Crehan Caroline, Kesler Erin, Nambiar Bejoy, Dube Queen, Lufesi Norman, Giaccone Matteo, Normand Charles, Azad Kishwar, Heys Michelle
Great Ormond Street Hospital Institute of Child Health, University College London, London, UK.
Institute for Global Child Health, University College London, London, UK.
BMJ Glob Health. 2019 Jan 16;4(1):e000860. doi: 10.1136/bmjgh-2018-000860. eCollection 2019.
More than two-thirds of newborn lives could be saved worldwide if evidence-based interventions were successfully implemented. We developed the NeoTree application to improve quality of newborn care in resource-poor countries. The NeoTree is a fully integrated digital health intervention that combines immediate data capture, entered by healthcare workers (HCW) on admission, while simultaneously providing them with evidence-based clinical decision support and newborn care education. We conducted a mixed-methods intervention development study, codeveloping and testing the NeoTree prototype with HCWs in a district hospital in Malawi. Focus groups explored the acceptability and feasibility of digital health solutions before and after implementation of the NeoTree in the clinical setting. One-to-one theoretical usability workshops and a 1-month clinical usability study informed iterative changes, gathered process and clinical data, System Usability Scale (SUS) and perceived improvements in quality of care. HCWs perceived the NeoTree to be acceptable and feasible. Mean SUS before and after the clinical usability study were high at 80.4 and 86.1, respectively (above average is >68). HCWs reported high-perceived improvements in quality of newborn care after using the NeoTree on the ward. They described improved confidence in clinical decision-making, clinical skills, critical thinking and standardisation of care. Identified factors for successful implementation included a technical support worker. Coproduction, mixed-methods approaches and user-focused iterative development were key to the development of the NeoTree prototype, which was shown to be an agile, acceptable, feasible and highly usable tool with the potential to improve the quality of newborn care in resource-poor settings.
如果成功实施基于证据的干预措施,全球超过三分之二的新生儿生命可以得到挽救。我们开发了NeoTree应用程序,以提高资源匮乏国家的新生儿护理质量。NeoTree是一种完全集成的数字健康干预措施,它结合了医护人员在新生儿入院时立即录入的数据,同时为他们提供基于证据的临床决策支持和新生儿护理教育。我们进行了一项混合方法的干预措施开发研究,与马拉维一家地区医院的医护人员共同开发并测试了NeoTree原型。焦点小组探讨了在临床环境中实施NeoTree之前和之后数字健康解决方案的可接受性和可行性。一对一的理论可用性研讨会和为期1个月的临床可用性研究为迭代更改提供了依据,收集了过程和临床数据、系统可用性量表(SUS)以及对护理质量的感知改善情况。医护人员认为NeoTree是可接受且可行的。临床可用性研究前后的平均SUS得分分别高达80.4和86.1(平均分以上为>68)。医护人员报告称,在病房使用NeoTree后,他们对新生儿护理质量的感知有了很大改善。他们表示在临床决策、临床技能、批判性思维和护理标准化方面的信心有所增强。确定的成功实施因素包括一名技术支持人员。共同生产、混合方法以及以用户为中心的迭代开发是NeoTree原型开发的关键,该原型被证明是一种灵活、可接受、可行且高度可用的工具,有潜力改善资源匮乏地区的新生儿护理质量。