肯尼亚城市初级医疗抗生素处方监测数据

数据集获取（Figshare）

• 源站标题：Analyzing data from the digital healthcare exchange platform for surveillance of antibiotic prescriptions in primary care in urban Kenya: A mixed-methods study
• DOI：10.1371/journal.pone.0222651
• 发布日期：2019-09-26
• 文件数：4 个
• 文件总体积：9.76 MB
• 源站页面：https://plos.figshare.com/articles/dataset/Analyzing_data_from_the_digital_healthcare_exchange_platform_for_surveillance_of_antibiotic_prescriptions_in_primary_care_in_urban_Kenya_A_mixed-methods_study/9908849

命令行下载

curl -L -o "pone.0222651.s001.tif" "https://ndownloader.figshare.com/files/17814875"
curl -L -o "pone.0222651.s002.pdf" "https://ndownloader.figshare.com/files/17814878"
curl -L -o "pone.0222651.s003.pdf" "https://ndownloader.figshare.com/files/17814881"
curl -L -o "pone.0222651.s004.xlsx" "https://ndownloader.figshare.com/files/17814884"

文件清单

• pone.0222651.s001.tif（122.92 KB）
• pone.0222651.s002.pdf（230.02 KB）
• pone.0222651.s003.pdf（524.39 KB）
• pone.0222651.s004.xlsx（8.88 MB）

文件总体积 9.76 MB（源站 API 实测）。

数据说明

Background
Knowledge of antibiotic prescription practices in low- and middle-income countries is limited due to a lack of adequate surveillance systems.
Objective
To assess the prescription of antibiotics for the treatment of acute respiratory tract infections (ARIs) in primary care.
Method
An explanatory sequential mixed-methods study was conducted in 4 private not-for-profit outreach clinics located in slum areas in Nairobi, Kenya. Claims data of patients who received healthcare between April 1 and December 27, 2016 were collected in real-time through a mobile telephone-based healthcare data and payment exchange platform (branded as M-TIBA). These data were used to calculate the percentage of ARIs for which antibiotics were prescribed. In-depth interviews were conducted among 12 clinicians and 17 patients to explain the quantitative results.
Results
A total of 49,098 individuals were registered onto the platform, which allowed them to access healthcare at the study clinics through M-TIBA. For 36,210 clinic visits by 21,913 patients, 45,706 diagnoses and 85,484 medication prescriptions were recorded. ARIs were the most common diagnoses (17,739; 38.8%), and antibiotics were the most frequently prescribed medications (21,870; 25.6%). For 78.5% (95% CI: 77.9%, 79.1%) of ARI diagnoses, antibiotics were prescribed, most commonly amoxicillin (45%; 95% CI: 44.1%, 45.8%). These relatively high levels of prescription were explained by high patient load, clinician and patient perceptions that clinicians should prescribe, lack of access to laboratory tests, offloading near-expiry drugs, absence of policy and surveillance, and the use of treatment guidelines that are not up-to-date. Clinicians in contrast reported to strictly follow the Kenyan treatment guidelines.
Conclusion
This study showed successful quantification of antibiotic prescription and the prescribing pattern using real-world data collected through M-TIBA in private not-for-profit clinics in Nairobi.

许可

CC BY 4.0

引用

学术使用请引用 DOI 10.1371/journal.pone.0222651（source: https://plos.figshare.com/articles/dataset/Analyzing_data_from_the_digital_healthcare_exchange_platform_for_surveillance_of_antibiotic_prescriptions_in_primary_care_in_urban_Kenya_A_mixed-methods_study/9908849）。