HIMSS2022 Looking Forward BKG

HIMSS 2022: Looking Forward

April 20, 2022
· 3 min read

Another year at HIMSS has come and gone and DataRobot remains as energized as ever! This year was a big moment for the DataRobot team. We debuted our growing and dedicated healthcare organization, offered a preview of the DataRobot 8.0 release, and – most importantly – had hundreds of conversations surrounding the impact of AI and the substantial support for the healthcare industry. Whether attendees were partaking in our live demonstrations or simply viewing our stand – the energy and excitement for the future of AI was evident. 

Trends at HIMSS 2022

Over the course of the conference, we noticed several trends. Notably, the vast increase in the presence of big tech, individualized wearable technology, and the rise of retail healthcare. With hundreds of attendees boasting their Oura rings, the advancement of at-home patient monitoring, we witnessed the future of wearable and retail healthcare. Retailers such as CVS and Best Buy have dove into the link between preventative healthcare and clinic convenience, and the study of consumer shopping choices as it relates to health. And as the presence of big tech has increased substantially from previous years, it remains abundantly clear that the healthcare industry is ready to take the next giant leap. Healthcare leaders have seen the need for analytical tools that provide deep insights along with the rapidly changing demands that require Innovative solutions that only AI can provide. 

Why This Matters

At DataRobot, we are excited about the future of individual healthcare data. Whether the data be from wearable devices or nontraditional retail healthcare ecosystems, the ability to access and understand patient data and improve health outcomes is stronger than ever before. We understand the vast amount of data may be intimidating to some. However, with the power of machine learning, we have the power to uncover deep insights and transform consumer health. 

How AI Can Help

Our booth was consistently filled with people asking questions regarding how AI can help them solve their hardest healthcare problems. While there are hundreds of potential use cases, there are three key areas we focused on at HIMSS:

1. Social Determinants of Health (SDOH)

SDOH are variables, often at the community level, that have long been assumed to impact health; however, there was a limited understanding of how to apply this information in a way that was actionable. In the wake of the disparities seen during the pandemic, there is a new commitment among the healthcare community to recognize and address SDOH both within and outside care systems. Use cases include: 

  • Geospatially identifying neighborhood-level conditions (such as type-2 diabetes, COPD, asthma, hypertension and so on)
  • Predicting disease outbreak and spread and identifying high value clinical pathway interventions 

2. Staffing

There is evidence from around the globe that healthcare organizations are struggling to retain and attract clinical staff, and this situation has been exacerbated by the pandemic. However, AI can help. Several of our clients have deployed models that yield real results: one model has been utilized to identify individuals likely to churn in the next six months, so the provider system can be proactive and intervene to assist with comprehensive staffing concerns. Use cases include:

  • Optimizing patients flow
  • Predicting staff surge requirements
  • Optimizing staffing retention. 

3. Disrupted Care

Identifying patients in need of outreach, deciding where to invest in community clinics, or even ensuring follow-up for no-show appointments are opportunities ripe for AI and remain critical for the healthcare industry. Use cases include:

  • Identifying no-show appointments
  • Prioritizing backlogs of patients awaiting treatment 
  • Identifying patients in need of preventative care

These three areas offer a glimpse into the impact that AI can have on the healthcare system. If you are excited about any of these topics or other use cases, please view our Pathfinder Healthcare Solution Accelerators to learn more.

With healthcare providers facing the continuing challenge of COVID-19 and the prospect of rebuilding traditional business post-pandemic, there is no better time for AI to assist in bringing speed, efficiency, trust, and accuracy to solving healthcare’s hardest problems. HIMSS 2022 offered a wonderful opportunity for us to listen, learn, and work towards broader integration of AI in healthcare, and we look forward to HIMSS 2023. 

How AI Can Help the Healthcare Industry Solve Its Hardest Problems
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About the author
Rob O'Neill
Rob O'Neill

Healthcare Field CTO, DataRobot

Rob O’Neill has twenty years’ experience in the healthcare industry and has a passion for the harnessing of data to drive health service transformation and improve patient outcomes. Prior to joining DataRobot as Field CTO for Healthcare, Rob led the delivery of data science and analytics for an integrated healthcare provider and system in the UK. Rob has worked in analytical leadership roles within a variety of healthcare providers within the UK’s National Health Service.

Meet Rob O’Neill
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