Development of clinical decision tools for management of diarrhea of children in high and low resource settings

开发资源丰富和匮乏环境下儿童腹泻管理的临床决策工具

• 批准号: 10649542
• 负责人: Daniel Ted Leung
• 金额: $ 45.28万
• 依托单位: UNIVERSITY OF UTAH
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-05-08 至 2027-05-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10649542
• 关键词: Accident and Emergency department; Accounting; Acute Diarrhea; Age; Ambulatory Care Facilities; Antibiotics; Applied Research; Big Data; Blood; Breast Feeding; Canada; Caregivers; Cause of Death; Cessation of life; Child; Childhood; Climate; Clinic; Clinical; Clinical Management; Clinical Research; Cost Savings; Country; Data; Data Sources; Diagnostic; Diagnostic tests; Diarrhea; District Hospitals; Electronic Health Record; Electronics; Emergency Care; Emergency research; Enteral; Ethnic Population; Etiology; Feces; Feedback; Fever; Focus Groups; Goals; Guidelines; Health Personnel; Health care facility; Health system; Hydration status; Income; Individual; Interview; Intrinsic factor; Laboratories; Methods; Modeling; Morbidity - disease rate; Multi-site clinical study; Multicenter Studies; North America; Patient Care; Patients; Performance; Physicians; Pilot Projects; Pollution; Population; Predictive Factor; Prevalence; Probability; Property; Recording of previous events; Resource-limited setting; Resources; Risk Factors; Sampling; Seasons; Site; Symptoms; Syndrome; Testing; Viral; Vomiting; Weather; antimicrobial; clinical application; clinical decision support; clinical development; clinical examination; clinical predictive model; clinical predictors; design; diagnostic tool; diarrheal disease; economic evaluation; economic impact; ethnic diversity; expectation; global health; health care service utilization; implementation design; implementation study; improved; low and middle-income countries; low income country; mortality; pathogen; pediatric emergency; predictive tools; prospective; respiratory; rural setting; smartphone application; support tools; tool; urban setting; urgent care

Abstract Diarrheal diseases are the among the leading cause of death in children worldwide, most of which occur in low-income countries. In high-income countries, pediatric diarrhea remains a major utilization of healthcare resources. The cornerstone for management of diarrhea is rehydration, though antimicrobials are beneficial in some instances. Unfortunately, given that treatment is frequently empiric, based mostly on clinical suspicion for bacterial causes, antimicrobials are overused in management of diarrheal illness worldwide. In high-income countries, diagnostic testing is oftentimes overutilized. Thus, there is a need for clinical decision support tools for antimicrobial and diagnostic stewardship in many settings. Current clinical prediction tools are based mostly on patient-intrinsic properties such as the clinical exam and symptom history specific for that patient. We have preliminary data suggesting that the integration of patient-extrinsic data, including climate and seasonality parameters, and population-level pre-test probabilities (from prior patients and prior years’ prevalence), can improve the performance of a clinical prediction model. We also have preliminary data showing the potential for an electronic clinical decision-support tool (eCDST) that estimates diarrheal etiology to decrease antibiotic prescription rates. Our overarching goal is to: 1) improve diarrhea clinical prediction through integration of patient-extrinsic data sources, and 2) explore the potential feasibility and utility of an eCDST, such as a smartphone application or an electronic health record tool. In Aim 1, we will use data from several prospective clinical studies of pediatric diarrhea to build improved clinical prediction models that includes patient-extrinsic data sources. In Aim 2, we will determine the potential feasibility, utility, and economic impact of an eCDST for antibiotic and diagnostic stewardship by examining clinican and caregiver perspectives through in-depth interviews and focus groups. We will also perform an economic evaluation of eCDST in a US setting. Completion of the Aims will result in an optimized clinical prediction model using big data and lay the groundwork needed to inform the design of implementation studies of eCDSTs for management of pediatric diarrhea.

