We’re excited to share the topic and questions for this week’s #HITsm chat happening Friday, 8/11 at Noon ET (9 AM PT). This week’s chat will be hosted by Prashant Natarajan (@natarpr) on the topic of “More About Artificial Intelligence in Healthcare.” Be sure to also check out Prashant’s HIMSS best selling book Demystifying Big Data and Machine Learning for Healthcare to learn about his perspectives and insights into the topic.
Healthcare transformation requires us to continually look at new and better ways to manage insights – both within and outside the organization today. Increasingly, the ability to glean and operationalize new insights efficiently as a byproduct of an organization’s day-to-day operations is becoming vital to hospitals and health systems ability to survive and prosper. One of the long-standing challenges in healthcare informatics has been the ability to deal with the sheer variety and volume of disparate healthcare data and the increasing need to derive veracity and value out of it.
The potential for big data in healthcare – especially given the trends discussed earlier is as bright as any other industry. The benefits that big data analytics, AI, and machine learning can provide for healthier patients, happier providers, and cost-effective care are real. The future of precision medicine, population health management, clinical research, and financial performance will include an increased role for machine-analyzed insights, discoveries, and all-encompassing analytics.
This chat explores participants thoughts and feelings about the future of artificial intelligence in the healthcare industry and how healthcare organizations might leverage artificial intelligence to discover new business value, use cases, and knowledge.
Note: For purpose of this chat, “artificial intelligence” can mean predictive analytics, machine learning, big data analytics, natural language processing and contextually intelligent agents.
- Artificial intelligence
- A Tale of 2 T’s: When Analytics and Artificial Intelligence Go Bad
- The evolution of machine learning
- Are Healthcare Data Streams Rich Enough To Support AI?
- The dangers of AI in health care: risk homeostasis and automation bias
Questions we will explore in this week’s #HITsm chat include:
T1: What words or short phrases convey your current thoughts & feelings about ‘artificial intelligence’ in the healthcare space? #HITsm #AI
T2: What are big & small steps healthcare can take to leverage big data & machine learning for population health & personalized care? #HITsm
T3: Which areas of healthcare might be most positively impacted by artificial intelligence? #HITsm #AI
T4: What are some areas within healthcare that will likely NOT be improved or replaced by artificial intelligence? #HITsm #AI
T5: What lessons learned from early days of ‘advanced analytics’ must not be forgotten as use of artificial intelligence expands? #HITsm #AI
Bonus: How is your organization preparing for the application and use of artificial intelligence in healthcare? #HITsm #AI
8/25 – Consumer Data Liquidity – The Road So Far, The Road Ahead
Hosted by Greg Meyer (@Greg_Meyer93)
We look forward to learning from the #HITsm community! As always, let us know if you’d like to host a future #HITsm chat or if you know someone you think we should invite to host.
If you’re searching for the latest #HITsm chat, you can always find the latest #HITsm chat and schedule of chats here.