Postpartum Hemorrhage Management in Obstetric Emergencies: Design and Development of a Smartphone-Based Intelligent System to Enhance Clinical Decision-Making and Quality of Maternal Care

Abstract

Background: Postpartum Hemorrhage (PPH) is one of the most common and life-threatening causes of maternal mortality worldwide. Empowering healthcare providers to manage this condition rapidly and effectively plays a vital role in improving maternal safety and reducing complications. With the advancement of digital technologies in both education and clinical practice, the use of intelligent systems can facilitate learning, decision-making, and enhance clinical performance. The present study aimed to design and develop a smartphone-based intelligent system for the management of postpartum hemorrha. Methods: This developmental–applied study was conducted in two phases. In the first phase (needs analysis), scientific content and essential skills related to postpartum hemorrhage management were identified through a systematic literature review and expert consultation. In the second phase (design and development), the main modules—including initial assessment, rapid diagnosis, pharmacological and non-pharmacological interventions, and prevention of complications—were designed. The final application was developed for the Android operating system using Kotlin, HTML, and CSS programming languages, and its content validity was confirmed by experts. Findings: The needs analysis revealed that the top priorities included rapid recognition of abnormal vital signs, clinical decision-making in selecting appropriate interventions, and effective control of bleeding. Expert evaluation indicated that the developed system demonstrated high levels of scientific accuracy, efficiency, user-friendliness, and visual appeal. Conclusion: The developed system provides an innovative and user-centered tool for improving decision-making skills and expediting the management process of postpartum hemorrhage in obstetric emergencies. Implementation of this technology can enhance the quality of maternal healthcare and reduce clinical errors in real-world settings. © 2026, Isfahan University of Medical Sciences(IUMS). All rights reserved.