博茨瓦纳诊所的临床数据流:混合方法评估协议》。

IF 1.4 Q3 HEALTH CARE SCIENCES & SERVICES JMIR Research Protocols Pub Date : 2024-10-09 DOI:10.2196/52411
Grey Faulkenberry, Audrey Masizana, Badisa Mosesane, Kagiso Ndlovu
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引用次数: 0

摘要

背景:博茨瓦纳对其医疗保健信息基础设施进行了大量投资,包括儿童健康与营养、艾滋病护理和结核病等垂直项目。然而,有效整合现有的 18 个以上的数据收集和报告系统已被证明是一项挑战。博茨瓦纳健康数据合作路线图战略(2020-24 年)》指出:"存在并行的报告系统,数据未被纳入国家层面的主流报告。"《博茨瓦纳国家电子学习战略(2020 年)》也指出:"各个层面的信息流不足,系统激增,报告工具不综合;因此,太多系统无法沟通:本研究的目标是:(1) 创建一个可视化的表述方式,说明数据是如何通过医疗保健系统的各个层级进行处理和输入输出的;(2) 了解一线工作者如何看待现有平台上的医疗保健数据共享,以及数据对医疗保健服务提供的影响:研究环境包括博茨瓦纳各地的 30 家医疗机构,旨在从多个角度了解数据流和系统整合方面的挑战。研究设计结合了定性和定量方法,并借鉴了快速评估流程和资源有限环境下的技术评估模型。研究采用参与式研究方法,确保利益相关者从一开始就全面参与。调查工具的设计旨在捕捉医护人员之间数据处理、共享和整合的复杂性。研究采用了有目的的抽样策略,以确保不同医护角色和环境的参与者具有广泛的代表性。数据收集采用了数字调查和深度访谈两种方式。初步的分析主题包括对医疗数据价值的看法以及在数据收集和共享方面的经验。研究获得了全面的伦理批准,体现了在整个研究过程中维护研究完整性和参与者福利的承诺:研究招募了近 44 家医疗机构,涵盖了各种医疗机构。在招募的 44 家医疗机构中,有 27 家回应了调查并参与了访谈。参与访谈的医护人员中,75%(112/150)来自诊所,20%(30/150)来自医院,5%(8/150)来自卫生站和流动诊所。截至 2023 年 10 月 10 日,该研究共收集了 200 多份定量调查问卷,并进行了 90 次半结构式访谈:到目前为止,这项研究得到了卫生保健界的热情参与,突出了这项研究目标的相关性和必要性。我们相信,以广泛的社区参与为核心的研究方法对于深入了解医疗数据生态系统至关重要。现在,重点将转移到研究的分析阶段,目的是为改善博茨瓦纳医疗保健系统内的数据流提出全面建议:DERR1-10.2196/52411。
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Clinical Data Flow in Botswana Clinics: Protocol for a Mixed-Methods Assessment.

Background: Botswana has made significant investments in its health care information infrastructure, including vertical programs for child health and nutrition, HIV care, and tuberculosis. However, effectively integrating the more than 18 systems in place for data collection and reporting has proved to be challenging. The Botswana Health Data Collaborative Roadmap Strategy (2020-24) states that "there exists parallel reporting systems and data is not integrated into the mainstream reports at the national level," seconded by the Botswana National eLearning strategy (2020), which states that "there is inadequate information flow at all levels, proliferation of systems, reporting tools are not synthesized; hence too many systems are not communicating."

Objective: The objectives of this study are to (1) create a visual representation of how data are processed and the inputs and outputs through each health care system level; (2) understand how frontline workers perceive health care data sharing across existing platforms and the impact of data on health care service delivery.

Methods: The setting included a varied range of 30 health care facilities across Botswana, aiming to capture insights from multiple perspectives into data flow and system integration challenges. The study design combined qualitative and quantitative methodologies, informed by the rapid assessment process and the technology assessment model for resource limited settings. The study used a participatory research approach to ensure comprehensive stakeholder engagement from its inception. Survey instruments were designed to capture the intricacies of data processing, sharing, and integration among health care workers. A purposive sampling strategy was used to ensure a wide representation of participants across different health care roles and settings. Data collection used both digital surveys and in-depth interviews. Preliminary themes for analysis include perceptions of the value of health care data and experiences in data collection and sharing. Ethical approvals were comprehensively obtained, reflecting the commitment to uphold research integrity and participant welfare throughout the study.

Results: The study recruited almost 44 health care facilities, spanning a variety of health care facilities. Of the 44 recruited facilities, 27 responded to the surveys and participated in the interviews. A total of 75% (112/150) of health care professionals participating came from clinics, 20% (30/150) from hospitals, and 5% (8/150) from health posts and mobile clinics. As of October 10, 2023, the study had collected over 200 quantitative surveys and conducted 90 semistructured interviews.

Conclusions: This study has so far shown enthusiastic engagement from the health care community, underscoring the relevance and necessity of this study's objectives. We believe the methodology, centered around extensive community engagement, is pivotal in capturing a nuanced understanding of the health care data ecosystem. The focus will now shift to the analysis phase of the study, with the aim of developing comprehensive recommendations for improving data flow within Botswana's health care system.

International registered report identifier (irrid): DERR1-10.2196/52411.

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