Tuesday, June 3, 2025
News PouroverAI
Visit PourOver.AI
No Result
View All Result
  • Home
  • AI Tech
  • Business
  • Blockchain
  • Data Science & ML
  • Cloud & Programming
  • Automation
  • Front-Tech
  • Marketing
  • Home
  • AI Tech
  • Business
  • Blockchain
  • Data Science & ML
  • Cloud & Programming
  • Automation
  • Front-Tech
  • Marketing
News PouroverAI
No Result
View All Result

7 public health data modernization lessons from Canada’s superior COVID-19 response

October 30, 2023
in Blockchain
Reading Time: 5 mins read
0 0
A A
0
Share on FacebookShare on Twitter


Over the first three years of the COVID-19 pandemic, the US suffered over twice the deaths per capita as Canada — over 600,000 potentially avoidable deaths. Experts agree that this was a hard-won victory of Canada’s public health response. While political and demographic realities were a major factor, an unsung hero is the data modernization efforts that helped Canada track and contain the sudden rise in infections and meet the demand for public health services.

When it comes to public health emergencies, Canadian authorities have long been committed to learning from crises, applying technology and transforming systems to position both state and federal agencies for success when the next challenge arrives. Even within imperfect political realities, public health organizations around the world can learn and emulate Canada’s response through data modernization, potentially saving millions of lives in the next public health emergency.

A proactive approach to the threat of a global health crisis

After the SARS outbreak in 2003, federal and provincial governments in Canada recognized that their existing public health systems and IT were inadequate. Canadian authorities proactively worked with IBM to develop a solution known as IBM Panorama, an end-to-end public health disease surveillance and immunization system. This solution would later be key to Canadian public health agencies’ response to COVID-19.

Meanwhile, across the US, public health officials continued to use paper-based systems that would later fail to keep up with the explosive spread of COVID-19.

In the years following the SARS outbreak, the business of public health largely returned to steady-state focus. The day-to-day activities of public health agencies consisted primarily of dealing with traditional vaccines, diseases and conditions.

During this period, Panorama helped Canadian authorities deal with a wide range of public health functions, including case investigation and outbreak management, as well as immunization and vaccine inventory management.

When the COVID-19 pandemic hit, health agencies were immediately thrown into the spotlight. Suddenly, public health agencies had to deal with:

A novel disease for which no standards (such as case definitions) existed

A rapidly evolving disease where variants, signs and symptoms, and interventions changed quickly

High case volumes and extensive contact tracing, which necessitated employment of new public health workers to meet demand (with limited training available)

New vaccines and evolving protocols, such as mixing and matching doses with different vaccines

The need to communicate health risks to the public based on rapidly developing data and uncertain interpretations

Though both the US and Canada faced unprecedented challenges during this time, the Canadian provinces that were equipped with Panorama were better prepared to respond to the COVID-19 pandemic. Unlike many US counterparts, they had a powerful enterprise-grade solution that was specifically designed for public health. This solution had the capability to manage large scale immunization events and disease surveillance.

Given global travel and climate change, it is reasonable to anticipate that another pandemic (and the problems listed above) could be right around the corner.

This time, the US can learn from the experiences and preparedness of Canada’s public health agencies. A successful public health response to a future pandemic will rely on collecting and managing critical data, investing in smart, capable and flexible data modernization systems, and preparing people with the proper knowledge and skills.

Lesson 1: Use a data model built for public health.

Canadian provinces used a disease surveillance solution featuring a person-centered public health data model, which meant it captured the requisite information needed for public health professionals to forecast and identify emerging trends and outbreaks (as well as analyze interventions and report to stakeholders). US public health agencies would benefit from choosing disease surveillance solutions that come with a proven, public health data model that offers relevant terminology, relationships and models.

Lesson 2: Make key decisions with high-quality data.

High-quality data is the bedrock of any public health response. US public health agencies should seek solutions that ingest data in multiple formats and have built-in processes for data cleansing to maintain the integrity of data. Data silos often occur when data is not shared or accessible, leading to workarounds and incomplete information. It is crucial to establish data sharing agreements in advance of an emergency.

