ICD-10 mapped disease conditions.

许可

CC BY 4.0

引用

学术使用请引用 DOI 10.1371/journal.pone.0224848（source: https://plos.figshare.com/articles/dataset/Outpatient_antibiotic_prescription_rate_and_pattern_in_the_private_sector_in_India_Evidence_from_medical_audit_data/10300358）。