Department of Public Health Medicine, Universiti Kebangsaan Malaysia Fakulti Perubatan, Cheras, Federal Territory of Kual, Malaysia
Centre for Research in Public Health and Community Care, University of Hertfordshire, Hertfordshire, UK.
BMJ Open. 2024 Jan 31;14(1):e078508. doi: 10.1136/bmjopen-2023-078508.
The implementation of digital health technologies (DHTs) in hospitals worldwide has been uneven since the COVID-19 pandemic. Ambiguity in defining the landscape of DHTs adds to the complexity of this process. To address these challenges, this scoping review aims to identify the facilitators and barriers of implementing DHTs in hospitals in lower-income and middle-income countries (LMIC) since COVID-19, describe the DHTs that have been adopted in hospital settings in LMIC during this period, and develop a comprehensive classification framework to define the landscape of DHTs implemented in LMIC.
We will conduct a systematic search in PubMed, Scopus, Web of Science and grey literature. Descriptive statistics will be used to report the characteristics of included studies. The facilitators and barriers to DHTs implementation, gathered from both quantitative and qualitative data, will be synthesised using a parallel-results convergent synthesis design. A thematic analysis, employing an inductive approach, will be conducted to categorise these facilitators and barriers into coherent themes. Additionally, we will identify and categorise all available DHTs based on their equipment types and methods of operation to develop an innovative classification framework.
Formal ethical approval is not required, as primary data collection is not involved in this study. The findings will be disseminated through peer-reviewed publications, conference presentations and meetings with key stakeholders and partners in the field of digital health.
自 COVID-19 大流行以来,全球医院的数字健康技术(DHT)的实施情况参差不齐。DHT 定义的不明确增加了这一过程的复杂性。为了应对这些挑战,本范围综述旨在确定自 COVID-19 以来,中低收入国家(LMIC)医院实施 DHT 的促进因素和障碍,描述在此期间 LMIC 医院环境中采用的 DHT,并制定一个综合分类框架来定义在 LMIC 实施的 DHT 景观。
我们将在 PubMed、Scopus、Web of Science 和灰色文献中进行系统搜索。将使用描述性统计来报告纳入研究的特征。将使用平行结果收敛综合设计,从定量和定性数据中综合 DHT 实施的促进因素和障碍。将采用归纳方法进行主题分析,将这些促进因素和障碍归入连贯的主题。此外,我们将根据设备类型和操作方法识别和分类所有可用的 DHT,以开发创新的分类框架。
本研究不涉及原始数据收集,因此不需要正式的伦理批准。研究结果将通过同行评审的出版物、会议演讲以及与数字健康领域的主要利益相关者和合作伙伴的会议来传播。