Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, Maryland (MD), USA.
Norwegian Institute of Public Health, Oslo, Norway.
Cochrane Database Syst Rev. 2020 Oct 28;10(10):CD012907. doi: 10.1002/14651858.CD012907.pub2.
Health systems need timely and reliable access to essential medicines and health commodities, but problems with access are common in many settings. Mobile technologies offer potential low-cost solutions to the challenge of drug distribution and commodity availability in primary healthcare settings. However, the evidence on the use of mobile devices to address commodity shortages is sparse, and offers no clear way forward.
Primary objective To assess the effects of strategies for notifying stock levels and digital tracking of healthcare-related commodities and inventory via mobile devices across the primary healthcare system Secondary objectives To describe what mobile device strategies are currently being used to improve reporting and digital tracking of health commodities To identify factors influencing the implementation of mobile device interventions targeted at reducing stockouts of health commodities SEARCH METHODS: We searched CENTRAL, MEDLINE Ovid, Embase Ovid, Global Index Medicus WHO, POPLINE K4Health, and two trials registries in August 2019. We also searched Epistemonikos for related systematic reviews and potentially eligible primary studies. We conducted a grey literature search using mHealthevidence.org, and issued a call for papers through popular digital health communities of practice. Finally, we conducted citation searches of included studies. We searched for studies published after 2000, in any language.
For the primary objective, we included individual and cluster-randomised trials, controlled before-after studies, and interrupted time series studies. For the secondary objectives, we included any study design, which could be quantitative, qualitative, or descriptive, that aimed to describe current strategies for commodity tracking or stock notification via mobile devices; or aimed to explore factors that influenced the implementation of these strategies, including studies of acceptability or feasibility. We included studies of all cadres of healthcare providers, including lay health workers, and others involved in the distribution of health commodities (administrative staff, managerial and supervisory staff, dispensary staff); and all other individuals involved in stock notification, who may be based in a facility or a community setting, and involved with the delivery of primary healthcare services. We included interventions aimed at improving the availability of health commodities using mobile devices in primary healthcare settings. For the primary objective, we included studies that compared health commodity tracking or stock notification via mobile devices with standard practice. For the secondary objectives, we included studies of health commodity tracking and stock notification via mobile device, if we could extract data relevant to our secondary objectives.
For the primary objective, two authors independently screened all records, extracted data from the included studies, and assessed the risk of bias. For the analyses of the primary objectives, we reported means and proportions where appropriate. We used the GRADE approach to assess the certainty of the evidence, and prepared a 'Summary of findings' table. For the secondary objective, two authors independently screened all records, extracted data from the included studies, and applied a thematic synthesis approach to synthesise the data. We assessed methodological limitation using the Ways of Evaluating Important and Relevant Data (WEIRD) tool. We used the GRADE-CERQual approach to assess our confidence in the evidence, and prepared a 'Summary of qualitative findings' table.
Primary objective For the primary objective, we included one controlled before-after study conducted in Malawi. We are uncertain of the effect of cStock plus enhanced management, or cStock plus effective product transport on the availability of commodities, quality and timeliness of stock management, and satisfaction and acceptability, because we assessed the evidence as very low-certainty. The study did not report on resource use or unintended consequences. Secondary objective For the secondary objectives, we included 16 studies, using a range of study designs, which described a total of eleven interventions. All studies were conducted in African (Tanzania, Kenya, Malawi, Ghana, Ethiopia, Cameroon, Zambia, Liberia, Uganda, South Africa, and Rwanda) and Asian (Pakistan and India) countries. Most of the interventions aimed to make data about stock levels and potential stockouts visible to managers, who could then take corrective action to address them. We identified several factors that may influence the implementation of stock notification and tracking via mobile device. These include challenges tied to infrastructural issues, such as poor access to electricity or internet, and broader health systems issues, such as drug shortages at the national level which cannot be mitigated by interventions at the primary healthcare level (low confidence). Several factors were identified as important, including strong partnerships with local authorities, telecommunication companies, technical system providers, and non-governmental organizations (very low confidence); availability of stock-level data at all levels of the health system (low confidence); the role of supportive supervision and responsive management (moderate confidence); familiarity and training of health workers in the use of the digital devices (moderate confidence); availability of technical programming expertise for the initial development and ongoing maintenance of the digital systems (low confidence); incentives, such as phone credit for personal use, to support regular use of the system (low confidence); easy-to-use systems built with user participation (moderate confidence); use of basic or personal mobile phones to support easier adoption (low confidence); consideration for software features, such as two-way communication (low confidence); and data availability in an easy-to-use format, such as an interactive dashboard (moderate confidence).
AUTHORS' CONCLUSIONS: We need more, well-designed, controlled studies comparing stock notification and commodity management via mobile devices with paper-based commodity management systems. Further studies are needed to understand the factors that may influence the implementation of such interventions, and how implementation considerations differ by variations in the intervention.
