Agenda - Day 1

• Get a good start on the day and make connections with industry leadership
• Join “drop-in” roundtables on most topical issues
• Schedule 1-2-1 video meetings with peers
• Gather essential content at virtual exhibit booths

Gain insight into today’s key learnings, take-aways and highlights to map the current situation and help in achieving success from today’s event.

An incredible amount of data has been captured during the COVID-19 pandemic and it’s both enlightening and confusing. This data is particularly robust as it’s coming from not only the healthcare sector but from tech companies as well. The question for analytics professionals is — how do you ensure it is accurate? Develop an action plan for:

• Designing and implementing more analytics into your data
• Creating protocols for better data capture
• Integrating third party data in order to scale your data across all healthcare touchpoints
• Educating staff to understand, trust and use the data generated

Take advantage of the current data deluge to build more complete and accurate data sets.

Despite the COVID-19 pandemic, hospital operations and emergency patient care were still required. Discover how St. Joseph’s Healthcare in Hamilton not only responded to the COVID-19 crisis but maintained operations and developed regional partnerships to deliver on their mandate. Examine their initiatives and strategies to:

• Test, track and vaccinate
• Develop and deploy digital analytic in-house tools to monitor COVID-19
• Quickly work alongside regional and local teams to incorporate data sharing agreements

Benefit from the lessons learned in testing, tracking and maintaining daily operations at St. Joseph’s Hospital Hamilton.

Privacy should not act as a barrier to data utility, health research, security or innovation. Abandon zero-sum thinking! Proactively identify the risks and embed necessary protective measures into your design and data architecture. Apply Privacy by Design (PbD) to:

• Build privacy and data utility into your analytics projects
• Employ an ethical framework in your work
• Enable privacy and freedom to work together in the future

Achieve the highest privacy standards to protect your patients’ information while still gaining business value from your data.

COVID-19 accelerated the adoption of new technologies and organizational structures across all industries. But perhaps none more than the healthcare sector. Join the discussion as we tackle some of the lessons Niagara Region Public Health learned as they scaled up to meet the demands of their COVID-19 response. Source insights to:

• Quickly scale up staffing who are skilled in data capture and analysis to meet increased demands
• Protect data and patient privacy while sharing critical information to trusted teams
• Build effective partnership agreements and establish trust in your collaborative work
• Communicate quickly and clearly with the public on COVID-19 mitigation and transparency

Leverage lessons learned and implement best practices for building data analytics capacity quickly and effectively during COVID-19. 

Artificial intelligence and machine learning are making significant inroads in the healthcare industry. Ranging from common predictive models highlighting patients most at risk and improving clinical decision support at the point of care to automating routine clinical tasks and improving population health management. Gain valuable insights to further implement AI and ML in your organization. Devise a blueprint to:

• Create lasting impact in your organization and on your patient outcomes
• Learn from actual success stories in machine learning and artificial intelligence
• Deliver results in both clinical and operational settings

Position yourself at the forefront of the healthcare industry with a robust ML and AI program.

Visit Virtual Booths, Source Content and Engage in Demos with Industry Experts

• Pose your biggest questions to leading industry experts through 1:1 video conversations or instant messages.
• Experience a live demo or test out a new product. Source leading-edge content from virtual booths.
• Walk away satisfied with solutions to your greatest challenges.

The success of machine learning in healthcare is highly data dependent and it’s important for practitioners to understand where data can be sourced. CIHI plays a critical role in the development of data standards to promote compatibility between provincial health data sources. Hear in-depth expertise on:

• The key challenges in adopting practical AI/ML solutions within the healthcare industry
• How and why this rapidly evolving area in healthcare is gaining traction
• Why “good data” is needed in healthcare

Understand the key role that AI/ML is playing in data analytics and healthcare decision making.

The future of healthcare is going to be a mix of technology and human-centered interactions. Healthcare organizations must prepare by placing more of an emphasis on data analytics and by building  better patient journeys to feed patient-centered algorithms. Create a data-driven strategy to:

• Put method improvement models into place to improve clinical efficiency and remove waste
• Create a data-literate culture that can read, understand and interpret patient data
• Marry data analytics and process improvements to drive improved patient outcomes
• Establish formal governance structures that incorporate patient-centered approaches to healthcare

Determine how to transform your organization to embody a more data-centric culture.

Artificial intelligence and machine learning are making significant inroads in the healthcare industry. Ranging from common predictive models highlighting patients most at risk and improving clinical decision support at the point of care to automating routine clinical tasks and improving population health management. Gain valuable insights to further implement AI and ML in your organization. Devise a blueprint to:

• Create lasting impact in your organization and on your patient outcomes
• Learn from actual success stories in machine learning and artificial intelligence
• Deliver results in both clinical and operational settings

Position yourself at the forefront of the healthcare industry with a robust ML and AI program.

Effective analytics start with improved data literacy. However, there is still confusion surrounding what organizations need to do to not only capture the necessary data but to mobilize it. Bolster your analytics program by improving your organization’s data literacy:

• Establish clear goals and boundaries for determining what your data should accomplish
• Create an action plan to educate teams on appropriate data acquisition and use
• Understand the ‘power plant’ of data and information management

Develop an integrated approach to improve your organization’s data literacy.

One of the most exciting aspects of data analysis is the ability to create robust predictive analytics. Uncover how you can improve diagnoses, treatments and operational effectiveness using predictive analytics. Gather practical tips to:

• Understand what predictive analytics is and what it can and can’t do
• Establish strategies to determine which data to collect and how it will be collected
• Create the capacity to capture and analyze more data

Prepare for the future by developing your own predictive analytics modeling program.

• Meet informally with fellow delegates in “Drop-in” virtual roundtable chats.
• Engage in 1:1 video conversation with peers or vendors.
• Connect with fellow delegates as “recommend matches” based on similar interests and business objectives.