Department of Pediatric Newborn Medicine, Brigham and Women's Hospital, Suite BB-502, 75 Francis Street, Boston, MA, 02115, USA.
Projahnmo Research Group, Johns Hopkins University- Bangladesh, "Abanti", Flat #5B, House #37, Road #27, Banani, Dhaka, 1213, Bangladesh.
BMC Med Inform Decis Mak. 2019 Jun 20;19(1):116. doi: 10.1186/s12911-019-0835-7.
In low-income settings, community health workers (CHWs) are frequently the first point of contact for newborns. Mobile technology may aid health workers in classifying illness and providing referral and management guidance for newborn care. This study evaluates the potential for mobile health technology to improve diagnosis and case management of newborns in Bangladesh.
A mobile application based on Bangladesh's Comprehensive Newborn Care Package national guidelines (mCNCP) was developed to aid CHWs in identifying and managing small and sick infants. After a 2-day training, CHWs assessed newborns at Sylhet Osmani Medical College Hospital and in the Projahnmo research site (Sylhet, Bangladesh) using either mCNCP or a comparable paper form (pCNCP), similar to standard IMCI-formatted paper forms. CHWs were randomized to conduct a block of ~ 6 newborn assessments starting with either mCNCP or pCNCP, then switched to the alternate method. Physicians using mCNCP served as gold standard assessors. CHW performance with mCNCP and pCNCP were compared using chi-squared tests of independence for equality of proportions, and logistic regressions clustered by CHW.
Two hundred seven total CHW assessments were completed on 101 enrolled infants. mCNCP assessments were more often fully completed and completed faster than pCNCP assessments (100% vs 23.8%, p < 0.001; 17.5 vs 23.6 min; p < 0.001). mCNCP facilitated calculations of respiratory rate, temperature, and gestational age. CHWs using mCNCP were more likely to identify small newborns (Odds Ratio (OR): 20.8, Confidence Interval (CI): (7.1, 60.8), p < 0.001), and to correctly classify 7 out of 16 newborn conditions evaluated, including severe weight loss (OR: 13.1, CI: (4.6, 37.5), p < 0.001), poor movement (OR: 6.6, CI: (2.3, 19.3), p = 0.001), hypothermia (OR: 14.9, CI: (2.7, 82.2), p = 0.002), and feeding intolerance (OR: 2.1, CI: (1.3, 3.3), p = 0.003). CHWs with mCNCP were more likely to provide counseling as needed on 4 out of 7 case management recommendations evaluated, including kangaroo mother care.
CHWs in rural Bangladesh with limited experience using tablets successfully used a mobile application for neonatal assessment after a two-day training. mCNCP may aid frontline health workers in Bangladesh to improve completion of neonatal assessment, classification of illnesses, and adherence to neonatal management guidelines.
在低收入环境中,社区卫生工作者(CHW)通常是新生儿的第一个接触点。移动技术可以帮助卫生工作者对疾病进行分类,并为新生儿护理提供转诊和管理指导。本研究评估了移动健康技术在改善孟加拉国新生儿诊断和病例管理方面的潜力。
开发了一个基于孟加拉国综合新生儿护理包国家指南(mCNCP)的移动应用程序,以帮助 CHW 识别和管理小而患病的婴儿。在为期两天的培训后,CHW 使用 mCNCP 或类似的纸质表格(pCNCP)在 Sylhet Osmani 医学院医院和 Projahnmo 研究点(孟加拉国锡尔赫特)评估新生儿。CHW 被随机分配进行大约 6 个新生儿评估,从 mCNCP 或 pCNCP 开始,然后切换到另一种方法。使用 mCNCP 的医生作为金标准评估员。使用卡方检验和逻辑回归对 CHW 使用 mCNCP 和 pCNCP 的表现进行比较,后者采用 CHW 聚类。
共有 207 次 CHW 评估完成了 101 名入组婴儿。mCNCP 评估更常完整完成且完成速度更快(100% vs 23.8%,p<0.001;17.5 分钟 vs 23.6 分钟;p<0.001)。mCNCP 便于计算呼吸频率、体温和胎龄。使用 mCNCP 的 CHW 更有可能识别小婴儿(优势比(OR):20.8,置信区间(CI):(7.1,60.8),p<0.001),并正确分类评估的 16 种新生儿情况中的 7 种,包括严重体重减轻(OR:13.1,CI:(4.6,37.5),p<0.001)、运动不良(OR:6.6,CI:(2.3,19.3),p=0.001)、体温过低(OR:14.9,CI:(2.7,82.2),p=0.002)和喂养不耐受(OR:2.1,CI:(1.3,3.3),p=0.003)。使用 mCNCP 的 CHW 更有可能根据需要提供 7 项病例管理建议中的 4 项咨询,包括袋鼠式护理。
在孟加拉国农村地区,经验有限的 CHW 在接受为期两天的培训后成功使用了移动应用程序进行新生儿评估。mCNCP 可能有助于孟加拉国的一线卫生工作者改善新生儿评估的完成情况、疾病分类以及对新生儿管理指南的遵守情况。