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孕产妇和儿童健康信息系统的粒状本体模型。

A Granular Ontology Model for Maternal and Child Health Information System.

机构信息

National University of Sciences and Technology (NUST), Islamabad, Pakistan.

College of Computer Sciences and Information Technology (CCSIT), King Faisal University, Alahssa 31982, Saudi Arabia.

出版信息

J Healthc Eng. 2017;2017:9519321. doi: 10.1155/2017/9519321. Epub 2017 May 16.

DOI:10.1155/2017/9519321
PMID:29065669
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5450172/
Abstract

In several developing countries, maternal and child health indicators trail behind the international targets set by the UN as Millennium or Sustainable Development Goals. One of the reasons is poor and nonstandardized maternal health record keeping that affects data quality. Effective decision making to improve public healthcare depends essentially on the availability of reliable data. Therefore, the aim of this research is the design and development of the standard compliant data access model for maintaining maternal and child health data to enable the effective exchange of healthcare data. The proposed model is very granular and comprehensive in contrast with existing systems. To evaluate the effectiveness of the model, a web application was implemented and was reviewed by healthcare providers and expectant mothers. User feedback highlights the usefulness of the proposed approach as compared to traditional record-keeping techniques. It is anticipated that the proposed model will lay a foundation for a comprehensive maternal and child healthcare information system. This shall enable trend analysis for policy making to help accelerate the efforts for meeting global maternal and child health targets.

摘要

在一些发展中国家,母婴健康指标落后于联合国千年发展目标或可持续发展目标所设定的国际目标。其中一个原因是母婴健康记录保存不善且不规范,这影响了数据质量。为改善公共医疗保健做出有效决策,从根本上取决于是否能获得可靠的数据。因此,本研究旨在设计和开发符合标准的数据访问模型,以维护母婴健康数据,从而实现医疗保健数据的有效交换。与现有系统相比,所提出的模型在粒度和全面性方面都非常出色。为了评估该模型的有效性,我们实现了一个 Web 应用程序,并由医疗保健提供者和孕妇进行了审查。用户反馈突出了与传统记录保存技术相比,所提出方法的实用性。预计所提出的模型将为全面的母婴医疗保健信息系统奠定基础。这将能够进行趋势分析以制定政策,帮助加快实现全球母婴健康目标的努力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8779/5450172/af967ee381bd/JHE2017-9519321.004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8779/5450172/c77f2b3a09ef/JHE2017-9519321.001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8779/5450172/097ea8af3c65/JHE2017-9519321.002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8779/5450172/a8000604ca09/JHE2017-9519321.003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8779/5450172/af967ee381bd/JHE2017-9519321.004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8779/5450172/c77f2b3a09ef/JHE2017-9519321.001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8779/5450172/097ea8af3c65/JHE2017-9519321.002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8779/5450172/a8000604ca09/JHE2017-9519321.003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8779/5450172/af967ee381bd/JHE2017-9519321.004.jpg

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