Generative AI-Powered Intrapartum Clinical Decision Support Among Healthcare Providers
Generative AI-Powered Intrapartum Clinical Decision Support and Healthcare Providers' Decision-Making Speed, Diagnostic Accuracy, Satisfaction, and Clinical Experience: A Quasi-Experimental Study
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]
調査の概要
状態
状態
条件
条件
介入・治療
介入・治療
詳細な説明
This single-center, non-randomized, parallel-group quasi-experimental study evaluated a generative AI-powered intrapartum clinical decision-support chatbot among healthcare providers involved in normal labor management.
The study included 427 obstetricians and nurses: 214 in the intervention group and 213 in the control group. Providers in the intervention group used the AI-based Smart Normal Labor application to support clinical assessment and decision-making during routine labor care. Providers in the control group followed conventional institutional care practices without using the application.
The evaluation combined assessments of clinical decision-making performance with provider-reported satisfaction, acceptance, clinical experience, and workflow. It also explored perceived barriers and facilitators to application use in clinical practice. The study focused on provider-level outcomes; maternal and neonatal clinical outcomes were not directly assessed.
研究の種類
研究の種類
入学 (実際)
入学
段階
段階
- 適用できない
連絡先と場所
研究場所
-
-
Dakahlia Governorate
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Al Mansurah、Dakahlia Governorate、エジプト、35712
- Basma wageah Basma
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-
参加基準
適格基準
適格基準
就学可能な年齢
- 子
- 大人
- 高齢者
健康ボランティアの受け入れ
受講資格のある性別
説明
Inclusion Criteria
Obstetricians and nurses 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.
At least six months of clinical experience in labor management. For the intervention group: completion of at least two months of training on the generative AI-powered Smart Normal Labor intrapartum chatbot before its use with clinical cases during the intervention.
For the intervention group: use of the generative AI-powered Smart Normal Labor intrapartum chatbot during clinical labor management.
For the control group: provision of routine care without prior use of the study chatbot.
Willingness to participate and provide informed consent.
Exclusion Criteria
Healthcare providers not directly involved in labor management, including administrative staff and laboratory personnel.
Less than six months of clinical experience in labor management.
Being on leave or unavailable during the study period.
Declining participation or not providing informed consent.
研究計画
研究はどのように設計されていますか？
デザインの詳細
- 主な目的：ヘルスサービス研究
- 割り当て：非ランダム化
- 介入モデル：並列代入
- マスキング：なし（オープンラベル）
アーム数
武器と介入
参加者グループ / アーム参加者グループ / アーム |
介入・治療介入・治療 |
|---|---|
|
実験的：Generative AI-Powered Intrapartum Chatbot Decision Support Group
Healthcare providers used the generative AI-powered Smart Normal Labor intrapartum chatbot to support clinical assessment, interpretation of labor progress, and clinical decision-making during normal labor management. The chatbot was used alongside routine institutional care practices. |
Smart Normal Labor is a mobile application incorporating a generative AI-powered chatbot for healthcare providers. It provides interactive clinical decision support using information entered by providers about labor progress and clinical findings. Its intended functions include supporting interpretation of clinical information and formulation of a management plan.
他の名前：
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介入なし：Routine Care Group
Healthcare providers managed normal labor according to routine institutional care practices without using the generative AI-powered intrapartum chatbot. |
この研究は何を測定していますか？
主要な結果の測定
主要な結果の測定
結果測定 |
メジャーの説明 |
時間枠 |
|---|---|---|
|
Time to a Confirmed Intrapartum Management Decision
時間枠：During the assessed intrapartum clinical encounter, from case presentation to confirmation of the management decision ,5 months
|
Elapsed time, measured in minutes, from admission of the woman in labor to confirmation of a clinical management plan by the healthcare provider. Shorter times indicate faster clinical decision-making. |
During the assessed intrapartum clinical encounter, from case presentation to confirmation of the management decision ,5 months
|
二次結果の測定
二次結果の測定
結果測定 |
メジャーの説明 |
時間枠 |
|---|---|---|
|
Diagnostic Accuracy in Intrapartum Clinical Cases
時間枠：During the assessed intrapartum clinical encounter, at completion of the diagnostic assessment ,5 months.
|
Percentage of assessed intrapartum clinical cases in which the healthcare provider's diagnosis agrees with the study-defined reference diagnosis, compared between the AI-supported intervention group and the conventional-care control group. Higher percentages indicate greater diagnostic accuracy. |
During the assessed intrapartum clinical encounter, at completion of the diagnostic assessment ,5 months.
|
協力者と研究者
研究記録日
主要日程の研究
研究開始 (実際)
研究開始
一次修了 (実際)
一次修了
研究の完了 (実際)
研究の完了
試験登録日
最初に提出
最初に提出
QC基準を満たした最初の提出物
QC基準を満たした最初の提出物
最初の投稿 (実際)
最初の投稿
学習記録の更新
投稿された最後の更新 (実際)
投稿された最後の更新
QC基準を満たした最後の更新が送信されました
QC基準を満たした最後の更新が送信されました
最終確認日
最終確認日
詳しくは
本研究に関する用語
その他の研究ID番号
その他の研究ID番号
- Smart Normal Labor
医薬品およびデバイス情報、研究文書
米国FDA規制医薬品の研究
米国FDA規制機器製品の研究
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