Interventions are the hardest part as disparate data has to be interwoven for behavior change if risk is to be mitigated, says Duke University Health System Chief Analytics Officer Stephen Blackwelder.
The challenge is not so much in the technology development but in the cultural maturity for people to realize what the data can do for them, says Chad Konchak, assistant vice president of Clinical Analytics at NorthShore University HealthSystem.
KVC Health Systems CIO Lonnie Johnson describes the IT and data strategies of his multi-state provider of foster care and adoption services, including its predictive modeling goals and first steps toward AI and machine learning.
It starts with engaging the clinicians and having a team to standardize care to reduce variation for measurable changes, says Srinivasan Suresh, MD, VP at UPMC Children's Hospital of Pittsburgh.
Michael Schwarz, executive director of IS at Indiana University Health System, says start with an understanding of what the data quality issues are and the differences in documentation and in workflow from different providers.
CHOC Children's CIO Anthony Chang, MD, explains why machine intelligence cannot replace human clinicians and that AI and ML will actually make physician and radiologist careers more attractive.
Advocate Aurora Health’s data and analytics heart failure pilot realized a 23 percent reduction in utilization, says Tina Esposito, the company’s chief health information officer.
Boston AI event focuses on how to build healthcare data competency and acquire new AI skills.