During the COVID-19 pandemic, Canada experienced half the per capita deaths compared to the United States, which experts attribute to Canada’s successful public health response. While political and demographic factors played a role, data modernization efforts were a key contributor to Canada’s ability to track and contain the spread of the virus. Public health organizations around the world can learn from Canada’s approach to data modernization and potentially save lives in future public health emergencies.

A Proactive Approach to Global Health Crises

Following the SARS outbreak in 2003, Canadian federal and provincial governments recognized the inadequacy of their existing public health systems and IT infrastructure. They collaborated with IBM to develop a comprehensive public health disease surveillance and immunization system called IBM Panorama. This system played a crucial role in Canada’s response to COVID-19. In contrast, public health officials in the US continued to rely on paper-based systems that were ill-equipped to handle the rapid spread of the virus.

Canadian authorities effectively used Panorama for various public health functions, including case investigation, outbreak management, and vaccine inventory management. When the COVID-19 pandemic struck, Canada was better prepared to respond compared to many US counterparts due to their adoption of this enterprise-grade solution specifically designed for public health.

Key Lessons from Canada’s Response

1. Lesson 1: Use a data model built for public health. Canadian provinces utilized a public health data model in their disease surveillance solution, which allowed for effective forecasting, trend identification, and intervention analysis. US public health agencies should consider adopting solutions that come with proven, terminology-rich data models.
2. Lesson 2: Make decisions based on high-quality data. High-quality data is essential for an effective public health response. US agencies should invest in solutions that can ingest data in multiple formats and have built-in processes for data cleansing to ensure data integrity.
3. Lesson 3: Handle large data volumes with system integration. Both Canadian and US public health agencies dealt with large volumes of data during the pandemic. Canada successfully integrated data through systems like Panorama, which served as a comprehensive source of truth for exposure, case investigation, and outbreak management information. The US should prioritize system integration to avoid silos and incomplete data.
4. Lesson 4: Adopt a cloud-native architecture for scalability. Investing in a cloud-native solution allows for elastic scalability, which is crucial during both regular operations and emergency situations in public health.
5. Lesson 5: Prioritize agile configurability for evolving disease scenarios. Public health agencies should opt for solutions that can adapt to emerging diseases and conditions, rather than only serving single diseases. This configurability allows for flexibility in responding to new public health challenges.
6. Lesson 6: Empower end users with customizable systems. Data modernization initiatives should consider human-centered design to attract and empower new talent in the public health field. Augmented intelligence, guided workflows, and machine learning can all contribute to more efficient and effective public health responses.
7. Lesson 7: Use storytelling to engage stakeholders and the public. In addition to reporting and analyzing data, public health agencies should focus on effective storytelling to increase public understanding and facilitate action. Canada provides “data storytelling” trainings for public health professionals to maximize the impact of data insights.

By incorporating these lessons into their data modernization efforts, US public health agencies can better manage steady-state operations and be prepared to respond effectively to future public health emergencies. The CDC Data Modernization Initiative and Public Health Infrastructure Grants provide opportunities for US agencies to learn from the experiences of their Canadian counterparts and invest in technology to improve public health management.

Summary

Canada’s effective response to the COVID-19 pandemic can be attributed, in part, to their data modernization efforts in the public health sector. Lessons can be learned from Canada’s proactive approach and use of technology, particularly the IBM Panorama system, which helped the country track and contain the spread of the virus. The US can benefit from adopting a similar approach to data modernization in order to improve public health response and better manage future health crises.

FAQs

What is IBM Panorama?

IBM Panorama is an end-to-end public health disease surveillance and immunization system. It was developed in collaboration with Canadian authorities following the SARS outbreak in 2003 and played a key role in Canada’s response to the COVID-19 pandemic.

What are the key lessons from Canada’s response?

The key lessons from Canada’s COVID-19 response include using a data model built for public health, making decisions based on high-quality data, handling large data volumes with system integration, adopting a cloud-native architecture for scalability, prioritizing agile configurability for evolving disease scenarios, empowering end users with customizable systems, and using storytelling to engage stakeholders and the public.

How can the US improve its public health response?

The US can improve its public health response by investing in data modernization, adopting technology solutions that are built for public health, ensuring high-quality data, integrating data systems to avoid silos, adopting cloud-native architecture for scalability, prioritizing agile configurability, empowering end users with customizable systems, and using effective storytelling to engage stakeholders and the public.