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孟加拉国利用地区卫生信息系统软件收集和利用卫生数据的认知和经验:一项定性探索性研究。

Perceptions and experiences with district health information system software to collect and utilize health data in Bangladesh: a qualitative exploratory study.

机构信息

Health system and population studies division (HSPSD), icddr,b, Dhaka, Bangladesh.

Carolina Population Center, University of North Carolina, Chapel Hill, USA.

出版信息

BMC Health Serv Res. 2020 May 26;20(1):465. doi: 10.1186/s12913-020-05322-2.


DOI:10.1186/s12913-020-05322-2
PMID:32456706
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7249629/
Abstract

BACKGROUND: Accurate and high-quality data are important for improving program effectiveness and informing policy. In 2009 Bangladesh's health management information system (HMIS) adopted the District Health Information Software, Version 2 (DHIS2) to capture real-time health service utilization data. However, routinely collected data are being underused because of poor data quality and reporting. We aimed to understand the facilitators and barriers to implementing DHIS2 as a way to retrieve meaningful and accurate data for reproductive, maternal, newborn, child, and adolescent health (RMNCAH) services. METHODS: This qualitative study was conducted in two districts of Bangladesh from September 2017 to 2018. Data collection included key informant interviews (n = 11), in-depth interviews (n = 23), and focus group discussions (n = 2). The study participants were involved with DHIS2 implementation from the community level to the national level. The data were analyzed thematically. RESULTS: DHIS2 could improve the timeliness and completeness of data reporting over time. The reported facilitating factors were strong government commitment, extensive donor support, and positive attitudes toward technology among staff. Quality checks and feedback loops at multiple levels of data gathering points are helpful for minimizing data errors. Introducing a dashboard makes DHIS2 compatible to use as a monitoring tool. Barriers to effective DHIS2 implementation were lack of human resources, slow Internet connectivity, frequent changes to DHIS2 versions, and maintaining both manual and electronic system side-by-side. The data in DHIS2 remains incomplete because it does not capture data from private health facilities. Having two parallel HMIS reporting the same RMNCAH indicators threatens data quality and increases the reporting workload. CONCLUSION: The overall insights from this study are expected to contribute to the development of effective strategies for successful DHIS2 implementation and building a responsive HMIS. Focused strategic direction is needed to sustain the achievements of digital data culture. Periodic refresher trainings, incentives for increased performance, and an automated single reporting system for multiple stakeholders could make the system more user-friendly. A national electronic health strategy and implementation framework can facilitate creating a culture of DHIS2 use for planning, setting priorities, and decision making among stakeholder groups.

摘要

背景:准确和高质量的数据对于提高项目效果和为政策提供信息非常重要。2009 年,孟加拉国的卫生管理信息系统(HMIS)采用了地区卫生信息软件 2 版(DHIS2)来获取实时卫生服务利用数据。然而,由于数据质量和报告不佳,常规收集的数据未得到充分利用。我们旨在了解实施 DHIS2 的促进因素和障碍,以便为生殖、孕产妇、新生儿、儿童和青少年健康(RMNCAH)服务获取有意义和准确的数据。

方法:这项定性研究于 2017 年 9 月至 2018 年在孟加拉国的两个地区进行。数据收集包括关键信息人员访谈(n=11)、深入访谈(n=23)和焦点小组讨论(n=2)。研究参与者从社区到国家各级都参与了 DHIS2 的实施。数据采用主题分析方法进行分析。

结果:DHIS2 可以随着时间的推移提高数据报告的及时性和完整性。报告的促进因素包括政府的坚定承诺、广泛的捐助者支持以及工作人员对技术的积极态度。在数据收集点的多个层次上进行质量检查和反馈循环有助于最大限度地减少数据错误。引入仪表板使 DHIS2 更兼容作为监测工具使用。有效实施 DHIS2 的障碍包括人力资源不足、互联网连接速度慢、DHIS2 版本频繁更改以及同时维护手动和电子系统。DHIS2 中的数据仍然不完整,因为它没有从私立卫生机构捕获数据。两个平行的 HMIS 报告相同的 RMNCAH 指标会威胁数据质量并增加报告工作量。

结论:这项研究的总体见解有望为成功实施 DHIS2 和建立响应式 HMIS 制定有效的战略做出贡献。需要有针对性的战略方向来维持数字数据文化的成果。定期的更新培训、提高绩效的激励措施以及为多个利益相关者提供的自动化单一报告系统可以使系统更便于用户使用。国家电子卫生战略和实施框架可以促进在利益相关者群体中创建使用 DHIS2 进行规划、确定优先事项和决策的文化。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0770/7249629/e0155399f25e/12913_2020_5322_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0770/7249629/9eaf40c0b01f/12913_2020_5322_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0770/7249629/e0155399f25e/12913_2020_5322_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0770/7249629/9eaf40c0b01f/12913_2020_5322_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0770/7249629/e0155399f25e/12913_2020_5322_Fig2_HTML.jpg

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