Smart Normal Labor From Healthcare Providers' Perspective: Evaluating Clinical Decision-Making Speed, Diagnostic Accuracy, Satisfaction, and Experience Using an AI-Based Mobile Application
试验速览
- 阶段
- 不适用
- 状态
- 招募中
- 入组人数
- 427
- 试验地点
- 1
- 主要终点
- Primary Outcome
研究概览
简要总结
Pregnancy and childbirth are uniquely important events in women's lives because they are accompanied by major physical, emotional, and psychological changes. Maternal satisfaction, emotional well-being, and perceptions of childbirth are strongly influenced by the quality of labor management. A woman's childbirth experience is shaped by multiple factors, including communication, autonomy, and active participation in the decision-making process. These factors are widely recognized as important indicators of the quality of maternity care. [1]
Recent demographic changes and global population growth have placed increasing demands on healthcare systems, particularly maternal health services. High birth rates in some regions, combined with shortages of trained healthcare professionals, have created a need for scalable, adaptable, and innovative models of care. In response to these challenges, digital health technologies have emerged as promising tools to enhance the quality of maternity care and support both healthcare providers and pregnant women. [2]
详细描述
General Objective
To evaluate the impact of an artificial intelligence (AI)-based smart normal labor application on healthcare providers' clinical decision-making speed, diagnostic accuracy, satisfaction, and overall clinical experience during the management of normal labor.
Specific Objectives
To assess the effect of the AI-based smart normal labor application on the speed of clinical decision-making among obstetricians and nurses during the management of normal labor.
To evaluate the effect of the AI-based smart normal labor application on diagnostic accuracy during the management of normal labor.
研究设计
- 研究类型
- Interventional
- 分配方式
- Non Randomized
- 干预模型
- Parallel
- 主要目的
- Health Services Research
- 盲法
- Single (Participant)
入排标准
- 性别
- All
- 接受健康志愿者
- 是
入选标准
- •Participants must meet the following conditions to be included in the study:
- •Healthcare providers (obstetricians and nurses) currently working in the Labor Kiosk, Obstetrics and Gynecology Department, or Outpatient Gynecology Clinics at Mansoura University Hospital.
- •Direct involvement in the care and supervision of women in active labor.
- •For the intervention group: previous exposure to and use of the AI-based smart normal labor application for a minimum defined period (e.g., 1 month).
- •For the control group: no prior use of the AI-based application, following standard care practices.
- •Willingness to participate and provide informed consent.
排除标准
- •Participants will be excluded if they:
- •Are healthcare providers not directly involved in labor management (e.g., administrative staff or laboratory personnel).
- •Have less than the minimum required clinical experience in labor management (e.g., <6 months).
- •Are on leave or unavailable during the study period.
- •Decline to participate or do not provide informed consent.
结局指标
主要结局
Primary Outcome
时间窗: During labor management (from the onset of active labor until delivery, assessed up to 6-8 hours).
The time required for healthcare providers to make appropriate clinical decisions during the management of normal labor, measured using a structured clinical decision-making assessment tool.
次要结局
- Secondary Outcome(During labor management (from the onset of active labor until delivery, assessed up to 6-8 hours).)
研究者
Basma Wageah Mohamed Mohamed Elrefay
lecturer
Delta University for Science and Technology