Impact of mobile health-enhanced supportive supervision and supply chain management on appropriate integrated community case management of malaria, diarrhoea, and pneumonia in children 2-59 months: A cluster randomised trial in Eastern Province, Zambia
Impact of mobile health-enhanced supportive supervision and supply chain management on appropriate integrated community case management of malaria, diarrhoea, and pneumonia in children 2-59 months: A cluster randomised trial in Eastern Province, Zambia
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DOI：
10.7189/jogh.10.010425
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发表时间：
2020-06-01
影响因子：
7.2
通讯作者：
MacLeod, William B.
中科院分区：
文献类型：
--
作者：
Biemba, Godfrey;Chiluba, Boniface;MacLeod, William B.
尽管过去二十年取得了进展，但儿童死亡率仍然很高，2018年全球有530万5岁以下儿童死亡。肺炎、腹泻和疟疾仍然是造成五岁以下儿童死亡的最常见原因；分别占全球死亡率的15%、8%和5%。最近的证据表明，肺炎、腹泻和疟疾的综合社区病例管理可以降低五岁以下儿童的死亡率。然而，尽管越来越多的证据表明综合管理的有效性，但实施方面仍存在挑战，特别是综合管理商品库存不足以及对社区卫生工作者的支持性监督不足。本研究旨在通过使用移动医疗（mHealth）技术解决成功实施iCCM的这两个关键挑战。方法：本整群随机对照试验比较了卫生保健中心集水区（聚类），其中卫生保健工作者及其主管实施了移动健康增强的iCCM支持性监督和供应链管理，与按照赞比亚现行指南实施iCCM的聚类进行了比较。干预组的卫生保健员使用移动电话社区DHIS2平台每周报告患有iCCM的儿童，并申请iCCM商品。他们的主管收到疾病病例数量的电子报告和每月自动监督提醒。主管在收到申请单后，组织医疗用品并通知卫生工作者领取。使用广义线性模型对主要结局进行意向治疗分析，即2-59个月的儿童接受iCCM训练的CHW治疗疟疾、肺炎或腹泻的适当治疗的百分比。采用具有可交换相关矩阵的对数二项回归计算了干预组和对照组的患病率和比较适当治疗的患病率的95%置信区间，并根据卫生机构的聚类进行了调整。结果干预组预期每月监督访视率为61.3%(98/160)，对照组为52.0%（78/150）。共有3690名2-59个月大的儿童出现疟疾、腹泻或肺炎。在干预组中，65.9%（1,252/1,899）的儿童接受了适当的iCCM治疗，而对照组为63.3%（1,134/1,791）。移动健康干预与18.0%的支持性监督改善和21.0%的肺炎适当治疗增加相关；这些变化没有统计学意义。接受订购用品的卫生保健员的比例增加了2-3倍：患病率从2.82（置信区间(CI) =1.50, 5.30）到3.01 （95% CI =1.29, 7.00）不等，具体取决于特定的商品。结论本研究无法确定使用移动健康技术是否会加强社区工作者iCCM商品的监督和供应链管理。在赞比亚农村，移动健康增强的iCCM对患有疟疾、肺炎和腹泻的儿童的适当诊断和治疗没有统计学上的显著影响。需要进行长期的纵向研究，以确定移动医疗增强的iCCM对卫生产出和结果的影响。
Background Despite progress made over the past twenty years, child mortality remains high, with 5.3 million children under five years having died in 2018 globally. Pneumonia, diarrhoea, and malaria remain among the commonest causes of under-five mortality; contributing 15%, 8%, and 5% of global mortality respectively. Recent evidence shows that integrated community case management (iCCM) of pneumonia, diarrhoea, and malaria can reduce under five mortality. However, despite growing evidence of the effectiveness of iCCM, there are implementation challenges, especially stock out of iCCM commodities and inadequate supportive supervision of community health workers (CHWs). This study aimed to address these two key challenges to successful iCCM implementation by using mobile health (mHealth) technology.Methods This cluster randomised controlled trial compared health centre catchment areas (clusters) where CHWs and their supervisors implemented mHealth-enhanced iCCM supportive supervision and supply chain management vs clusters implementing iCCM as per current Zambian guidelines. CHWs in intervention clusters used community DHIS2 platform on mobile phones to report on a weekly basis children with iCCM conditions and make requisitions for iCCM commodities. Their supervisors received electronic reports on disease caseloads and monthly automated supervision reminders. The supervisors on receipt of requisitions, organized the medical supplies and notified CHWs for collection. Intention-to-treat analysis on the primary outcome, the percentage of children aged 2-59 months receiving appropriate treatment for malaria, pneumonia, or diarrhoea from an iCCM trained CHW, was performed using a generalized linear model. Prevalence ratios and 95% confidence intervals comparing the prevalence of appropriate treatment in the intervention and control groups were calculated using log binomial regression with an exchangeable correlation matrix, adjusted for clustering by health facility.Results In the intervention clusters, 61.3% (98/160) of expected monthly supervision visits took place vs 52.0% (78/150) in the controls. A total of 3690 children 2-59 months old presented with malaria, diarrhoea, or pneumonia. In the intervention group, 65.9% (1,252/1,899) of children received appropriate care for iCCM conditions, compared to 63.3% (1,134/1,791) in the control group. The mHealth intervention was associated with 18.0% improvement in supportive supervision and 21.0% increase in appropriate treatment for pneumonia; these changes were not statistically significant. There was a 2-3-fold increase in the proportion of CHWs receiving supplies ordered: prevalence ratios ranged from 2.82 (confidence interval (CI) =1.50, 5.30) to 3.01 (95% CI =1.29, 7.00) depending on the particular commodity.Conclusion This study was unable to determine whether using mHealth technology would strengthen supervision and supply chain management of iCCM commodities for community-level workers. There was no statistically significant effect of mHealth enhanced iCCM on appropriate diagnosis and treatment for children with malaria, pneumonia, and diarrhoea in rural Zambia. Longer term longitudinal studies are required to determine the impact of mHealth enhanced iCCM on health outputs and outcomes.