Lesson 3: Handle data volumes with system integration.

Both Canadian and US public health agencies were overwhelmed by huge volumes of data during the COVID-19 pandemic. US agencies invested emergency COVID-19 funding into new case management and contact training solutions. However, these were often stand-alone solutions that didn’t address the underlying issues of siloed, incomplete or duplicative data.

Canada used integrated public health information systems, like Panorama, for seamless data ingestion, cleansing and import processing. Through systems integration via open APIs and other means of integrating data into patient health records, this served as the single source of truth for all exposure, case investigation, contact tracing, outbreak management and case management information for each resident.

Lesson 4: Adopt a cloud-native architecture to ensure elastic scalability.

Many of the investments in new technology solutions from the COVID-19 pandemic are now being sunset. For sustainable investments, public health agencies need the ability to scale data and information systems to the data volumes experienced during steady-state operations as well as during emergency responses. Investing in a cloud-native solution offers a flexible architecture and a future-proof solution that allows the public health agency to have elastic scalability.

Lesson 5: Prioritize agile configurability to adapt to developing disease scenarios.

Canadian public health agencies benefited from IBM Panorama’s ability to serve all 100+ reportable diseases and conditions. When the novel coronavirus started to emerge from lab tests, signs and symptoms led epidemiologists to code this data in a parking lot within Panorama, until LOINC and SNOWMED officially coded COVID-19. This kind of configurability is necessary to adapt to emerging diseases and conditions, instead of systems that only serve single diseases and conditions.

Lesson 6: Empower end users to respond rapidly with an easy, customizable system.

The public health field has experienced a large turnover as people retire or experience burnout. Data modernization initiatives afford public health agencies the opportunity to attract new talent by offering solutions using human-centered design. These solutions use augmented intelligence, guided workflows, machine learning and even consider generative AI to embed domain expertise within workflows and advance the efficiency and training of new users.

Lesson 7: Use storytelling to engage stakeholders and the public.

While epidemiologists are equipped to report and analyze data and communicate it to other scientists, accessible storytelling is crucial to fostering greater trust and impact when translating science into public communications and public policy. In Canada, there are “data storytelling” trainings for public health professionals that empower public health information officers and state health officers to frame data insights to maximize public understanding and action.

Create a proactive data modernization plan to prepare for the unexpected

COVID-19 revealed opportunities to change the way public health is managed, as well as the need to invest in technology. With the CDC Data Modernization Initiative and Public Health Infrastructure Grants, now is the time for US public health agencies to learn from fellow public health agencies, like those in Canada, as they modernize.

By taking a proactive data modernization approach, US public health agencies can manage steady-state operations and be better prepared to respond to the unknowns of the next public health emergency.

Incorporate these lessons into your data modernization journey

Marketing Lead, State Local & Ed Government Industry

Associate Partner, Health & Human Services and Public Health, State & Local Government Industry



Source link

Tags: CanadasCOVID19datahealthLessonsmodernizationPublicresponsesuperior
Previous Post

More China companies buyback shares as Beijing seeks to stabilise market By Reuters

Next Post

Data Science vs Machine Learning vs Artificial Intelligence vs Big Data

Related Posts

5 SLA metrics you should be monitoring
Blockchain

5 SLA metrics you should be monitoring

June 10, 2024
10BedICU Leverages OpenAI’s API to Revolutionize Critical Care in India
Blockchain

10BedICU Leverages OpenAI’s API to Revolutionize Critical Care in India

June 9, 2024
Arkham: US Government Seizes $300M from Alameda Research Accounts
Blockchain

Arkham: US Government Seizes $300M from Alameda Research Accounts

June 8, 2024
Fake Musk Live Streams Flood YouTube During SpaceX Launch
Blockchain

Fake Musk Live Streams Flood YouTube During SpaceX Launch

June 7, 2024
How to Track Crypto Transactions for Taxes?
Blockchain

How to Track Crypto Transactions for Taxes?

