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Enhancing healthcare outcome with scalable processing and predictive analytics via cloud healthcare API
Seyede Sana Salehi1, Hamid Saadatfar2, Solomon Sunday Oyelere3,4,5
1Department of Computer Engineering, Islamshahr Branch, Islamic Azad University, Islamshahr, Iran.
Frontiers in Digital Health
|January 26, 2026
Summary
Google Cloud Healthcare API transforms healthcare with advanced analytics and machine learning. While offering benefits like FHIR support, challenges in privacy and compliance require strategic management for successful cloud adoption.
Area of Science:
- Health Informatics
- Cloud Computing in Healthcare
- Data Analytics
Background:
- Healthcare data is heterogeneous and complex.
- Cloud platforms offer potential for advanced analytics and improved outcomes.
- Existing platforms face challenges in data management and integration.
Purpose of the Study:
- Investigate Google Cloud Healthcare API's role in healthcare transformation.
- Analyze cloud-based healthcare platforms' features and effectiveness.
- Compare Google Cloud Healthcare API with alternatives.
Main Methods:
- Systematic literature review.
- Examination of cloud-based healthcare platform features.
- Analysis of cloud solutions' impact on clinical outcomes.
- Comparative analysis of Google Cloud Healthcare API and competitors.
Main Results:
- Google Cloud Healthcare API offers a serverless architecture with native support for healthcare standards (FHIR, HL7v2, DICOM) and AI/ML integration.
- Cloud-based predictive analytics reduce hospital readmissions, physician burnout, and enable telemedicine.
- Improvements in patient outcomes, operational efficiency, and care delivery are achievable with comprehensive cloud solutions.
Conclusions:
- Google Cloud Healthcare API presents advantages for healthcare transformation.
- Challenges include data privacy, regulatory compliance, and vendor lock-in.
- Strategic planning and change management are crucial for successful cloud adoption in healthcare.
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