Healthcare Analytics Summit 20

Sept. 1 – 3, 2020


We are now accepting presenter nominations for Breakout Sessions, the Analytics Walkabout, and the Machine Learning Marketplace. Please submit your proposal by filling out the submission form below and submitting it to by Friday, February 21, 2020.

With an expected sell-out crowd of over 1500 attendees, the Healthcare Analytics Summit is the premier, highest-attended industry event of its kind. The goal at HAS is to inspire and drive outcomes improvement by providing numerous examples of leading-edge analytics best practices.



We’re Looking for Presenters for the Following:

  • Breakout Sessions – These are approximately 55 minutes, consisting of about 35-40 minutes of content, 10-15 minutes of Q&A, and 5 minutes of polling, feedback, and introduction. We have a personalized support process to guide you through developing the presentation. We are selective when choosing Breakout presentation speakers. Breakout presentations occur on Wednesday, September 2 and Thursday, September 3.
  • The Analytics Walkabout – This is a unique opportunity to engage one-on-one with audience members to share successes. The Analytics Walkabout consists of 24 improvement case study stations and is the kickoff activity for HAS 20, from 6:00 – 9:00 pm on Tuesday, September 1. The walkabout is less formal and, in general, is a 10-minute presentation followed by individual discussions.
  • The Machine Learning Marketplace – This exciting event continues to grow in popularity. Once again, we will be highlighting examples of machine learning and AI in healthcare, in an interactive walkabout format where attendees can ask presenters in-depth questions about their machine learning projects. The Machine Learning Marketplace presentations will take place either on Tuesday evening, September 1 or on the afternoon of Thursday, September 3.

Presenter Topics

We are particularly interested in the presentations on the following topics where data and analytics were used to achieve value:

  • Innovative machine learning:
    • AI, Machine learning, NLP, or predictive analytics use cases.
    • Best practices or lessons learned (what to do, what to avoid) in healthcare machine learning.
    • Addressing the AI bias and equity challenge.
    • Integrating data science or data scientists into your analytics or analytics organization.
    • Moving from predictive to prescriptive analytics.
  • Innovative data, analytics, and analytics transformation examples:
    • Best practices in becoming a data-driven organization.
    • Transforming your analytics team.
    • How to deliver data to the masses.
    • Effectively telling stories with data and data visualization.
    • The softer skills side of data and analytics.
    • Driving data and decision-making back into the EMR at the point of care (i.e., closed-loop analytics).
  • Population health management:
    • Care management, quality measures performance, operations, contracting.
    • Effective use of social determinants of health.
    • Patient reported outcomes.
    • Innovative community and health system partnerships.
  • Innovative data and digital transformation examples:
    • Digital therapeutics.
    • Virtual primary care.
    • Innovative mobile capture and tracking solutions.
    • Digitizing key healthcare processes.
    • Virtual reality.
    • Pricing transparency.
  • Increased revenue:
    • Increased payments (improved collection rate, case acceleration, payer contracts).
    • Increased volume (capacity, access, reduced referral leakage, care expansion).
    • Expansion (expanded service lines, mergers and acquisitions, life science trials revenue, digital retail).
  • Reduced costs:
    • Pricing transparency and activity-based costing.
    • Reduced labor costs, staffing costs, provider contracts.
    • Optimized supply chain (pharmacy, surgical supplies, general supplies, blood utilization, etc.).
    • Other areas (e.g., reduced clinical support service costs, improved analytics efficiencies, or reduced “low-value” care).
    • Payer/provider collaboration and best practices.
  • Improved quality:
    • Improved clinical operations (reduced readmissions, service lines improvements, research and operations).
    • Improved patient safety (reduced safety events and infections, voluntary reporting, liability, and safety excellence).
  • Life Science:
    • Precision medicine.
    • Digital medicine.
    • Improve trials and trials recruitment.
    • Biotech.
    • Small-n diseases.

Please submit your proposal by filling out the submission form below and submitting it to by Friday, February 21, 2020.



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