Hospital Intelligence Platform-Jio Platforms Ltd
Hospital Intelligence Platform
Problem
- Medical data is fragmented across different systems (EMR, HIS, PACS, LIMS), making retrieval and processing inefficient.
- No standardized framework existed to collect and integrate data from various hospital devices and systems.
- Compliance with the DPDPA Act 2023 and Reliance’s information security guidelines was necessary to protect patient data.
- Absence of AI-powered solutions to optimize hospital workflows, improve decision-making, and enhance patient outcomes.
- Need for AI-powered analytics to detect patterns, improve diagnosis accuracy, and predict potential health risks proactively.
Solution
- Created a centralized data repository to store and process structured and unstructured medical data securely.
- Developed APIs and protocols to seamlessly connect different biomedical equipment and pull data into a single system.
- Implemented SHA256 encryption and image processing techniques to ensure patient data privacy.
- Deployed AI-powered tools for diagnosis, hospital resource optimization, and predictive analytics to enhance healthcare services.
- Built a hospital application with annotation tools to allow doctors to label medical images, creating high-quality training datasets.
Outcomes
- Deployed an AI model (Specificity: 81.94%, Sensitivity: 81.55%) to classify chest X-rays, improving diagnostic efficiency.
- AI-based patient Length of Stay prediction model (trained on 1 million data points) improved resource allocation by 15% and reduced operational costs by 10%.
- AI model (Specificity: 78.4%, Sensitivity: 79.9%) successfully identified diabetic retinopathy, aiding early detection.
- Deployed a histopathology AI model (Specificity: 99.1%, Sensitivity: 98.64%) to classify Invasive Ductal Carcinoma (IDC), improving cancer diagnostics.
- AI model (Specificity: 91.7%, Sensitivity: 88.45%) classified knee and hip implants using X-ray analysis, enhancing post-surgical evaluation accuracy.
SKOCH Award Nominee
Category: Digital Transformation
Sub-Category: Digital Strategy and Innovation
Project: Hospital Intelligence Platform
Start Date: 25-07-2022
Organisation: Jio Platforms Ltd
Respondent: Mr Vikas Gupta
https://www.jio.com/platforms/
Level: DX-1
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Case Study
Hospital Intelligence Platform by Jio Platforms Ltd.
Jio Platforms Ltd. developed the Hospital Intelligence Platform to address critical inefficiencies in healthcare data management and hospital operations. Launched in July 2022, the platform leverages Big Data, Artificial Intelligence (AI), and robust security measures to integrate patient information, optimize decision-making, and improve healthcare outcomes. By consolidating disparate medical data sources, the platform enhances the accuracy, efficiency, and security of hospital operations.
Problems Faced
The healthcare sector faces multiple challenges related to data fragmentation, security, and operational inefficiencies. Firstly, medical data is scattered across various systems, such as Electronic Medical Records (EMR), Hospital Information Systems (HIS), PACS, and LIMS, making it difficult to retrieve and analyze patient information efficiently. Secondly, a lack of standard integration protocols for biomedical equipment hindered seamless data collection and utilization. Thirdly, data privacy concerns arose due to strict compliance requirements under the DPDPA Act 2023 and Reliance’s internal security policies. Fourthly, hospitals struggled with resource mismanagement due to the absence of AI-driven insights for patient care and hospital workflow optimization. Lastly, the need for predictive analytics to improve diagnosis accuracy and patient outcomes remained unmet.
Solutions Implemented
To address these challenges, Jio Platforms Ltd. developed a centralized hospital intelligence system that integrates structured and unstructured medical data. A Big Data-driven architecture was implemented to enable seamless data retrieval and analysis. The platform established standardized APIs to integrate data from various biomedical devices, allowing real-time synchronization. Robust encryption (SHA256) and anonymization techniques were deployed to ensure compliance with data protection regulations. AI-powered solutions were introduced to optimize hospital workflows, diagnosis, and predictive analytics. Additionally, a custom annotation tool was developed, allowing doctors to label medical images, thereby enhancing AI training datasets and improving diagnostic accuracy.
Key Outcomes
The implementation of the Hospital Intelligence Platform resulted in significant improvements in hospital operations and patient care. An AI model for chest X-ray classification (Specificity: 81.94%, Sensitivity: 81.55%) streamlined radiology workflows, improving diagnostic accuracy. Another AI model for predicting ICU length of stay enhanced resource allocation by 15% and reduced operational costs by 10%. A diabetic retinopathy detection model (Specificity: 78.4%, Sensitivity: 79.9%) enabled early diagnosis, while an AI-based breast cancer detection system (Specificity: 99.1%, Sensitivity: 98.64%) improved cancer screening efficiency. Additionally, an implant detection AI model (Specificity: 91.7%, Sensitivity: 88.45%) facilitated post-surgical monitoring, leading to better patient management.
Summary
The Hospital Intelligence Platform by Jio Platforms Ltd. represents a significant breakthrough in digital transformation within healthcare. By integrating AI, Big Data, and secure data management practices, the platform enhances efficiency, diagnostic accuracy, and patient care. Its scalability and compliance-driven architecture make it a highly adaptable solution for hospitals, ensuring sustainable improvements in healthcare delivery.
For more information, please contact:
Mr Vikas Gupta at Vikas10.Gupta@ril.com
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