卫生系统需要及时、可靠地获取基本药物和卫生商品,但在许多情况下,获取这些资源都存在问题。移动技术为解决初级卫生保健环境中药物配送和商品供应问题提供了潜在的低成本解决方案。然而,关于使用移动设备来解决商品短缺问题的证据很少,也没有明确的解决办法。
主要目的是评估通过移动设备通知药品库存水平和医疗相关商品及库存数字追踪的策略在整个初级卫生保健系统中的效果。次要目的是描述当前用于改善卫生商品报告和数字追踪的移动设备策略有哪些。确定影响针对减少卫生商品缺货的移动设备干预措施实施的因素。
我们于 2019 年 8 月检索了 CENTRAL、MEDLINE Ovid、Embase Ovid、全球索引医学(WHO)、POPLINE K4Health 以及两个试验注册库。我们还在 Epistemonikos 中检索了相关的系统评价和潜在的合格原始研究。我们使用 mHealthevidence.org 进行了灰色文献检索,并通过流行的数字卫生社区实践发布了征集论文的通知。最后,我们对纳入的研究进行了引文检索。我们检索了 2000 年后发表的所有语言的研究。
对于主要目标,我们纳入了个体和群组随机试验、对照前后研究和中断时间序列研究。对于次要目标,我们纳入了任何研究设计,包括定量、定性或描述性研究,旨在描述当前通过移动设备进行商品追踪或库存通知的策略;或旨在探讨影响这些策略实施的因素,包括对可接受性或可行性的研究。我们纳入了所有卫生保健提供者(包括基层卫生工作者)以及参与卫生商品配送的其他人员(行政人员、管理和监督人员、配药人员)的研究;以及所有其他参与库存通知的人员,他们可能在设施或社区环境中工作,并参与初级卫生保健服务的提供。我们纳入了旨在通过移动设备改善初级卫生保健环境中卫生商品供应的干预措施。对于主要目标,我们纳入了将通过移动设备进行卫生商品追踪或库存通知与标准实践进行比较的研究。对于次要目标,如果我们可以提取与我们的次要目标相关的数据,我们也纳入了通过移动设备进行卫生商品追踪和库存通知的研究。
对于主要目标,两名作者独立筛选所有记录,从纳入的研究中提取数据,并评估偏倚风险。对于主要目标的分析,我们适当地报告了均值和比例。我们使用 GRADE 方法评估证据的确定性,并编制了“证据总结表”。对于次要目标,两名作者独立筛选所有记录,从纳入的研究中提取数据,并应用主题综合方法对数据进行综合。我们使用评估重要和相关数据的方法(WEIRD)工具评估方法学局限性。我们使用 GRADE-CERQual 方法评估我们对证据的信心,并编制了“定性证据总结表”。
主要目标对于主要目标,我们纳入了一项在马拉维开展的对照前后研究。我们对 cStock 加强化管理或 cStock 加有效药品运输对商品供应、库存管理的质量和及时性、以及满意度和可接受性的影响持不确定态度,因为我们评估证据的确定性为极低。该研究未报告资源使用或意外后果。
次要目标对于次要目标,我们纳入了 16 项研究,使用了多种研究设计,共描述了 11 项干预措施。所有研究均在非洲(坦桑尼亚、肯尼亚、马拉维、加纳、埃塞俄比亚、喀麦隆、赞比亚、利比里亚、乌干达、南非和卢旺达)和亚洲(巴基斯坦和印度)国家开展。大多数干预措施旨在使管理人员能够了解库存水平和潜在的库存短缺情况,以便他们采取纠正措施来解决这些问题。我们确定了可能影响通过移动设备进行库存通知和追踪实施的几个因素。这些因素包括与电力或互联网接入等基础设施问题以及国家一级的药品短缺等更广泛的卫生系统问题有关,而这些问题无法通过初级卫生保健层面的干预措施来缓解(低可信度)。几个因素被认为很重要,包括与地方当局、电信公司、技术系统提供商和非政府组织建立强有力的伙伴关系(非常低可信度);卫生系统各级都有库存数据(低可信度);支持性监督和响应性管理的作用(中等可信度);卫生工作者对数字设备使用的熟悉程度和培训(中等可信度);数字系统的初始开发和持续维护所需的技术编程专业知识(低可信度);支持定期使用系统的激励措施,如个人手机充值(低可信度);易于使用的系统,有用户参与(中等可信度);使用基本或个人移动电话以支持更广泛的采用(低可信度);考虑软件功能,如双向通信(低可信度);以及易于使用的格式的数据可用性,如交互式仪表板(中等可信度)。
我们需要更多设计良好的、对照的研究,比较通过移动设备进行库存通知和商品管理与基于纸张的商品管理系统。需要进一步研究以了解可能影响此类干预措施实施的因素,以及实施考虑因素如何因干预措施的变化而有所不同。