摘要 腹泻病是全世界儿童死亡的主要原因之一，其中大多数发生在 低收入国家。在高收入国家，儿科腹泻仍然是医疗保健的主要用途 资源腹泻管理的基础是补液，尽管抗菌药物在治疗腹泻中是有益的。 一些实例。不幸的是，由于治疗通常是经验性的，主要是基于临床怀疑， 由于细菌原因，在世界范围内，抗菌药物在治疗疟疾疾病中被过度使用。在高收入 在一些国家，诊断检测常常被过度使用。因此，需要临床决策支持工具 在许多环境中进行抗菌和诊断管理。目前的临床预测工具主要基于 患者固有属性，例如该患者的临床检查和症状史。我们有 初步数据表明，患者外部数据的整合，包括气候和季节性 参数和人群水平的预检验概率（来自既往患者和既往患病率），可以 改善临床预测模型的性能。我们也有初步的数据显示， 一种电子临床决策支持工具（eCDST），用于估计腹泻病因，以减少抗生素 处方药费率。我们的总体目标是：1）通过整合以下指标来改善腹泻临床预测： 患者外部数据源，以及2）探索eCDST的潜在可行性和实用性，例如 智能手机应用程序或电子健康记录工具。在目标1中，我们将使用来自几个前瞻性研究的数据， 儿科腹泻的临床研究，以建立改进的临床预测模型， 数据源在目标2中，我们将确定eCDST的潜在可行性、实用性和经济影响， 通过深入研究临床医生和护理人员的观点， 访谈和焦点小组。我们还将在美国环境中对eCDST进行经济评估。 目标的完成将导致使用大数据的优化临床预测模型，并奠定 为设计用于儿科疾病管理的eCDST实施研究提供信息所需的基础工作 腹泻

项目成果

Drivers of inappropriate use of antimicrobials in South Asia: A systematic review of qualitative literature.

南亚不当使用抗菌药物的驱动因素：定性文献的系统回顾。

• DOI: 10.1101/2023.09.28.23296313
• 发表时间: 2023
• 期刊: medRxiv : the preprint server for health sciences
• 作者: Murray,JenniferL;Leung,DanielT;Hanson,OliviaR;Ahmed,ShariaM;Pavia,AndrewT;Khan,AshrafulI;Szymczak,JuliaE;Vaughn,ValerieM;Patel,PayalK;Biswas,Debashish;Watt,MelissaH
• 通讯作者: Watt,MelissaH

Derivation and External Validation of a Clinical Prediction Model for Viral Diarrhea Etiology in Bangladesh.

• DOI: 10.1093/ofid/ofad295
• 发表时间: 2023-07
• 期刊: Open forum infectious diseases
• 影响因子: 4.2

Qualitative Assessment of a Smartphone-Based Mobile Health Tool to Guide Diarrhea Management in Bangladesh.

• DOI: 10.4269/ajtmh.23-0444
• 发表时间: 2024-01-03
• 期刊: The American journal of tropical medicine and hygiene
• 作者: Biswas D;Asadullah A;Khan SH;Khan ZH;Islam MT;Khan AI;Qadri F;Nelson EJ;Watt MH;Leung DT
• 通讯作者: Leung DT

Assessment of Model Estimated and Directly Observed Weather Data for Etiological Prediction of Diarrhea.

评估用于腹泻病因预测的模型估计和直接观测的天气数据。

• DOI: 10.1101/2023.10.12.23296959
• 发表时间: 2023
• 期刊: medRxiv : the preprint server for health sciences
• 作者: Brintz,BenJ;Colston,JoshM;Ahmed,ShariaM;Chao,DennisL;Zaitschik,Ben;Leung,DanielT
• 通讯作者: Leung,DanielT

Clinical Prediction Rule to Guide Diagnostic Testing for Shigellosis and Improve Antibiotic Stewardship for Pediatric Diarrhea.

• DOI: 10.1093/ofid/ofad119
• 发表时间: 2023-03
• 期刊: Open forum infectious diseases
• 影响因子: 4.2