The primary aim of this study is to develop and implement a proactive, AI-supported strategy for the prevention and early management of urinary incontinence (UI) among older adults in Iran. Specifically, the study seeks to:

Develop a tiered clinical competency model that equips healthcare providers with progressive skills for UI prevention.

Integrate artificial intelligence tools—including natural language processing (NLP), predictive modeling, and smart clinical dashboards—into routine elderly care to enhance risk assessment and care planning.

Establish standardized electronic portfolios to monitor patient outcomes and evaluate clinician performance in UI management.

Implement interactive training modules and clinical audit systems to sustain high-quality, preventive care practices across interdisciplinary healthcare teams.

This study is designed as a developmental implementation project, aimed at creating a framework for the proactive management of urinary incontinence (UI) in older adults. The focus is on designing a comprehensive, AI-assisted system and corresponding clinical standards. 

System Development
The project involves the creation of an AI-supported, knowledge-based system integrated into elderly care services. Key components include:

-Natural Language Processing (NLP): For automatic extraction of UI-related risk factors from electronic medical records and Published literature.

-Predictive Risk Modeling: Algorithms trained on geriatric datasets to stratify patients by UI risk level and guide preventive strategies based on updated clinical guidelines.

-Clinical Dashboards: Interactive, real-time tools for monitoring patient status and supporting clinical decision-making.

-Electronic Portfolios: Structured digital records to track patient outcomes and healthcare provider performance over time.

The system will have the potential of  integrating into the existing healthcare infrastructure through collaboration with national health IT platforms.

Standards Development
To support sustainable and scalable implementation, the study will establish standardized clinical and educational frameworks:

Standard 1: Protocols for risk identification (e.g., EMR-based alerts, checklists)

Standard 2: Unified documentation templates and electronic portfolios for use across care settings

Standard 3: Preventive care pathways, guided by AI-based risk scoring and stratification

Standard 4: Interdisciplinary collaboration frameworks for coordinated care among primary and specialty providers

The development of the modular training and standards framework is expected to achieve the following:

-Defined Clinical Competency Levels: A four-tier clinical competency model (Beginner to Master) for UI prevention will be clearly outlined, allowing for structured progression in knowledge and skills among healthcare providers.

-Development of Modular Curriculum: Four comprehensive training modules will be created, covering UI risk screening, lifestyle and medication impacts, AI tools in geriatric care, and long-term, interdisciplinary management strategies.

-Alignment with National Standards: The modular content will be aligned with newly developed national standards for risk identification, AI-driven care pathways, unified documentation, and team-based management.

=Digital-Ready Training Content: All modules will be designed for delivery through e-learning platforms, simulations, and AI-integrated training tools, ready for deployment upon project launch.

We will provide the essential foundation for the full implementation of this project, which will mark a major shift from reactive to preventive care in geriatric health services. Through the development of standardized protocols, modular training, and AI-integrated tools, we will enable healthcare providers to identify risks earlier, personalize care strategies, and collaborate more effectively across disciplines.

This transformation will lead to better clinical outcomes, improved quality of life for older adults, and a more efficient, technology-enabled healthcare system. By embedding preventive UI management into routine practice, we aim to create a scalable, sustainable model that aligns with international standards and addresses the growing needs of Iran’s aging population.

There will be  a national shift from reactive to preventive care in managing urinary incontinence among older adults. By combining AI tools with standardized training and care protocols, we aim to enhance clinical outcomes, support healthy aging, and build a more efficient, future-ready healthcare system.

ICS, Standards for UI Management, 2024.
INCONTINENCE 7 th Edition 2023