June 7, 2024
NVIDIA Enhances Low-Resolution SDR Video with RTX Video SDK Release
Blockchain

NVIDIA Enhances Low-Resolution SDR Video with RTX Video SDK Release

June 7, 2024
Next Post
Data Science vs Machine Learning vs Artificial Intelligence vs Big Data

Data Science vs Machine Learning vs Artificial Intelligence vs Big Data

Kickstart Your Business to the Next Level with AI Inferencing

Kickstart Your Business to the Next Level with AI Inferencing

Top 5 Skills for automation, PLC HMI & SCADA Engineer in 2022 – 2050

Top 5 Skills for automation, PLC HMI & SCADA Engineer in 2022 - 2050

Leave a Reply Cancel reply

Your email address will not be published. Required fields are marked *

  • Trending
  • Comments
  • Latest
Is C.AI Down? Here Is What To Do Now

Is C.AI Down? Here Is What To Do Now

January 10, 2024
Accenture creates a regulatory document authoring solution using AWS generative AI services

Accenture creates a regulatory document authoring solution using AWS generative AI services

February 6, 2024
23 Plagiarism Facts and Statistics to Analyze Latest Trends

23 Plagiarism Facts and Statistics to Analyze Latest Trends

June 4, 2024
Managing PDFs in Node.js with pdf-lib

Managing PDFs in Node.js with pdf-lib

November 16, 2023
Turkish Airlines Marketing Strategy: Beyond “Globally Yours”

Turkish Airlines Marketing Strategy: Beyond “Globally Yours”

May 29, 2024
The 15 Best Python Courses Online in 2024 [Free + Paid]

The 15 Best Python Courses Online in 2024 [Free + Paid]

April 13, 2024
Can You Guess What Percentage Of Their Wealth The Rich Keep In Cash?

Can You Guess What Percentage Of Their Wealth The Rich Keep In Cash?

June 10, 2024
AI Compared: Which Assistant Is the Best?

AI Compared: Which Assistant Is the Best?

June 10, 2024
How insurance companies can use synthetic data to fight bias

How insurance companies can use synthetic data to fight bias

June 10, 2024
5 SLA metrics you should be monitoring

5 SLA metrics you should be monitoring

June 10, 2024
From Low-Level to High-Level Tasks: Scaling Fine-Tuning with the ANDROIDCONTROL Dataset

From Low-Level to High-Level Tasks: Scaling Fine-Tuning with the ANDROIDCONTROL Dataset

June 10, 2024
UGRO Capital: Targeting to hit milestone of Rs 20,000 cr loan book in 8-10 quarters: Shachindra Nath

UGRO Capital: Targeting to hit milestone of Rs 20,000 cr loan book in 8-10 quarters: Shachindra Nath

June 10, 2024
Facebook Twitter LinkedIn Pinterest RSS
News PouroverAI

The latest news and updates about the AI Technology and Latest Tech Updates around the world... PouroverAI keeps you in the loop.

CATEGORIES

  • AI Technology
  • Automation
  • Blockchain
  • Business
  • Cloud & Programming
  • Data Science & ML
  • Digital Marketing
  • Front-Tech
  • Uncategorized

SITEMAP

  • Disclaimer
  • Privacy Policy
  • DMCA
  • Cookie Privacy Policy
  • Terms and Conditions
  • Contact us

Copyright © 2023 PouroverAI News.
PouroverAI News

No Result
View All Result
  • Home
  • AI Tech
  • Business
  • Blockchain
  • Data Science & ML
  • Cloud & Programming
  • Automation
  • Front-Tech
  • Marketing

Copyright © 2023 PouroverAI News.
PouroverAI News

Welcome Back!

Login to your account below

Forgotten Password? Sign Up

Create New Account!

Fill the forms bellow to register

All fields are required. Log In

Retrieve your password

Please enter your username or email address to reset your password.

Log In