Improving Performance of a Pediatric TeleMedicine and Medication Delivery Service through mHealth Technology

通过移动医疗技术提高儿科远程医疗和药物输送服务的性能

• 批准号: 10741179
• 负责人: Eric Jorge Nelson
• 金额: $ 20.24万
• 依托单位: UNIVERSITY OF FLORIDA
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-08-17 至 2025-05-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10741179
• 关键词: 5 year old; Acute respiratory infection; Address; Area; Artificial Intelligence; Caring; Cessation of life; Child; Child Care; Childhood; Clinical; Clinical Pathways; Cluster randomized trial; Communities; Complement; Complex; Data; Databases; Derivation procedure; Disease; Electronics; Emergency Care; Emergency Situation; Emergency medical service; Environment; Evaluation; Event; Funding; Future; Ghana; Goals; Guideline Adherence; Guidelines; Haiti; Health Services Accessibility; Hospital Referrals; Hospitals; Household; Infrastructure; Intervention; Knowledge; Location; Logistics; Methods; Modeling; Morbidity - disease rate; Outcome Measure; Paper; Participant; Pathway interactions; Patients; Performance; Persons; Pharmaceutical Preparations; Pilot Projects; Probability; Provider; Qualitative Research; Randomized, Controlled Trials; Research; Research Design; Resource-limited setting; Resources; Safety; Sensitivity and Specificity; Service delivery model; Services; Severities; Severity of illness; Site; Stress Tests; Technology; Telemedicine; Treatment Cost; Triage; USAID; United States National Institutes of Health; Validation; Virtual Tool; World Health Organization; clinical decision support; design; diarrheal disease; experience; health care availability; health care delivery; human centered design; implementation science; improved; innovation; mHealth; mortality; novel; pediatric patients; prediction algorithm; primary outcome; prototype; service delivery; statistical learning; success; support tools; treatment planning; virtual

PROJECT SUMMARY / ABSTRACT Acute respiratory infection and diarrheal disease are the two leading causes of pediatric death between 1 month and 5 years of age globally. These common problems have low-cost treatments, but these treatments are most effective when administered early. This is difficult in resource-limited settings, especially at night. Based on over 5 years of formative NIH-funded implementation science research, our team has built and deployed a telemedicine and medication delivery service (TMDS) called MotoMeds to improve nighttime access to care for children. The rationale is that a TMDS generates a multiplier effect to reduce mortality and morbidity to a greater extent than the provision of in-person emergency medical services (EMS) alone. A TMDS differs from EMS in that it mobilizes resources from a centralized location and transports these resources to households. An EMS, on the other hand, identifies patients at households and transports the patients to centralized resources. EMS logistics, clinical guidelines and decision-support tools do not readily apply to a TMDS. Novel methods are needed to assure that TMDS models of healthcare delivery safely reach their potential. MotoMeds was launched in Haiti in 2019 as a pre-pilot focused on safety and logistical feasibility and configured for scale in a pilot study in 2021. We developed paper-based decision-support tools for virtual call center exams that were derived from in-person World Health Organization (WHO) guidelines. Our research exposed a critical need for electronic clinical decision support (eCDS) to assure guideline adherence at scale and a need to confidently assign triage levels despite limitations in virtual telemedicine environments. Accurate triage is essential to determine TMDS pathways of care: delivery alone (mild cases), medication delivery plus an in-person exam (moderate cases) and EMS/hospital referral (severe cases). In the R21, we will address these needs by concurrently 1) designing an alpha prototype of the eCDS tool through human centered design followed by qualitative research analysis, while 2) using existing data from our prior two studies to derive and internally validate a disease severity prediction (DSP) algorithm for integration into the eCDS tool. In the R33, we will externally validate the accuracy of the DSP and evaluate the performance of a beta eCDS prototype in a pilot stepped wedge cluster randomized trial. The performance of the beta eCDS prototype will be determined by comparing rates of guideline adherence (primary outcome measure) and logistical metrics among providers using paper (control) vs electronic (intervention) decision support. This single-site pilot will provide essential experience and metrics for a future multi-site randomized controlled trial of the eCDS integrated with the DSP.

项目总结/摘要 急性呼吸道感染和呼吸道疾病是儿童死亡的两个主要原因， 5个月和5岁的全球。这些常见的问题都有低成本的治疗方法，但这些治疗方法 在早期使用时最有效。这在资源有限的环境中是困难的，特别是在晚上。 基于超过5年的形成NIH资助的实施科学研究，我们的团队已经建立并 部署了一项名为MotoMeds的远程医疗和药物递送服务（TMDS）， 获得对儿童的照顾。基本原理是TMDS产生乘数效应，降低死亡率， 这在很大程度上比仅提供现场急救医疗服务（EMS）更能降低发病率。一 TMDS与EMS的不同之处在于，它从一个集中的位置调动资源，并将这些资源 资源到户。另一方面，EMS在家庭中识别患者并将其运送到 患者集中资源。EMS物流、临床指南和决策支持工具并不容易 适用于TMDS。需要新的方法来确保TMDS模式的医疗保健服务安全地达到 他们的潜力MotoMeds于2019年在海地推出，作为一个专注于安全和后勤的预试点 可行性，并在2021年的试点研究中进行规模化配置。我们开发了基于纸张的决策支持工具 用于虚拟呼叫中心考试，这些考试源自世界卫生组织（WHO）的指导方针。 我们的研究揭示了对电子临床决策支持（eCDS）的迫切需求，以确保指南 尽管虚拟远程医疗存在局限性，但大规模的依从性和自信地分配分诊级别的需求 环境.准确的分诊对于确定TMDS护理途径至关重要：单独分娩（轻度病例）， 药物递送加上亲自检查（中度病例）和EMS/医院转诊（重度病例）。在 R21，我们将通过以下方式同时满足这些需求：1）设计eCDS工具的alpha原型， 以人为本的设计，其次是定性研究分析，而2）使用现有的数据，从我们以前的 两项研究推导并在内部验证疾病严重程度预测（DSP）算法， 到eCDS工具中。在R33中，我们将从外部验证DSP的准确性，并评估 在一项先导性阶梯式楔形簇随机试验中，β eCDS原型的性能。的 测试版eCDS原型的性能将通过比较指南遵守率来确定 （主要结局指标）和使用纸质（对照）与电子 （干预）决策支持。这一单站点试点将为未来的 eCDS与DSP整合的多中心随机对照试验。