Executive Summary:
In a time characterized by major challenges in healthcare, data has emerged as a vital element for driving systemic transformation. This white paper explores the innovative methods employed by the Provincial Health Services Authority (PHSA) to leverage data, artificial intelligence, and cloud technologies in addressing complex healthcare issues.
- Healthcare Landscape: Mounting Challenges
The healthcare landscape is facing unprecedented challenges that threaten the well-being of individuals and communities alike. As we navigate a complex environment shaped by both lingering effects of the COVID-19 pandemic and a myriad of systemic pressures, the implications for public health are significant.
Key Systemic Pressures:
- Declining Life Expectancy
- First drop since 1921
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- Key Pressures:
- COVID-19 pandemic
- Illicit drug toxicity crisis
- Key Pressures:
- Mental Health Deterioration– 25% decline in youth mental wellness – Increasing anxiety and mood disorders
- Healthcare Workforce Crisis– Highest retirement rates in healthcare sector – 1 in 7 Canadians without healthcare provider – Extended wait times for medical services
- Data Infrastructure: The Foundational Transformation
Organizations are increasingly recognizing the need for robust data infrastructure to support their evolving needs. The PHSA Data Platform serves as a prime example of foundational transformation, enabling efficient management and utilization of vast amounts of data. Below are key characteristics and strategies that outline the platform’s significance and its strategic approach to cloud migration:
- 100+ Source Systems
- 20+ Terabytes Raw Data
- 50 Billion+ Data Rows
Hybrid Data Types:
- Structured clinical data
- Unstructured physician notes
- Real-time and batch data feeds
Cloud Migration Strategy:
- Transition from on-premise to Azure
- Enhanced data processing capabilities
- Improved machine learning integration
- Increased operational agility
- AI and Machine Learning Applications
The integration of AI and machine learning is transforming numerous fields, particularly in healthcare and emergency services. These advanced technologies enable significant improvements in efficiency, accuracy, and decision-making processes. Below are some key areas where practical implementations of AI and machine learning are making a notable impact:
a) Cancer Data Processing
- Reduced reporting time from 2 years to near real-time
- Natural Language Processing (NLP)
- Human-in-the-loop methodology
b) Diagnostic Imaging
- Synthetic data generation for AI training
- 201 synthetic vs. 201 real medical images
- Radiologist-validated accuracy
c) Emergency Services
- Predictive resource allocation
- Rotary wing service optimization
- Geographical coverage modeling
- Technological Approach: Microsoft Fabric Integration
Leveraging sophisticated data management solutions is essential for organizations aiming to enhance operational efficiency. The following key implementation goals outline the strategic approach for integrating Microsoft Fabric into our technological framework:
- Centralized data zones
- Improved data lineage tracking
- Enhanced cross-program data sharing
- Unstructured data utilization
- Proof of Concept: Congenital Syphilis Intervention
Comprehensive Data Strategy:
- End-to-end data capture
- Integrated public health and clinical datasets
- Retrospective and prospective outcome assessment
- NLP pattern recognition
- Synthetic data generation for research
- Challenges and Mitigation Strategies
In today’s rapidly changing business landscape, organizations often face a myriad of challenges that can impede their progress and adaptation to new realities. As companies strive to innovate and stay competitive, understanding these obstacles is crucial for developing effective strategies. Below are some of the key challenges encountered, along with corresponding mitigation strategies designed to address them effectively.
Identified Challenges:
- Organizational change resistance
- Technology evolution speed
- Budget constraints
- Complex integration requirements
Mitigation Approaches:
- Community of practice development
- Flexible technology adoption
- Incremental implementation
- Collaborative vendor partnerships
- Future Roadmap
As we look toward the future of healthcare, it is imperative to embrace innovative strategies that leverage technology to improve patient outcomes. Our roadmap outlines key strategic focus areas that will guide our efforts in enhancing healthcare delivery through advanced data-driven approaches. By honing in on these priorities, we can better position ourselves to address the evolving needs of patients and the healthcare system as a whole. Below are our strategic focus areas and recommended actions to drive this transformation:
- Expand AI-driven healthcare interventions
- Enhance predictive diagnostic capabilities
- Develop patient-centric data platforms
- Promote research through synthetic data
Recommended Actions:
- Invest in data infrastructure
- Develop cross-functional data teams
- Prioritize privacy-preserving technologies
- Embrace continuous learning models
Conclusion:
The future of healthcare depends on intelligent, integrated, and innovative data strategies. By changing data from a passive record into an active tool for problem-solving, health systems can tackle complex challenges, enhance patient outcomes, and develop more responsive, personalized care models.
Developed based on the 2024 Big Data West session by Alexandra Flat, Executive Vice President of Health System Intelligence, Data Governance, and Analytics, Provincial Health Services Authority
